1
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Manzhos S, Lüder J, Ihara M. Machine learning of kinetic energy densities with target and feature smoothing: Better results with fewer training data. J Chem Phys 2023; 159:234115. [PMID: 38112506 DOI: 10.1063/5.0175689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023] Open
Abstract
Machine learning (ML) of kinetic energy functionals (KEFs), in particular kinetic energy density (KED) functionals, is a promising way to construct KEFs for orbital-free density functional theory (DFT). Neural networks and kernel methods including Gaussian process regression (GPR) have been used to learn Kohn-Sham (KS) KED from density-based descriptors derived from KS DFT calculations. The descriptors are typically expressed as functions of different powers and derivatives of the electron density. This can generate large and extremely unevenly distributed datasets, which complicates effective application of ML techniques. Very uneven data distributions require many training datapoints, can cause overfitting, and can ultimately lower the quality of an ML KED model. We show that one can produce more accurate ML models from fewer data by working with smoothed density-dependent variables and KED. Smoothing palliates the issue of very uneven data distributions and associated difficulties of sampling while retaining enough spatial structure necessary for working within the paradigm of KEDF. We use GPR as a function of smoothed terms of the fourth order gradient expansion and KS effective potential and obtain accurate and stable (with respect to different random choices of training points) kinetic energy models for Al, Mg, and Si simultaneously from as few as 2000 samples (about 0.3% of the total KS DFT data). In particular, accuracies on the order of 1% in a measure of the quality of energy-volume dependence B'=EV0-ΔV-2EV0+E(V0+ΔV)ΔV/V02 (where V0 is the equilibrium volume and ΔV is a deviation from it) are obtained simultaneously for all three materials.
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Affiliation(s)
- Sergei Manzhos
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552, Japan
| | - Johann Lüder
- Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No. 70, Lien-Hai Road, Kaohsiung 80424, Taiwan
- Center of Crystal Research, National Sun Yat-sen University, No. 70, Lien-Hai Road, Kaohsiung 80424, Taiwan
- Center for Theoretical and Computational Physics, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
| | - Manabu Ihara
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552, Japan
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2
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Talmazan RA, Podewitz M. PyConSolv: A Python Package for Conformer Generation of (Metal-Containing) Systems in Explicit Solvent. J Chem Inf Model 2023; 63:5400-5407. [PMID: 37606893 PMCID: PMC10498442 DOI: 10.1021/acs.jcim.3c00798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Indexed: 08/23/2023]
Abstract
We introduce PyConSolv, a freely available Python package that automates the generation of conformers of metal- and nonmetal-containing complexes in explicit solvent, through classical molecular dynamics simulations. Using a streamlined workflow and interfacing with widely used computational chemistry software, PyConSolv is an all-in-one tool for the generation of conformers in any solvent. Input requirements are minimal; only the geometry of the structure and the desired solvent in xyz (XMOL) format are needed. The package can also account for charged systems, by including arbitrary counterions in the simulation. A bonded model parametrization is performed automatically, utilizing AmberTools, ORCA, and Multiwfn software packages. PyConSolv provides a selection of preparametrized solvents and counterions for use in classical molecular dynamics simulations. We show the applicability of our package on a number of (transition-metal-containing) systems. The software is provided open source and free of charge.
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Affiliation(s)
- R. A. Talmazan
- Institute
of Materials Chemistry, TU Wien, Getreidemarkt 9, A-1060 Wien, Austria
| | - M. Podewitz
- Institute
of Materials Chemistry, TU Wien, Getreidemarkt 9, A-1060 Wien, Austria
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3
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Sun Q. Exact exchange with range-separated algorithm for thermodynamic limit of periodic Hartree-Fock theory. J Chem Phys 2023; 159:024108. [PMID: 37428044 DOI: 10.1063/5.0155815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/20/2023] [Indexed: 07/11/2023] Open
Abstract
The expensive cost of computing exact exchange in periodic systems limits the application range of density functional theory with hybrid functionals. To reduce the computational cost of exact change, we present a range-separated algorithm to compute electron repulsion integrals for Gaussian-type crystal basis. The algorithm splits the full-range Coulomb interactions into short-range and long-range parts, which are, respectively, computed in real and reciprocal space. This approach significantly reduces the overall computational cost, as integrals can be efficiently computed in both regions. The algorithm can efficiently handle large numbers of k points with limited central processing unit (CPU) and memory resources. As a demonstration, we performed an all-electron k-point Hartree-Fock calculation for LiH crystal with one million Gaussian basis functions, which was completed on a desktop computer in 1400 CPU hours.
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Affiliation(s)
- Qiming Sun
- Quantum Engine LLC, Lacey, Washington 98516, USA
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4
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Budiutama G, Li R, Manzhos S, Ihara M. Hybrid Density Functional Tight Binding (DFTB)─Molecular Mechanics Approach for a Low-Cost Expansion of DFTB Applicability. J Chem Theory Comput 2023. [PMID: 37450317 DOI: 10.1021/acs.jctc.3c00310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
The density functional-based tight binding (DFTB) method has seen a rise in adoption for materials modeling, as it offers significant improvement in scalability with accuracy comparable to the density functional theory (DFT) when good parameterizations exist. The cost reduction in DFTB compared to DFT is achieved by the pre-parameterization of the elements of the Hamiltonian matrix as well as the repulsion potential between all pairs of atoms. Parameterization for new systems with accuracies competitive with DFT in specific applications requires specialized manpower and computational resources. This prevents the application of the DFTB method to systems for which it was not parameterized. In this work, we explore an approach to address the problem of missing parameters of DFTB by modeling the interactions with missing Slater-Koster parameters with an interatomic interaction potential. When the distance between two atoms modeled at the force-field level is sufficiently large, the approach results in accurate structural and electronic properties. The resulting calculation is therefore a hybrid between DFTB and molecular mechanics, a pure DFTB for atoms with a complete set of interatomic parameterizations, and a mix between DFTB and molecular mechanics for atoms with a missing interatomic parameterization. The approach is expected to be particularly useful for hybrid materials and interfaces. The method is tested on the examples of 2D materials, mixed oxides, and a large-scale calculation of an oxide-oxide interface.
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Affiliation(s)
- Gekko Budiutama
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552 Japan
| | - Ruicheng Li
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552 Japan
| | - Sergei Manzhos
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552 Japan
| | - Manabu Ihara
- School of Materials and Chemical Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552 Japan
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5
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Alizadeh Sahraei A, Azizi D, Mokarizadeh AH, Boffito DC, Larachi F. Emerging Trends of Computational Chemistry and Molecular Modeling in Froth Flotation: A Review. ACS ENGINEERING AU 2023; 3:128-164. [PMID: 37362006 PMCID: PMC10288516 DOI: 10.1021/acsengineeringau.2c00053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 06/28/2023]
Abstract
Froth flotation is the most versatile process in mineral beneficiation, extensively used to concentrate a wide range of minerals. This process comprises mixtures of more or less liberated minerals, water, air, and various chemical reagents, involving a series of intermingled multiphase physical and chemical phenomena in the aqueous environment. Today's main challenge facing the froth flotation process is to gain atomic-level insights into the properties of its inherent phenomena governing the process performance. While it is often challenging to determine these phenomena via trial-and-error experimentations, molecular modeling approaches not only elicit a deeper understanding of froth flotation but can also assist experimental studies in saving time and budget. Thanks to the rapid development of computer science and advances in high-performance computing (HPC) infrastructures, theoretical/computational chemistry has now matured enough to successfully and gainfully apply to tackle the challenges of complex systems. In mineral processing, however, advanced applications of computational chemistry are increasingly gaining ground and demonstrating merit in addressing these challenges. Accordingly, this contribution aims to encourage mineral scientists, especially those interested in rational reagent design, to become familiarized with the necessary concepts of molecular modeling and to apply similar strategies when studying and tailoring properties at the molecular level. This review also strives to deliver the state-of-the-art integration and application of molecular modeling in froth flotation studies to assist either active researchers in this field to disclose new directions for future research or newcomers to the field to initiate innovative works.
