Electronic structure calculations with GPAW: a real-space implementation of the projector augmented-wave method

Ultrastrong Coupling of a Single Molecule to a Plasmonic Nanocavity: A First-Principles Study

Ultrastrong coupling (USC) is a distinct regime of light-matter interaction in which the coupling strength is comparable to the resonance energy of the cavity or emitter. In the USC regime, common approximations to quantum optical Hamiltonians, such as the rotating wave approximation, break down as the ground state of the coupled system gains photonic character due to admixing of vacuum states with higher excited states, leading to ground-state energy changes. USC is usually achieved by collective coherent coupling of many quantum emitters to a single mode cavity, whereas USC with a single molecule remains challenging. Here, we show by time-dependent density functional theory (TDDFT) calculations that a single organic molecule can reach USC with a plasmonic dimer, consisting of a few hundred atoms. In this context, we discuss the capacity of TDDFT to represent strong coupling and its connection to the quantum optical Hamiltonian. We find that USC leads to appreciable ground-state energy modifications accounting for a non-negligible part of the total interaction energy, comparable to k _B T at room temperature.

Water Chemistry beneath Graphene: Condensation of a Dense OH-H2O Phase under Graphene

Room temperature oxygen hydrogenation below graphene flakes supported by Ir(111) is investigated through a combination of X-ray photoelectron spectroscopy, scanning tunneling microscopy, and density functional theory calculations using an evolutionary search algorithm. We demonstrate how the graphene cover and its doping level can be used to trap and characterize dense mixed O-OH-H₂O phases that otherwise would not exist. Our study of these graphene-stabilized phases and their response to oxygen or hydrogen exposure reveals that additional oxygen can be dissolved into them at room temperature creating mixed O-OH-H₂O phases with an increased areal coverage underneath graphene. In contrast, additional hydrogen exposure converts the mixed O-OH-H₂O phases back to pure OH-H₂O with a reduced areal coverage underneath graphene.

Generating stable molecules using imitation and reinforcement learning

Chemical space is routinely explored by machine learning methods to discover interesting molecules, before time-consuming experimental synthesizing is attempted. However, these methods often rely on a graph representation, ignoring 3D information necessary for determining the stability of the molecules. We propose a reinforcement learning (RL) approach for generating molecules in Cartesian coordinates allowing for quantum chemical prediction of the stability. To improve sample-efficiency we learn basic chemical rules from imitation learning (IL) on the GDB-11 database to create an initial model applicable for all stoichiometries. We then deploy multiple copies of the model conditioned on a specific stoichiometry in a RL setting. The models correctly identify low energy molecules in the database and produce novel isomers not found in the training set. Finally, we apply the model to larger molecules to show how RL further refines the IL model in domains far from the training data.

Toward Exotic Layered Materials: 2D Cuprous Iodide

Heterostructures composed of 2D materials are already opening many new possibilities in such fields of technology as electronics and magnonics, but far more could be achieved if the number and diversity of 2D materials were increased. So far, only a few dozen 2D crystals have been extracted from materials that exhibit a layered phase in ambient conditions, omitting entirely the large number of layered materials that may exist at other temperatures and pressures. This work demonstrates how such structures can be stabilized in 2D van der Waals (vdw) stacks under room temperature via growing them directly in graphene encapsulation by using graphene oxide as the template material. Specifically, an ambient stable 2D structure of copper and iodine, a material that normally only occurs in layered form at elevated temperatures between 645 and 675 K, is produced. The results establish a simple route to the production of more exotic phases of materials that would otherwise be difficult or impossible to stabilize for experiments in ambient.

Hirshfeld atom refinement based on projector augmented wave densities with periodic boundary conditions

Hirshfeld atom refinement (HAR) is an X-ray diffraction refinement method that, in numerous publications, has been shown to give H-atom bond lengths in close agreement with neutron diffraction derived values. Presented here is a first evaluation of an approach using densities derived from projector augmented wave (PAW) densities with three-dimensional periodic boundary conditions for HAR. The results show an improvement over refinements that neglect the crystal environment or treat it classically, while being on a par with non-periodic approximations for treating the solid-state environment quantum mechanically. A suite of functionals were evaluated for this purpose, showing that the SCAN and revSCAN functionals are most suited to these types of calculation.