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Affiliation(s)
- Abolfazl Alizadeh Sahraei
- Department
of Chemical Engineering, Université
Laval, 1065 Avenue de la Médecine, Québec, Québec G1V 0A6, Canada
| | - Dariush Azizi
- Department
of Chemical Engineering, École Polytechnique
de Montréal, 2900 Boulevard Édouard-Montpetit, Montréal H3T 1J4, Canada
| | - Abdol Hadi Mokarizadeh
- School
of Polymer Science and Polymer Engineering, University of Akron, Akron, Ohio 44325, United States
| | - Daria Camilla Boffito
- Department
of Chemical Engineering, École Polytechnique
de Montréal, 2900 Boulevard Édouard-Montpetit, Montréal H3T 1J4, Canada
| | - Faïçal Larachi
- Department
of Chemical Engineering, Université
Laval, 1065 Avenue de la Médecine, Québec, Québec G1V 0A6, Canada
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6
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Woo J, Kim S, Kim WY. Gaussian-Approximated Poisson Preconditioner for Iterative Diagonalization in Real-Space Density Functional Theory. J Phys Chem A 2023; 127:3883-3893. [PMID: 37094552 DOI: 10.1021/acs.jpca.2c09111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Various real-space methods optimized on massive parallel computers have been developed for efficient large-scale density functional theory (DFT) calculations of materials and biomolecules. The iterative diagonalization of the Hamiltonian matrix is a computational bottleneck in real-space DFT calculations. Despite the development of various iterative eigensolvers, the absence of efficient real-space preconditioners has hindered their overall efficiency. An efficient preconditioner must satisfy two conditions: appropriate acceleration of the convergence of the iterative process and inexpensive computation. This study proposed a Gaussian-approximated Poisson preconditioner (GAPP) that satisfied both conditions and was suitable for real-space methods. A low computational cost was realized through the Gaussian approximation of a Poisson Green's function. Fast convergence was achieved through the proper determination of Gaussian coefficients to fit the Coulomb energies. The performance of GAPP was evaluated for several molecular and extended systems, and it showed the highest efficiency among the existing preconditioners adopted in real-space codes.
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Affiliation(s)
- Jeheon Woo
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Seonghwan Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Woo Youn Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
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7
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Lebedeva IV, García A, Artacho E, Ordejón P. Modular implementation of the linear- and cubic-scaling orbital minimization methods in electronic structure codes using atomic orbitals. ROYAL SOCIETY OPEN SCIENCE 2023; 10:230063. [PMID: 37122948 PMCID: PMC10130719 DOI: 10.1098/rsos.230063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/29/2023] [Indexed: 05/03/2023]
Abstract
We present a code modularization approach to design efficient and massively parallel cubic- and linear-scaling solvers for electronic structure calculations using atomic orbitals. The modular implementation of the orbital minimization method, in which linear algebra and parallelization issues are handled via external libraries, is demonstrated in the SIESTA code. The distributed block compressed sparse row (DBCSR) and scalable linear algebra package (ScaLAPACK) libraries are used for algebraic operations with sparse and dense matrices, respectively. The MatrixSwitch and libOMM libraries, recently developed within the Electronic Structure Library, facilitate switching between different matrix formats and implement the energy minimization. We show results comparing the performance of several cubic-scaling algorithms, and also demonstrate the parallel performance of the linear-scaling solvers, and their supremacy over the cubic-scaling solvers for insulating systems with sizes of several hundreds of atoms.
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Affiliation(s)
- Irina V. Lebedeva
- CIC nanoGUNE BRTA, Donostia-San Sebastián 20018, Spain
- Catalan Institute of Nanoscience and Nanotechnology—ICN2 (CSIC and BIST), Campus UAB, Bellaterra 08193, Spain
- Simune Atomistics, Avenida de Tolosa 76, Donostia-San Sebastián 20018, Spain
| | - Alberto García
- Institut de Ciència de Materials de Barcelona (ICMAB-CSIC), Bellaterra 08193, Spain
| | - Emilio Artacho
- CIC nanoGUNE BRTA, Donostia-San Sebastián 20018, Spain
- Donostia International Physics Center DIPC, Donostia-San Sebastián 20018, Spain
- Theory of Condensed Matter, Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE, UK
- Ikerbasque, Basque Foundation for Science, Bilbao 48011, Spain
| | - Pablo Ordejón
- Catalan Institute of Nanoscience and Nanotechnology—ICN2 (CSIC and BIST), Campus UAB, Bellaterra 08193, Spain
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8
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Vuong VQ, Cevallos C, Hourahine B, Aradi B, Jakowski J, Irle S, Camacho C. Accelerating the density-functional tight-binding method using graphical processing units. J Chem Phys 2023; 158:084802. [PMID: 36859078 DOI: 10.1063/5.0130797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Acceleration of the density-functional tight-binding (DFTB) method on single and multiple graphical processing units (GPUs) was accomplished using the MAGMA linear algebra library. Two major computational bottlenecks of DFTB ground-state calculations were addressed in our implementation: the Hamiltonian matrix diagonalization and the density matrix construction. The code was implemented and benchmarked on two different computer systems: (1) the SUMMIT IBM Power9 supercomputer at the Oak Ridge National Laboratory Leadership Computing Facility with 1-6 NVIDIA Volta V100 GPUs per computer node and (2) an in-house Intel Xeon computer with 1-2 NVIDIA Tesla P100 GPUs. The performance and parallel scalability were measured for three molecular models of 1-, 2-, and 3-dimensional chemical systems, represented by carbon nanotubes, covalent organic frameworks, and water clusters.
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Affiliation(s)
- Van-Quan Vuong
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Caterina Cevallos
- School of Chemistry, University of Costa Rica, San José 11501-2060, Costa Rica
| | - Ben Hourahine
- SUPA, Department of Physics, The John Anderson Building, 107 Rottenrow East, Glasgow G4 0NG, United Kingdom
| | - Bálint Aradi
- Bremen Center for Computational Materials Science, Universität Bremen, Bremen, Germany
| | - Jacek Jakowski
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - Stephan Irle
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - Cristopher Camacho
- School of Chemistry, University of Costa Rica, San José 11501-2060, Costa Rica
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9
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Pederson R, Kozlowski J, Song R, Beall J, Ganahl M, Hauru M, Lewis AGM, Yao Y, Mallick SB, Blum V, Vidal G. Large Scale Quantum Chemistry with Tensor Processing Units. J Chem Theory Comput 2023; 19:25-32. [PMID: 36508260 DOI: 10.1021/acs.jctc.2c00876] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
We demonstrate the use of Googles cloud-based Tensor Processing Units (TPUs) to accelerate and scale up conventional (cubic-scaling) density functional theory (DFT) calculations. Utilizing 512 TPU cores, we accomplish the largest such DFT computation to date, with 247848 orbitals, corresponding to a cluster of 10327 water molecules with 103270 electrons, all treated explicitly. Our work thus paves the way toward accessible and systematic use of conventional DFT, free of any system-specific constraints, at unprecedented scales.
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Affiliation(s)
- Ryan Pederson
- Department of Physics and Astronomy, University of California, Irvine, California92617, United States.,X, the Moonshot Factory, Mountain View, California94043, United States.,Sandbox@Alphabet, Mountain View, California94043, United States
| | - John Kozlowski
- X, the Moonshot Factory, Mountain View, California94043, United States.,Sandbox@Alphabet, Mountain View, California94043, United States.,Department of Chemistry, University of California, Irvine, California92617, United States
| | - Ruyi Song
- X, the Moonshot Factory, Mountain View, California94043, United States.,Sandbox@Alphabet, Mountain View, California94043, United States.,Department of Chemistry, Duke University, Durham, North Carolina27708, United States
| | - Jackson Beall
- Sandbox@Alphabet, Mountain View, California94043, United States.,SandboxAQ, Palo Alto, California94304, United States
| | - Martin Ganahl
- Sandbox@Alphabet, Mountain View, California94043, United States.,SandboxAQ, Palo Alto, California94304, United States
| | - Markus Hauru
- Sandbox@Alphabet, Mountain View, California94043, United States.,The Alan Turing Institute, 96 Euston Road, LondonNW1 2DB, England, U.K
| | - Adam G M Lewis
- Sandbox@Alphabet, Mountain View, California94043, United States.,SandboxAQ, Palo Alto, California94304, United States
| | - Yi Yao
- Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina27708, United States
| | - Shrestha Basu Mallick
- X, the Moonshot Factory, Mountain View, California94043, United States.,Sandbox@Alphabet, Mountain View, California94043, United States
| | - Volker Blum
- Department of Chemistry, Duke University, Durham, North Carolina27708, United States.,Thomas Lord Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina27708, United States
| | - Guifre Vidal
- X, the Moonshot Factory, Mountain View, California94043, United States.,Sandbox@Alphabet, Mountain View, California94043, United States.,Google Quantum AI, Mountain View, California94043, United States
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10
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Ruth M, Gerbig D, Schreiner PR. Machine Learning of Coupled Cluster (T)-Energy Corrections via Delta (Δ)-Learning. J Chem Theory Comput 2022; 18:4846-4855. [PMID: 35816588 DOI: 10.1021/acs.jctc.2c00501] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Accurate thermochemistry is essential in many chemical disciplines, such as astro-, atmospheric, or combustion chemistry. These areas often involve fleetingly existent intermediates whose thermochemistry is difficult to assess. Whenever direct calorimetric experiments are infeasible, accurate computational estimates of relative molecular energies are required. However, high-level computations, often using coupled cluster theory, are generally resource-intensive. To expedite the process using machine learning techniques, we generated a database of energies for small organic molecules at the CCSD(T)/cc-pVDZ, CCSD(T)/aug-cc-pVDZ, and CCSD(T)/cc-pVTZ levels of theory. Leveraging the power of deep learning by employing graph neural networks, we are able to predict the effect of perturbatively included triples (T), that is, the difference between CCSD and CCSD(T) energies, with a mean absolute error of 0.25, 0.25, and 0.28 kcal mol-1 (R2 of 0.998, 0.997, and 0.998) with the cc-pVDZ, aug-cc-pVDZ, and cc-pVTZ basis sets, respectively. Our models were further validated by application to three validation sets taken from the S22 Database as well as to a selection of known theoretically challenging cases.
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Affiliation(s)
- Marcel Ruth
- Institute of Organic Chemistry, Justus Liebig University, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
| | - Dennis Gerbig
- Institute of Organic Chemistry, Justus Liebig University, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
| | - Peter R Schreiner
- Institute of Organic Chemistry, Justus Liebig University, Heinrich-Buff-Ring 17, 35392 Giessen, Germany
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11
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Genin SN, Ryabinkin IG, Paisley NR, Whelan SO, Helander MG, Hudson ZM. Estimating Phosphorescent Emission Energies in Ir
III
Complexes Using Large‐Scale Quantum Computing Simulations**. Angew Chem Int Ed Engl 2022; 61:e202116175. [DOI: 10.1002/anie.202116175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Scott N. Genin
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | - Ilya G. Ryabinkin
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | - Nathan R. Paisley
- Department of Chemistry The University of British Columbia 2036 Main Mall Vancouver British Columbia V6T 1Z1 Canada
| | - Sarah O. Whelan
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | | | - Zachary M. Hudson
- Department of Chemistry The University of British Columbia 2036 Main Mall Vancouver British Columbia V6T 1Z1 Canada
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12
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Genin SN, Ryabinkin IG, Paisley NR, Whelan SO, Helander MG, Hudson ZM. Estimating Phosphorescent Emission Energies in Ir
III
Complexes Using Large‐Scale Quantum Computing Simulations**. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202116175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Scott N. Genin
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | - Ilya G. Ryabinkin
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | - Nathan R. Paisley
- Department of Chemistry The University of British Columbia 2036 Main Mall Vancouver British Columbia V6T 1Z1 Canada
| | - Sarah O. Whelan
- OTI Lumionics Inc. 100 College St. #351 Toronto Ontario M5G 1L5 Canada
| | | | - Zachary M. Hudson
- Department of Chemistry The University of British Columbia 2036 Main Mall Vancouver British Columbia V6T 1Z1 Canada
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13
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Clark AE, Adams H, Hernandez R, Krylov AI, Niklasson AMN, Sarupria S, Wang Y, Wild SM, Yang Q. The Middle Science: Traversing Scale In Complex Many-Body Systems. ACS CENTRAL SCIENCE 2021; 7:1271-1287. [PMID: 34471670 PMCID: PMC8393217 DOI: 10.1021/acscentsci.1c00685] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A roadmap is developed that integrates simulation methodology and data science methods to target new theories that traverse the multiple length- and time-scale features of many-body phenomena.