Highly-anisotropic plasmons in two-dimensional hyperbolic copper borides

Hyperbolic materials have wide application prospects, such as all-angle negative refraction, sub-diffraction imaging and nano-sensing, owning to the unusual electromagnetic response characteristics. Compared with artificial hyperbolic metamaterials, natural hyperbolic materials have many advantages. Anisotropic two-dimensional (2D) materials show great potential in the field of optoelectronics due to the intrinsic in-plane anisotropy. Here, the electronic and optical properties of two hyperbolic 2D materials, monolayer CuB₆ and CuB₃, are investigated using first-principles calculations. They are predicted to have multiple broadband hyperbolic windows with low loss and highly-anisotropic plasmon excitation from infrared to ultraviolet regions. Remarkably, plasmon propagation along the x-direction is almost forbidden in CuB₃ monolayer. The hyperbolic windows and plasmonic properties of these 2D copper borides can be effectively regulated by electron (or hole) doping, which offers a promising strategy for tuning the optical properties of the materials.

Thermal excitation signals in the inhomogeneous warm dense electron gas

We investigate the emergence of electronic excitations from the inhomogeneous electronic structure at warm dense matter parameters based on first-principles calculations. The emerging modes are controlled by the imposed perturbation amplitude. They include satellite signals around the standard plasmon feature, transformation of plasmons to optical modes, and double-plasmon modes. These modes exhibit a pronounced dependence on the temperature. This makes them potentially invaluable for the diagnostics of plasma parameters in the warm dense matter regime. We demonstrate that these modes can be probed with present experimental techniques.

Effect of Concrete Composition on the Thermodynamic Binding of Dopamine: A DFT Study

Concrete has long been a standard in construction projects. However, increasing the binding of cement paste to the concrete aggregate (a collection of geological materials containing, e.g., gravel, sand, etc.) remains an open area of research, as this is a common failure point in concrete-based infrastructure. One solution is the application of an adhesive into the mix that not only is capable of binding under aqueous conditions but can aid in the binding of the aggregate to the cement paste. Bioinspired catecholic-type molecules have been shown to be an ultrastrong adhesive, even under wet conditions, and would, in principle, be an ideal candidate to use. In this study, we examine how dopamine (a molecule with a catechol functionality) binds to various oxides found in concrete mixtures. We find that dopamine binds preferentially to alkaline earth oxides; thus, for concrete mixtures rich in these minerals dopamine would be an ideal candidate for improved adhesion.

A Differentiable Neural-Network Force Field for Ionic Liquids

We present NeuralIL, a model for the potential energy of an ionic liquid that accurately reproduces first-principles results with orders-of-magnitude savings in computational cost. Built on the basis of a multilayer perceptron and spherical Bessel descriptors of the atomic environments, NeuralIL is implemented in such a way as to be fully automatically differentiable. It can thus be trained on ab initio forces instead of just energies, to make the most out of the available data, and can efficiently predict arbitrary derivatives of the potential energy. Using ethylammonium nitrate as the test system, we obtain out-of-sample accuracies better than 2 meV atom-1 (<0.05 kcal mol-1) in the energies and 70 meV Å-1 in the forces. We show that encoding the element-specific density in the spherical Bessel descriptors is key to achieving this. Harnessing the information provided by the forces drastically reduces the amount of atomic configurations required to train a neural network force field based on atom-centered descriptors. We choose the Swish-1 activation function and discuss the role of this choice in keeping the neural network differentiable. Furthermore, the possibility of training on small data sets allows for an ensemble-learning approach to the detection of extrapolation. Finally, we find that a separate treatment of long-range interactions is not required to achieve a high-quality representation of the potential energy surface of these dense ionic systems.

Autonomous Design of Photoferroic Ruddlesden-Popper Perovskites for Water Splitting Devices

The use of ferroelectric materials for light-harvesting applications is a possible solution for increasing the efficiency of solar cells and photoelectrocatalytic devices. In this work, we establish a fully autonomous computational workflow to identify light-harvesting materials for water splitting devices based on properties such as stability, size of the band gap, position of the band edges, and ferroelectricity. We have applied this workflow to investigate the Ruddlesden-Popper perovskite class and have identified four new compositions, which show a theoretical efficiency above 5%.

Simulations of x-ray absorption spectra for CO desorbing from Ru(0001) with transition-potential and time-dependent density functional theory approaches

The desorption of a carbon monoxide molecule from a Ru(0001) surface was studied by means of X-ray Absorption Spectra (XAS) computed with Transition Potential (TP-DFT) and Time Dependent (TD-DFT) DFT methods. By unraveling the evolution of the CO electronic structure upon desorption, we observed that at 2.3 Å from the surface, the CO molecule has already predominantly gas-phase character. While C 1s XAS is quite insensitive to changes in the C-O bond length, the O 1s excitation is very sensitive with the π* coming down in energy upon CO bond stretching, which competes with the increase in orbital energy due to the repulsive interaction with the metallic surface. We show in a systematic way that the TP-DFT method can describe the XAS rather well at the endpoints (chemisorbed and gas phase) but is affected by artificial charge transfer and/or incorrect spin treatment in the transition region in cases like CO, where there are low-lying π* orbitals and large exchange interactions between the core 1s and valence-acceptor π* orbitals. As an alternative, we demonstrate by comparing with experimental data that a linear response approach using TD-DFT employing common exchange-correlation functionals and finite-size clusters can yield a good description of the spectral evolution of the 1s → π* transition with correct spin and gas-to-chemisorbed chemical shifts in good agreement with experiment.

Edge Effect in Electronic and Transport Properties of 1D Fluorinated Graphene Materials

A systematic examination of the electronic and transport properties of 1D fluorine-saturated zigzag graphene nanoribbons (ZGNRs) is presented in this article. One publication (Withers et al., Nano Lett., 2011, 11, 3912-3916.) reported a controlled synthesis of fluorinated graphene via an electron beam, where the correlation between the conductivity of the resulting materials and the width of the fluorinated area is revealed. In order to understand the detailed transport mechanism, edge-fluorinated ZGNRs with different widths and fluorination degrees are investigated. Periodic density functional theory (DFT) is employed to determine their thermodynamic stabilities and electronic structures. The associated transport models of the selected structures are subsequently constructed. The combination of a non-equilibrium Green's function (NEGF) and a standard Landauer equation is applied to investigate the global transport properties, such as the total current-bias voltage dependence. By projecting the corresponding lesser Green's function on the atomic orbital basis and their spatial derivatives, the local current density maps of the selected systems are calculated. Our results suggest that specific fluorination patterns and fluorination degrees have significant impacts on conductivity. The conjugated π system is the dominate electron flux migration pathway, and the edge effect of the ZGNRs can be well observed in the local transport properties. In addition, with an asymmetric fluorination pattern, one can trigger spin-dependent transport properties, which shows its great potential for spintronics applications.

Excited States Calculations of MoS2@ZnO and WS2@ZnO Two-Dimensional Nanocomposites for Water-Splitting Applications

Transition metal dichalcogenide (TMD) MoS2 and WS2 monolayers (MLs) deposited atop of crystalline zinc oxide (ZnO) and graphene-like ZnO (g-ZnO) substrates have been investigated by means of density functional theory (DFT) using PBE and GLLBSC exchange-correlation functionals. In this work, the electronic structure and optical properties of studied hybrid nanomaterials are described in view of the influence of ZnO substrates thickness on the MoS2@ZnO and WS2@ZnO two-dimensional (2D) nanocomposites. The thicker ZnO substrate not only triggers the decrease of the imaginary part of dielectric function relatively to more thinner g-ZnO but also results in the less accumulated charge density in the vicinity of the Mo and W atoms at the conduction band minimum. Based on the results of our calculations, we predict that MoS2 and WS2 monolayers placed at g-ZnO substrate yield essential enhancement of the photoabsorption in the visible region of solar spectra and, thus, can be used as a promising catalyst for photo-driven water splitting applications.