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Affiliation(s)
- Aurora E. Clark
- Department of Chemistry, Washington State University, Pullman, Washington 99163, United States
| | - Henry Adams
- Department of Mathematics, Colorado State
University, Fort Collins, Colorado 80523, United States
| | - Rigoberto Hernandez
- Departments
of Chemistry, Chemical and Biomolecular Engineering, and Materials
Science and Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Anna I. Krylov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States
| | - Anders M. N. Niklasson
- Theoretical
Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Sapna Sarupria
- Department of Chemical and Biomolecular Engineering, Center for Optical
Materials Science and Engineering Technologies (COMSET), Clemson University, Clemson, South Carolina 29670, United States
- Department
of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Yusu Wang
- Halıcıŏglu Data Science Institute, University of California, San Diego, La Jolla, California 92093, United States
| | - Stefan M. Wild
- Mathematics
and Computer Science Division, Argonne National
Laboratory, Lemont, Illinois 60439, United
States
| | - Qian Yang
- Computer Science and Engineering Department, University of Connecticut, Storrs, Connecticut 06269-4155, United States
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14
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Bürkle M, Perera U, Gimbert F, Nakamura H, Kawata M, Asai Y. Deep-Learning Approach to First-Principles Transport Simulations. PHYSICAL REVIEW LETTERS 2021; 126:177701. [PMID: 33988436 DOI: 10.1103/physrevlett.126.177701] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 03/18/2021] [Indexed: 06/12/2023]
Abstract
Large-scale first-principles transport calculations, while essential for device modeling, remain computationally demanding. To overcome this bottle neck, we combine first-principles transport calculations with machine learning-based nonlinear regression. We calculate the electronic conductance through first-principles based nonequilibrium Green's function techniques for small systems and map the transport properties onto local properties using local descriptors. We show that using the local descriptor as input features for deep learning-based nonlinear regression allows us to build a robust neural network that can predict the conductance of large systems beyond that of the current state-of-the-art first-principles calculation algorithms. Our protocol is applied to alkali metal nanowires, i.e., potassium, which have unique geometrical and electronic properties and hence nontrivial transport properties. We demonstrate that within our approach we can achieve qualitative agreement with experiment at a fraction of the computational effort as compared to the direct calculation of the transport properties using conventional first-principles methods.
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Affiliation(s)
- Marius Bürkle
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Umesha Perera
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Florian Gimbert
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Hisao Nakamura
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Masaaki Kawata
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Yoshihiro Asai
- National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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15
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Kowalski K, Bair R, Bauman NP, Boschen JS, Bylaska EJ, Daily J, de Jong WA, Dunning T, Govind N, Harrison RJ, Keçeli M, Keipert K, Krishnamoorthy S, Kumar S, Mutlu E, Palmer B, Panyala A, Peng B, Richard RM, Straatsma TP, Sushko P, Valeev EF, Valiev M, van Dam HJJ, Waldrop JM, Williams-Young DB, Yang C, Zalewski M, Windus TL. From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape. Chem Rev 2021; 121:4962-4998. [PMID: 33788546 DOI: 10.1021/acs.chemrev.0c00998] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early codesign projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.
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Affiliation(s)
- Karol Kowalski
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Raymond Bair
- Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Nicholas P Bauman
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | - Eric J Bylaska
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jeff Daily
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Wibe A de Jong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Thom Dunning
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Niranjan Govind
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Robert J Harrison
- Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York 11794, United States
| | - Murat Keçeli
- Argonne National Laboratory, Lemont, Illinois 60439, United States
| | | | | | - Suraj Kumar
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Erdal Mutlu
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Bruce Palmer
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ajay Panyala
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Bo Peng
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | - T P Straatsma
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6373, United States
| | - Peter Sushko
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Edward F Valeev
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Marat Valiev
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | | | | | - Chao Yang
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Marcin Zalewski
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Theresa L Windus
- Department of Chemistry, Iowa State University and Ames Laboratory, Ames, Iowa 50011, United States
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16
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Abstract
The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.
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Affiliation(s)
- Benjamin W J Chen
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lang Xu
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Manos Mavrikakis
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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17
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Maia JDC, Dos Anjos Formiga Cabral L, Rocha GB. GPU algorithms for density matrix methods on MOPAC: linear scaling electronic structure calculations for large molecular systems. J Mol Model 2020; 26:313. [PMID: 33090341 DOI: 10.1007/s00894-020-04571-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/08/2020] [Indexed: 11/29/2022]
Abstract
Purification of the density matrix methods should be employed when dealing with complex chemical systems containing many atoms. The running times for these methods scale linearly with the number of atoms if we consider the sparsity from the density matrix. Since the efficiency expected from those methods is closely tied to the underlying parallel implementations of the linear algebra operations (e.g., P2 = P × P), we proposed a central processing unit (CPU) and graphics processing unit (GPU) parallel matrix-matrix multiplication in SVBR (symmetrical variable block row) format for energy calculations through the SP2 algorithm. This algorithm was inserted in MOPAC's MOZYME method, using the original LMO Fock matrix assembly, and the atomic integral calculation implemented on it. Correctness and performance tests show that the implemented SP2 is accurate and fast, as the GPU is able to achieve speedups up to 40 times for a water cluster system with 42,312 orbitals running in one NVIDIA K40 GPU card compared to the single-threaded version. The GPU-accelerated SP2 algorithm using the MOZYME LMO framework enables the calculations of semiempirical wavefunction with stricter SCF criteria for localized charged molecular systems, as well as the single-point energies of molecules with more than 100.000 LMO orbitals in less than 1 h. Graphical abstract Parallel CPU and GPU purification algorithms for electronic structure calculations were implemented in MOPAC's MOZYME method. Some matrices in these calculations, e.g., electron density P, are compressed, and the developed linear algebra operations deal with non-zero entries only. We employed the NVIDIA/CUDA platform to develop GPU algorithms, and accelerations up to 40 times for larger systems were achieved.
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Affiliation(s)
- Julio Daniel Carvalho Maia
- Centro de Informática, Universidade Federal da Paraíba, João Pessoa, PB, CEP: 58055-000, Brazil.,Theoretical and Computational Biophysics Group - Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | | | - Gerd Bruno Rocha
- Departamento de Química - CCEN, Universidade Federal da Paraíba, Caixa Postal: 5093, João Pessoa, PB, CEP: 58051-970, Brazil.