Implicit Solvation Methods for Catalysis at Electrified Interfaces

Implicit solvation is an effective, highly coarse-grained approach in atomic-scale simulations to account for a surrounding liquid electrolyte on the level of a continuous polarizable medium. Originating in molecular chemistry with finite solutes, implicit solvation techniques are now increasingly used in the context of first-principles modeling of electrochemistry and electrocatalysis at extended (often metallic) electrodes. The prevalent ansatz to model the latter electrodes and the reactive surface chemistry at them through slabs in periodic boundary condition supercells brings its specific challenges. Foremost this concerns the difficulty of describing the entire double layer forming at the electrified solid–liquid interface (SLI) within supercell sizes tractable by commonly employed density functional theory (DFT). We review liquid solvation methodology from this specific application angle, highlighting in particular its use in the widespread ab initio thermodynamics approach to surface catalysis. Notably, implicit solvation can be employed to mimic a polarization of the electrode’s electronic density under the applied potential and the concomitant capacitive charging of the entire double layer beyond the limitations of the employed DFT supercell. Most critical for continuing advances of this effective methodology for the SLI context is the lack of pertinent (experimental or high-level theoretical) reference data needed for parametrization.

Scalable Molecular GW Calculations: Valence and Core Spectra

We present a scalable implementation of the GW approximation using Gaussian atomic orbitals to study the valence and core ionization spectroscopies of molecules. The implementation of the standard spectral decomposition approach to the screened-Coulomb interaction, as well as a contour-deformation method, is described. We have implemented both of these approaches using the robust variational fitting approximation to the four-center electron repulsion integrals. We have utilized the MINRES solver with the contour-deformation approach to reduce the computational scaling by 1 order of magnitude. A complex heuristic in the quasiparticle equation solver further allows a speed-up of the computation of core and semicore ionization energies. Benchmark tests using the GW100 and CORE65 data sets and the carbon 1s binding energy of the well-studied ethyl trifluoroacetate, or ESCA molecule, were performed to validate the accuracy of our implementation. We also demonstrate and discuss the parallel performance and computational scaling of our implementation using a range of water clusters of increasing size.

Inq, a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory

We present inq, a new implementation of density functional theory (DFT) and time-dependent DFT (TDDFT) written from scratch to work on graphic processing units (GPUs). Besides GPU support, inq makes use of modern code design features and takes advantage of newly available hardware. By designing the code around algorithms, rather than against specific implementations and numerical libraries, we aim to provide a concise and modular code. The result is a fairly complete DFT/TDDFT implementation in roughly 12 000 lines of open-source C++ code representing a modular platform for community-driven application development on emerging high-performance computing architectures.

Computational study on noncovalent interactions between (n, n) single-walled carbon nanotubes and simple lignin model-compounds

Composites of carbon nanotubes (CNTs) and lignin are promising and potentially cheap precursors of-to this day-expensive carbon fibers. Since the control of the CNT-lignin interface is crucial to maximize fiber performance, it is imperative to understand the fundamental noncovalent interactions between lignin and CNT. In the present study a density functional theory study is conducted to investigate the fundamental noncovalent interaction strength between metallic (n, n) single-walled CNT (SWCNT) and simple lignin model molecules. In particular, the respective adsorption energies are used to gauge the strength of interaction classes (ππ interaction, CHπ hydrogen bonding and OH-related hydrogen bonding. From the data, substituent-dependent interaction trends as well as class- and curvature-dependent interaction trends are derived. Overall, we find that most of the interaction strength trends appear to be strongly influenced by geometry: flat orientation of the test molecules relative to the (n, n) SWCNT surface and small (n, n) SWCNT curvature-that is, large diameter enhances the CHπ and ππ interactions.

Adiabatic versus non-adiabatic electron transfer at 2D electrode materials

2D electrode materials are often deployed on conductive supports for electrochemistry and there is a great need to understand fundamental electrochemical processes in this electrode configuration. Here, an integrated experimental-theoretical approach is used to resolve the key electronic interactions in outer-sphere electron transfer (OS-ET), a cornerstone elementary electrochemical reaction, at graphene as-grown on a copper electrode. Using scanning electrochemical cell microscopy, and co-located structural microscopy, the classical hexaamineruthenium (III/II) couple shows the ET kinetics trend: monolayer > bilayer > multilayer graphene. This trend is rationalized quantitatively through the development of rate theory, using the Schmickler-Newns-Anderson model Hamiltonian for ET, with the explicit incorporation of electrostatic interactions in the double layer, and parameterized using constant potential density functional theory calculations. The ET mechanism is predominantly adiabatic; the addition of subsequent graphene layers increases the contact potential, producing an increase in the effective barrier to ET at the electrode/electrolyte interface.

Machine Learning-Driven High-Throughput Screening of Alloy-Based Catalysts for Selective CO2 Hydrogenation to Methanol

The revolutionary development of machine learning and data science and exploration of its application in material science are huge achievements of the scientific community in the past decade. In this work, we have reported an efficient approach of machine learning-aided high-throughput screening for finding selective earth-abundant high-entropy alloy-based catalysts for CO₂ to methanol formation using a machine learning algorithm and microstructure model. For this, we have chosen earth-abundant Cu, Co, Ni, Zn, and Mg metals to form various alloy-based compositions (bimetallic, trimetallic, tetrametallic, and high-entropy alloys) for selective CO₂ reduction reaction toward CH₃OH. Since there are several possible surface microstructures for different alloys, we have used machine learning along with DFT calculations for high-throughput screening of the catalysts. In this study, the stability of various 8-atom fcc periodic (111) surface unit cells has been calculated using the atomic-size difference factor (δ) as well as the ratio taken from Gibbs free energy of mixing (Ω). Thinking about the simplicity and accuracy, microstructure models by considering the neighboring atoms of the adsorption sites and others as Cu atoms have been considered for different adsorption sites (on-top, bridge, and hollow-hcp). Moreover, the adsorption energies of the *H, *O, *CO, *HCO, *H₂CO, and *H₃CO intermediates have been predicted using the best fitted algorithm of the training set. The predicted adsorption energies have been screened based on the pure Cu adsorption energy. Furthermore, the screened catalysts have been correlated among different adsorption site microstructures. At the end, we were able to find seven active catalysts, among which two catalysts are CuCoNiZn-based tetrametallic, three catalysts are CuNiZn-based trimetallic, and two catalysts are CuCoZn-based trimetallic alloys. Hence, this work demonstrates not an ultimate but an efficient approach for finding new product-selective catalysts, and we expect that it can be convenient for other similar types of reactions in forthcoming days.

Combining pressure and electrochemistry to synthesize superhydrides

Recently, superhydrides have been computationally identified and subsequently synthesized with a variety of metals at very high pressures. In this work, we evaluate the possibility of synthesizing superhydrides by uniquely combining electrochemistry and applied pressure. We perform computational searches using density functional theory and particle swarm optimization calculations over a broad range of pressures and electrode potentials. Using a thermodynamic analysis, we construct pressure-potential phase diagrams and provide an alternate synthesis concept, pressure-potential ([Formula: see text]), to access phases having high hydrogen content. Palladium-hydrogen is a widely studied material system with the highest hydride phase being Pd3H4 Most strikingly for this system, at potentials above hydrogen evolution and ∼ 300 MPa pressure, we find the possibility to make palladium superhydrides (e.g., PdH10). We predict the generalizability of this approach for La-H, Y-H, and Mg-H with 10- to 100-fold reduction in required pressure for stabilizing phases. In addition, the [Formula: see text] strategy allows stabilizing additional phases that cannot be done purely by either pressure or potential and is a general approach that is likely to work for synthesizing other hydrides at modest pressures.