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18
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Baker JS, Bowler DR. Polar Morphologies from First Principles: PbTiO
3
Films on SrTiO
3
Substrates and the p(2×Λ) Surface Reconstruction. ADVANCED THEORY AND SIMULATIONS 2020. [DOI: 10.1002/adts.202000154] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Jack S. Baker
- London Centre for Nanotechnology UCL 17‐19 Gordon St London WC1H 0AH UK
- Department of Physics & Astronomy UCL Gower St London WC1E 6BT UK
| | - David R. Bowler
- London Centre for Nanotechnology UCL 17‐19 Gordon St London WC1H 0AH UK
- Department of Physics & Astronomy UCL Gower St London WC1E 6BT UK
- International Centre for Materials Nanoarchitectonics (MANA) National Institute for Materials Science (NIMS) 1‐1 Namiki Tsukuba Ibaraki 305‐0044 Japan
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19
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Manzhos S, Golub P. Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression. J Chem Phys 2020; 153:074104. [DOI: 10.1063/5.0015042] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Sergei Manzhos
- Centre Énergie Matériaux Télécommunications, Institut National de la Recherche Scientifique, 1650 Boulevard Lionel-Boulet, Varennes, Quebec J3X 1S2, Canada
| | - Pavlo Golub
- Department of Theoretical Chemistry, J. Heyrovský Institute of Physical Chemistry, Dolejškova 2155/3, 182 23 Prague 8, Czech Republic
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20
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Hirakawa T, Bowler DR, Miyazaki T, Morikawa Y, Truflandier LA. Blue moon ensemble simulation of aquation free energy profiles applied to mono and bifunctional platinum anticancer drugs. J Comput Chem 2020; 41:1973-1984. [DOI: 10.1002/jcc.26367] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 05/21/2020] [Accepted: 06/01/2020] [Indexed: 12/31/2022]
Affiliation(s)
- Teruo Hirakawa
- Department of Precision EngineeringGraduate School of Engineering, Osaka University Suita Osaka Japan
- Institut des Sciences Moléculaires (ISM), Université Bordeaux Talence Cedex France
| | - David R. Bowler
- Department of Physics & AstronomyUniversity College London (UCL) London United Kingdom
- London Centre for Nanotechnology, UCL London United Kingdom
- International Centre for Materials Nanoarchitechtonics (WPI‐MANA), National Institute for Materials Science (NIMS) Tsukuba Ibaraki Japan
| | - Tsuyoshi Miyazaki
- International Centre for Materials Nanoarchitechtonics (WPI‐MANA), National Institute for Materials Science (NIMS) Tsukuba Ibaraki Japan
| | - Yoshitada Morikawa
- Department of Precision EngineeringGraduate School of Engineering, Osaka University Suita Osaka Japan
- Elements Strategy Initiative for Catalysts and Batteries (ESICB), Kyoto University Kyoto Japan
- Research Center for Ultra‐Precision Science and TechnologyGraduate School of Engineering, Osaka University Suita Osaka Japan
| | - Lionel A. Truflandier
- Department of Precision EngineeringGraduate School of Engineering, Osaka University Suita Osaka Japan
- Institut des Sciences Moléculaires (ISM), Université Bordeaux Talence Cedex France
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21
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Ratcliff LE, Dawson W, Fisicaro G, Caliste D, Mohr S, Degomme A, Videau B, Cristiglio V, Stella M, D’Alessandro M, Goedecker S, Nakajima T, Deutsch T, Genovese L. Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations. J Chem Phys 2020; 152:194110. [PMID: 33687268 DOI: 10.1063/5.0004792] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Laura E. Ratcliff
- Department of Materials, Imperial College London, London SW7 2AZ, United Kingdom
| | | | - Giuseppe Fisicaro
- Consiglio Nazionale delle Ricerche, Istituto per la Microelettronica e Microsistemi (CNR-IMM), Z.I. VIII Strada 5, I-95121 Catania, Italy
| | - Damien Caliste
- Univ. Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38000 Grenoble, France
| | - Stephan Mohr
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Nextmol (Bytelab Solutions SL), Barcelona, Spain
| | - Augustin Degomme
- Univ. Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38000 Grenoble, France
| | - Brice Videau
- Univ. Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38000 Grenoble, France
| | | | - Martina Stella
- Department of Materials, Imperial College London, London SW7 2AZ, United Kingdom
| | - Marco D’Alessandro
- Istituto di Struttura della Materia-CNR (ISM-CNR), Via del Fosso del Cavaliere 100, 00133 Roma, Italy
| | | | | | - Thierry Deutsch
- Univ. Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38000 Grenoble, France
| | - Luigi Genovese
- Univ. Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38000 Grenoble, France
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22
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Nakata A, Baker JS, Mujahed SY, Poulton JTL, Arapan S, Lin J, Raza Z, Yadav S, Truflandier L, Miyazaki T, Bowler DR. Large scale and linear scaling DFT with the CONQUEST code. J Chem Phys 2020; 152:164112. [DOI: 10.1063/5.0005074] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Affiliation(s)
- Ayako Nakata
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Jack S. Baker
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
- Department of Physics & Astronomy, University College London, Gower St., London WC1E 6BT, United Kingdom
| | - Shereif Y. Mujahed
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
- Department of Physics & Astronomy, University College London, Gower St., London WC1E 6BT, United Kingdom
| | - Jack T. L. Poulton
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
- Department of Physics & Astronomy, University College London, Gower St., London WC1E 6BT, United Kingdom
| | - Sergiu Arapan
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Jianbo Lin
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Zamaan Raza
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Sushma Yadav
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Lionel Truflandier
- Institut des Sciences Moléculaires, Université Bordeaux, 351 Cours de la Libération, 33405 Talence, France
| | - Tsuyoshi Miyazaki
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - David R. Bowler
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
- Department of Physics & Astronomy, University College London, Gower St., London WC1E 6BT, United Kingdom
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23
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Kang S, Woo J, Kim J, Kim H, Kim Y, Lim J, Choi S, Kim WY. ACE-Molecule: An open-source real-space quantum chemistry package. J Chem Phys 2020; 152:124110. [DOI: 10.1063/5.0002959] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Sungwoo Kang
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Jeheon Woo
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Jaewook Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Hyeonsu Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Yongjun Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Jaechang Lim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Sunghwan Choi
- National Institute of Supercomputing and Network, Korea Institute of Science and Technology Information, 245 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
| | - Woo Youn Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea
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24
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Schütt O, VandeVondele J. Machine Learning Adaptive Basis Sets for Efficient Large Scale Density Functional Theory Simulation. J Chem Theory Comput 2018; 14:4168-4175. [PMID: 29957943 PMCID: PMC6096449 DOI: 10.1021/acs.jctc.8b00378] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
It is chemically intuitive that an optimal atom centered basis set must adapt to its atomic environment, for example by polarizing toward nearby atoms. Adaptive basis sets of small size can be significantly more accurate than traditional atom centered basis sets of the same size. The small size and well conditioned nature of these basis sets leads to large saving in computational cost, in particular in a linear scaling framework. Here, it is shown that machine learning can be used to predict such adaptive basis sets using local geometrical information only. As a result, various properties of standard DFT calculations can be easily obtained at much lower costs, including nuclear gradients. In our approach, a rotationally invariant parametrization of the basis is obtained by employing a potential anchored on neighboring atoms to ultimately construct a rotation matrix that turns a traditional atom centered basis set into a suitable adaptive basis set. The method is demonstrated using MD simulations of liquid water, where it is shown that minimal basis sets yield structural properties in fair agreement with basis set converged results, while reducing the computational cost in the best case by a factor of 200 and the required flops by 4 orders of magnitude. Already a very small training set yields satisfactory results as the variational nature of the method provides robustness.
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Affiliation(s)
- Ole Schütt
- Department of Materials , ETH Zürich , 8093 Zürich , Switzerland
| | - Joost VandeVondele
- Department of Materials , ETH Zürich , 8093 Zürich , Switzerland.,Swiss National Supercomputing Centre (CSCS) , 6900 Lugano , Switzerland
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25
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Scheiber H, Shi Y, Khaliullin RZ. Communication: Compact orbitals enable low-cost linear-scaling ab initio molecular dynamics for weakly-interacting systems. J Chem Phys 2018; 148:231103. [PMID: 29935517 DOI: 10.1063/1.5029939] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Hayden Scheiber
- Department of Chemistry, McGill University, 801 Sherbrooke St. West, Montreal, Québec H3A 0B8, Canada
| | - Yifei Shi
- Department of Chemistry, McGill University, 801 Sherbrooke St. West, Montreal, Québec H3A 0B8, Canada
| | - Rustam Z. Khaliullin
- Department of Chemistry, McGill University, 801 Sherbrooke St. West, Montreal, Québec H3A 0B8, Canada
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26
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Banerjee AS, Lin L, Suryanarayana P, Yang C, Pask JE. Two-Level Chebyshev Filter Based Complementary Subspace Method: Pushing the Envelope of Large-Scale Electronic Structure Calculations. J Chem Theory Comput 2018; 14:2930-2946. [PMID: 29660292 DOI: 10.1021/acs.jctc.7b01243] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit diagonalization of the Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ a two-level Chebyshev polynomial filter based complementary subspace strategy to (1) compute a set of vectors that span the occupied subspace of the Hamiltonian; (2) reduce subspace diagonalization to just partially occupied states; and (3) obtain those states in an efficient, scalable manner via an inner Chebyshev filter iteration. By reducing the necessary computation to just partially occupied states and obtaining these through an inner Chebyshev iteration, our approach reduces the cost of large metallic calculations significantly, while eliminating subspace diagonalization for insulating systems altogether. We describe the implementation of the method within the framework of the discontinuous Galerkin (DG) electronic structure method and show that this results in a computational scheme that can effectively tackle bulk and nano systems containing tens of thousands of electrons, with chemical accuracy, within a few minutes or less of wall clock time per SCF iteration on large-scale computing platforms. We anticipate that our method will be instrumental in pushing the envelope of large-scale ab initio molecular dynamics. As a demonstration of this, we simulate a bulk silicon system containing 8,000 atoms at finite temperature, and obtain an average SCF step wall time of 51 s on 34,560 processors; thus allowing us to carry out 1.0 ps of ab initio molecular dynamics in approximately 28 h (of wall time).
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Affiliation(s)
- Amartya S Banerjee
- Computational Research Division , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - Lin Lin
- Computational Research Division , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States.,Department of Mathematics , University of California , Berkeley , California 94720 , United States
| | - Phanish Suryanarayana
- College of Engineering , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States
| | - Chao Yang
- Computational Research Division , Lawrence Berkeley National Laboratory , Berkeley , California 94720 , United States
| | - John E Pask
- Physics Division , Lawrence Livermore National Laboratory , Livermore , California 94550 , United States
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27
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Mohr S, Dawson W, Wagner M, Caliste D, Nakajima T, Genovese L. Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library. J Chem Theory Comput 2017; 13:4684-4698. [PMID: 28873312 DOI: 10.1021/acs.jctc.7b00348] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes.
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Affiliation(s)
- Stephan Mohr
- Barcelona Supercomputing Center (BSC) , 08034 Barcelona, Spain
| | - William Dawson
- RIKEN Advanced Institute for Computational Science , Kobe 650-0002, Japan
| | - Michael Wagner
- Barcelona Supercomputing Center (BSC) , 08034 Barcelona, Spain
| | - Damien Caliste
- Université Grenoble Alpes, INAC-MEM, L_Sim, F-38000 Grenoble, France.,CEA, INAC-MEM, L_Sim, F-38000 Grenoble, France
| | - Takahito Nakajima
- RIKEN Advanced Institute for Computational Science , Kobe 650-0002, Japan
| | - Luigi Genovese
- Université Grenoble Alpes, INAC-MEM, L_Sim, F-38000 Grenoble, France.,CEA, INAC-MEM, L_Sim, F-38000 Grenoble, France
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28
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Nakata A, Futamura Y, Sakurai T, Bowler DR, Miyazaki T. Efficient Calculation of Electronic Structure Using O(N) Density Functional Theory. J Chem Theory Comput 2017; 13:4146-4153. [DOI: 10.1021/acs.jctc.7b00385] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ayako Nakata
- First-Principles
Simulation Group, Nano-Theory Field, International Center for Materials
Nanoarchitectonics (WPI-MANA), National Institute for Materials Science
(NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Yasunori Futamura
- Department
of Computer Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
| | - Tetsuya Sakurai
- Department
of Computer Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
- CREST, Japan Science
and Technology Agency, 4-1-8 Hon-cho, Kawaguchi, Saitama 332-0012, Japan
| | - David R Bowler
- Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, U.K
- WPI-MANA, National
Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- London Centre for Nanotechnology, University College London, 17-19 Gordon Street, London WC1H 0AH, U.K
| | - Tsuyoshi Miyazaki
- First-Principles
Simulation Group, Nano-Theory Field, International Center for Materials
Nanoarchitectonics (WPI-MANA), National Institute for Materials Science
(NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, U.K
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29
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Mohr S, Masella M, Ratcliff LE, Genovese L. Complexity Reduction in Large Quantum Systems: Fragment Identification and Population Analysis via a Local Optimized Minimal Basis. J Chem Theory Comput 2017; 13:4079-4088. [DOI: 10.1021/acs.jctc.7b00291] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Stephan Mohr
- Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain
| | - Michel Masella
- Laboratoire
de
Biologie Structurale et Radiologie, Service de Bioénergétique,
Biologie Structurale et Mécanisme, Institut de Biologie et de Technologie de Saclay, CEA Saclay, F-91191 Gif-sur-Yvette Cedex, France
| | - Laura E. Ratcliff
- Argonne
Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, United States
| | - Luigi Genovese
- Université Grenoble Alpes, INAC-MEM, L_Sim, F-38000 Grenoble, France
- CEA, INAC-MEM,
L_Sim, F-38000 Grenoble, France
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30
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Witte J, Neaton JB, Head-Gordon M. Effective empirical corrections for basis set superposition error in the def2-SVPD basis: gCP and DFT-C. J Chem Phys 2017. [DOI: 10.1063/1.4986962] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
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31
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Milanese JM, Provorse MR, Alameda E, Isborn CM. Convergence of Computed Aqueous Absorption Spectra with Explicit Quantum Mechanical Solvent. J Chem Theory Comput 2017; 13:2159-2171. [DOI: 10.1021/acs.jctc.7b00159] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Joel M. Milanese
- Chemistry and Chemical Biology, University of California at Merced, Merced, California 95343, United States
| | - Makenzie R. Provorse
- Chemistry and Chemical Biology, University of California at Merced, Merced, California 95343, United States
| | - Enrique Alameda
- Chemistry and Chemical Biology, University of California at Merced, Merced, California 95343, United States
| | - Christine M. Isborn
- Chemistry and Chemical Biology, University of California at Merced, Merced, California 95343, United States
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Ratcliff LE, Mohr S, Huhs G, Deutsch T, Masella M, Genovese L. Challenges in large scale quantum mechanical calculations. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2016. [DOI: 10.1002/wcms.1290] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Laura E. Ratcliff
- Argonne Leadership Computing Facility Argonne National Laboratory Lemon IL USA
| | - Stephan Mohr
- Department of Computer Applications in Science and Engineering Barcelona Supercomputing Center (BSC‐CNS) Barcelona Spain
| | - Georg Huhs
- Department of Computer Applications in Science and Engineering Barcelona Supercomputing Center (BSC‐CNS) Barcelona Spain
| | - Thierry Deutsch
- University Grenoble Alpes INAC‐MEM Grenoble France
- CEA, INAC‐MEM Grenoble France
| | - Michel Masella
- Laboratoire de Biologie Structurale et Radiologie, Service de Bioénergétique, Biologie Structurale et Mécanisme Institut de Biologie et de Technologie de Saclay, CEA Saclay Gif‐sur‐Yvette Cedex France
| | - Luigi Genovese
- University Grenoble Alpes INAC‐MEM Grenoble France
- CEA, INAC‐MEM Grenoble France
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Mao Y, Horn PR, Mardirossian N, Head-Gordon T, Skylaris CK, Head-Gordon M. Approaching the basis set limit for DFT calculations using an environment-adapted minimal basis with perturbation theory: Formulation, proof of concept, and a pilot implementation. J Chem Phys 2016; 145:044109. [DOI: 10.1063/1.4959125] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Yuezhi Mao
- Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Paul R. Horn
- Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Narbe Mardirossian
- Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Teresa Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, USA
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, USA
- Department of Bioengineering, University of California, Berkeley, California 94720, USA
- Chemical Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Chris-Kriton Skylaris
- School of Chemistry, University of Southampton, Highfield, Southampton, SO17 1BJ, United Kingdom
| | - Martin Head-Gordon
- Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, USA
- Chemical Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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34
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Wall ME. Quantum crystallographic charge density of urea. IUCRJ 2016; 3:237-46. [PMID: 27437111 PMCID: PMC4937779 DOI: 10.1107/s2052252516006242] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 04/13/2016] [Indexed: 05/20/2023]
Abstract
Standard X-ray crystallography methods use free-atom models to calculate mean unit-cell charge densities. Real molecules, however, have shared charge that is not captured accurately using free-atom models. To address this limitation, a charge density model of crystalline urea was calculated using high-level quantum theory and was refined against publicly available ultra-high-resolution experimental Bragg data, including the effects of atomic displacement parameters. The resulting quantum crystallographic model was compared with models obtained using spherical atom or multipole methods. Despite using only the same number of free parameters as the spherical atom model, the agreement of the quantum model with the data is comparable to the multipole model. The static, theoretical crystalline charge density of the quantum model is distinct from the multipole model, indicating the quantum model provides substantially new information. Hydrogen thermal ellipsoids in the quantum model were very similar to those obtained using neutron crystallography, indicating that quantum crystallography can increase the accuracy of the X-ray crystallographic atomic displacement parameters. The results demonstrate the feasibility and benefits of integrating fully periodic quantum charge density calculations into ultra-high-resolution X-ray crystallographic model building and refinement.
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Affiliation(s)
- Michael E. Wall
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Mail Stop B256, Los Alamos, New Mexico 87545, USA
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35
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Niklasson AMN, Mniszewski SM, Negre CFA, Cawkwell MJ, Swart PJ, Mohd-Yusof J, Germann TC, Wall ME, Bock N, Rubensson EH, Djidjev H. Graph-based linear scaling electronic structure theory. J Chem Phys 2016; 144:234101. [DOI: 10.1063/1.4952650] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
| | - Susan M. Mniszewski
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Christian F. A. Negre
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Marc J. Cawkwell
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Pieter J. Swart
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Jamal Mohd-Yusof
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Timothy C. Germann
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Michael E. Wall
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Nicolas Bock
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Emanuel H. Rubensson
- Division of Scientific Computing, Department of Information Technology, Uppsala University, Box 337, SE-751 05 Uppsala, Sweden
| | - Hristo Djidjev
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
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36
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Andermatt S, Cha J, Schiffmann F, VandeVondele J. Combining Linear-Scaling DFT with Subsystem DFT in Born–Oppenheimer and Ehrenfest Molecular Dynamics Simulations: From Molecules to a Virus in Solution. J Chem Theory Comput 2016; 12:3214-27. [DOI: 10.1021/acs.jctc.6b00398] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
| | - Jinwoong Cha
- Department
of Materials, ETH Zürich, Zürich, Switzerland
| | - Florian Schiffmann
- Department
of Materials, ETH Zürich, Zürich, Switzerland
- Centre
of Policy Studies, Victoria University, Melbourne, Australia
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37
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Niklasson AMN, Cawkwell MJ, Rubensson EH, Rudberg E. Canonical density matrix perturbation theory. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2015; 92:063301. [PMID: 26764847 DOI: 10.1103/physreve.92.063301] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Indexed: 06/05/2023]
Abstract
Density matrix perturbation theory [Niklasson and Challacombe, Phys. Rev. Lett. 92, 193001 (2004)] is generalized to canonical (NVT) free-energy ensembles in tight-binding, Hartree-Fock, or Kohn-Sham density-functional theory. The canonical density matrix perturbation theory can be used to calculate temperature-dependent response properties from the coupled perturbed self-consistent field equations as in density-functional perturbation theory. The method is well suited to take advantage of sparse matrix algebra to achieve linear scaling complexity in the computational cost as a function of system size for sufficiently large nonmetallic materials and metals at high temperatures.
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Affiliation(s)
- Anders M N Niklasson
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - M J Cawkwell
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Emanuel H Rubensson
- Division of Scientific Computing, Department of Information Technology, Uppsala University Box 337, SE-751 05 Uppsala, Sweden
| | - Elias Rudberg
- Division of Scientific Computing, Department of Information Technology, Uppsala University Box 337, SE-751 05 Uppsala, Sweden
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38
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Shift-and-invert parallel spectral transformation eigensolver: Massively parallel performance for density-functional based tight-binding. J Comput Chem 2015; 37:448-59. [DOI: 10.1002/jcc.24254] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 10/15/2015] [Accepted: 10/25/2015] [Indexed: 01/12/2023]
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39
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Mniszewski SM, Cawkwell MJ, Wall ME, Mohd-Yusof J, Bock N, Germann TC, Niklasson AMN. Efficient Parallel Linear Scaling Construction of the Density Matrix for Born–Oppenheimer Molecular Dynamics. J Chem Theory Comput 2015; 11:4644-54. [DOI: 10.1021/acs.jctc.5b00552] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- S. M. Mniszewski
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - M. J. Cawkwell
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - M. E. Wall
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - J. Mohd-Yusof
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - N. Bock
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - T. C. Germann
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - A. M. N. Niklasson
- Computer, Computational, and Statistical Sciences Division and ‡Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
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40
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Hu W, Lin L, Yang C. DGDFT: A massively parallel method for large scale density functional theory calculations. J Chem Phys 2015; 143:124110. [DOI: 10.1063/1.4931732] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Wei Hu
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Lin Lin
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Department of Mathematics, University of California, Berkeley, California 94720, USA
| | - Chao Yang
- Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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41
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O'Rourke C, Bowler DR. Linear scaling density matrix real time TDDFT: Propagator unitarity and matrix truncation. J Chem Phys 2015; 143:102801. [PMID: 26373994 DOI: 10.1063/1.4919128] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Real time, density matrix based, time dependent density functional theory (TDDFT) proceeds through the propagation of the density matrix, as opposed to the Kohn-Sham orbitals. It is possible to reduce the computational workload by imposing spatial cutoff radii on sparse matrices, and the propagation of the density matrix in this manner provides direct access to the optical response of very large systems, which would be otherwise impractical to obtain using the standard formulations of TDDFT. Following a brief summary of our implementation, along with several benchmark tests illustrating the validity of the method, we present an exploration of the factors affecting the accuracy of the approach. In particular, we investigate the effect of basis set size and matrix truncation, the key approximation used in achieving linear scaling, on the propagator unitarity and optical spectra. Finally, we illustrate that, with an appropriate density matrix truncation range applied, the computational load scales linearly with the system size and discuss the limitations of the approach.
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Affiliation(s)
- Conn O'Rourke
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
| | - David R Bowler
- London Centre for Nanotechnology, University College London, 17-19 Gordon St., London WC1H 0AH, United Kingdom
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42
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Ratcliff LE, Genovese L, Mohr S, Deutsch T. Fragment approach to constrained density functional theory calculations using Daubechies wavelets. J Chem Phys 2015; 142:234105. [DOI: 10.1063/1.4922378] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Laura E. Ratcliff
- Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, USA
- Université de Grenoble Alpes, CEA, INAC-SP2M, L_Sim, F-38000 Grenoble, France
| | - Luigi Genovese
- Université de Grenoble Alpes, CEA, INAC-SP2M, L_Sim, F-38000 Grenoble, France
| | - Stephan Mohr
- Université de Grenoble Alpes, CEA, INAC-SP2M, L_Sim, F-38000 Grenoble, France
| | - Thierry Deutsch
- Université de Grenoble Alpes, CEA, INAC-SP2M, L_Sim, F-38000 Grenoble, France
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Recent advances in QM/MM free energy calculations using reference potentials. Biochim Biophys Acta Gen Subj 2014; 1850:954-965. [PMID: 25038480 PMCID: PMC4547088 DOI: 10.1016/j.bbagen.2014.07.008] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2014] [Revised: 07/06/2014] [Accepted: 07/07/2014] [Indexed: 01/02/2023]
Abstract
Background Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Scope of review Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. Major conclusions The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. General significance As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. We present some of the advances to accelerate high-level QM/MM calculations. Quantitative limitations of low-level methods can be overcome by these approaches. Reference potentials make free energy simulations feasible for large systems. Automated fitting reduces the need of expensive sampling of high-level approaches. Application of reference potentials can be extended to a wide range of processes.
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Mohr S, Ratcliff LE, Boulanger P, Genovese L, Caliste D, Deutsch T, Goedecker S. Daubechies wavelets for linear scaling density functional theory. J Chem Phys 2014; 140:204110. [DOI: 10.1063/1.4871876] [Citation(s) in RCA: 128] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Corsetti F. Performance analysis of electronic structure codes on HPC systems: a case study of SIESTA. PLoS One 2014; 9:e95390. [PMID: 24748385 PMCID: PMC3991679 DOI: 10.1371/journal.pone.0095390] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Accepted: 03/26/2014] [Indexed: 11/18/2022] Open
Abstract
We report on scaling and timing tests of the SIESTA electronic structure code for ab initio molecular dynamics simulations using density-functional theory. The tests are performed on six large-scale supercomputers belonging to the PRACE Tier-0 network with four different architectures: Cray XE6, IBM BlueGene/Q, BullX, and IBM iDataPlex. We employ a systematic strategy for simultaneously testing weak and strong scaling, and propose a measure which is independent of the range of number of cores on which the tests are performed to quantify strong scaling efficiency as a function of simulation size. We find an increase in efficiency with simulation size for all machines, with a qualitatively different curve depending on the supercomputer topology, and discuss the connection of this functional form with weak scaling behaviour. We also analyze the absolute timings obtained in our tests, showing the range of system sizes and cores favourable for different machines. Our results can be employed as a guide both for running SIESTA on parallel architectures, and for executing similar scaling tests of other electronic structure codes.
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46
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Taylor DE, Rice BM. Quantum-Informed Multiscale M&S for Energetic Materials. ADVANCES IN QUANTUM CHEMISTRY 2014. [DOI: 10.1016/b978-0-12-800345-9.00005-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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47
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Todorović M, Bowler DR, Gillan MJ, Miyazaki T. Density-functional theory study of gramicidin A ion channel geometry and electronic properties. J R Soc Interface 2013; 10:20130547. [PMID: 24068174 PMCID: PMC3808544 DOI: 10.1098/rsif.2013.0547] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2013] [Accepted: 09/03/2013] [Indexed: 01/29/2023] Open
Abstract
Understanding the mechanisms underlying ion channel function from the atomic-scale requires accurate ab initio modelling as well as careful experiments. Here, we present a density functional theory (DFT) study of the ion channel gramicidin A (gA), whose inner pore conducts only monovalent cations and whose conductance has been shown to depend on the side chains of the amino acids in the channel. We investigate the ground state geometry and electronic properties of the channel in vacuum, focusing on their dependence on the side chains of the amino acids. We find that the side chains affect the ground state geometry, while the electrostatic potential of the pore is independent of the side chains. This study is also in preparation for a full, linear scaling DFT study of gA in a lipid bilayer with surrounding water. We demonstrate that linear scaling DFT methods can accurately model the system with reasonable computational cost. Linear scaling DFT allows ab initio calculations with 10,000-100,000 atoms and beyond, and will be an important new tool for biomolecular simulations.
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Affiliation(s)
- Milica Todorović
- National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan
| | - David R. Bowler
- International Centre for Materials Nanoarchitectonics (MANA), National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
- London Centre for Nanotechnology, UCL, 17–19 Gordon Street, London WC1H 0AH, UK
- Thomas Young Centre, Department of Physics and Astronomy, UCL, Gower Street, London WC1E 6BT, UK
| | - Michael J. Gillan
- London Centre for Nanotechnology, UCL, 17–19 Gordon Street, London WC1H 0AH, UK
- Thomas Young Centre, Department of Physics and Astronomy, UCL, Gower Street, London WC1E 6BT, UK
| | - Tsuyoshi Miyazaki
- National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan
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Otsuka T, Okimoto N, Taiji M, Bowler DR, Miyazaki T. Structural relaxation and binding energy calculations of FK506 binding protein complexes using the large-scale DFT code CONQUEST. ACTA ACUST UNITED AC 2013. [DOI: 10.1088/1742-6596/454/1/012057] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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49
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Small Optical Gap Molecules and Polymers: Using Theory to Design More Efficient Materials for Organic Photovoltaics. Top Curr Chem (Cham) 2013; 352:1-38. [DOI: 10.1007/128_2013_459] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2022]
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50
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Bowler DR, Miyazaki T. O(N) methods in electronic structure calculations. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2012; 75:036503. [PMID: 22790422 DOI: 10.1088/0034-4885/75/3/036503] [Citation(s) in RCA: 170] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Linear-scaling methods, or O(N) methods, have computational and memory requirements which scale linearly with the number of atoms in the system, N, in contrast to standard approaches which scale with the cube of the number of atoms. These methods, which rely on the short-ranged nature of electronic structure, will allow accurate, ab initio simulations of systems of unprecedented size. The theory behind the locality of electronic structure is described and related to physical properties of systems to be modelled, along with a survey of recent developments in real-space methods which are important for efficient use of high-performance computers. The linear-scaling methods proposed to date can be divided into seven different areas, and the applicability, efficiency and advantages of the methods proposed in these areas are then discussed. The applications of linear-scaling methods, as well as the implementations available as computer programs, are considered. Finally, the prospects for and the challenges facing linear-scaling methods are discussed.
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Affiliation(s)
- D R Bowler
- London Centre for Nanotechnology, UCL, 17-19 Gordon St, London WC1H 0AH, UK.
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