Photo-Induced Cluster-to-Cluster Transformation of [Au37-xAgx(PPh3)13Cl10]3+ into [Au25-yAgy(PPh3)10Cl8]+: Fragmentation of a Trimer of 8-Electron Superatoms by Light

We present the photoinduced size/structure transformation of [Au_37-xAg_x(PPh₃)₁₃Cl₁₀]³⁺ (M37) into [Au_25-yAg_y(PPh₃)₁₀Cl₈]⁺ (M25) cluster. Single-crystal X-ray diffraction revealed that M37 has a tri-icosahedron M₃₆ metal core assembled via the fusion of three Au₇Ag₆ icosahedrons in a cyclic fashion and that the M₃₆ core is further protected by phosphine and chloride ligands. The M37 cluster is found to be highly sensitive toward ambient light, and the M37 → M25 transition is observed with 530 nm irradiation, monitored by time-dependent UV-vis spectroscopy, electrospray ionization mass spectrometry (ESI-MS), and femtosecond transient absorption spectroscopy. Linear-response time-dependent DFT calculations indicated that the strong absorption of the M37 cluster close to 500 nm induces an antibonding-type configuration in the induced electron density within the plane of the three 8-electron systems, possibly promoting dissociation of one of the 8-electron superatoms. This theoretical result supports the experimental observation of the sensitivity of the M37 → M25 transition to 530 nm irradiation.

Parameterization of magnetic vector potentials and fields for efficient multislice calculations of elastic electron scattering

The multislice method, which simulates the propagation of the incident electron wavefunction through a crystal, is a well established method for analysing the multiple scattering effects that an electron beam may undergo. The inclusion of magnetic effects into this method proves crucial towards simulating enhanced magnetic interaction of vortex beams with magnetic materials, calculating magnetic Bragg spots or searching for magnon signatures, to name a few examples. Inclusion of magnetism poses novel challenges to the efficiency of the multislice method for larger systems, especially regarding the consistent computation of magnetic vector potentials A and magnetic fields B over large supercells. This work presents a tabulation of parameterized magnetic (PM) values for the first three rows of transition metal elements computed from atomic density functional theory (DFT) calculations, allowing for the efficient computation of approximate A and B across large crystals using only structural and magnetic moment size and direction information. Ferromagnetic b.c.c. (body-centred cubic) Fe and tetragonal FePt are chosen to showcase the performance of PM values versus directly obtaining A and B from the unit-cell spin density by DFT. The magnetic fields of b.c.c. Fe are well described by the PM approach while for FePt the PM approach is less accurate due to deformations in the spin density. Calculations of the magnetic signal, namely the change due to A and B of the intensity of diffraction patterns, show that the PM approach for both b.c.c. Fe and FePt is able to describe the effects of magnetism in these systems to a good degree of accuracy.

Function of Doping Ru Element in the Hydrogen Evolution Reaction in Rare-Earth Transition-Metal Intermetallics

Transition metal-based intermetallics are promising electrocatalysts for replacing the commercial Pt metal in the hydrogen evolution reaction (HER). In this work, RENi₂ and RERu_0.25Ni_1.75 (RE = Pr, Tb, and Er) were synthesized and their electrocatalytic HER activities were explored. Among undoped compounds, PrNi₂ exhibits the best performance and requires an overpotential of 55 mV, while partially replacing Ni with Ru element (PrRu_0.25Ni_1.75) can greatly reduce the overpotential to 20 mV at a current density of 10 mA/cm². Such enhancement was recognized that belongs to their extrinsic property, and their intrinsic HER activities were similar after normalizing the electrocatalytic surface area. Further investigation on ScM₂ and ScRu_0.25M_1.75 (M = Co and Ni) suggests that doping Ru element in ScCo₂ will significantly enhance antibonding character around the Fermi level (E_F) and weaken hydrogen adsorption energy. On the other hand, the antibonding population for ScNi₂ and ScRu_0.25Ni_1.75 is similar at E_F, which accounts for their close intrinsic HER activities.

Time-Dependent Density Functional Theory Calculations of N- and S-Doped TiO2 Nanotube for Water-Splitting Applications

On the basis of time-dependent density functional theory (TD-DFT) we performed first-principle calculations to predict optical properties and transition states of pristine, N- and S-doped, and N+S-codoped anatase TiO2 nanotubes of 1 nm-diameter. The host O atoms of the pristine TiO2 nanotube were substituted by N and S atoms to evaluate the influence of dopants on the photocatalytic properties of hollow titania nanostructures. The charge transition mechanism promoted by dopants positioned in the nanotube wall clearly demonstrates the constructive and destructive contributions to photoabsorption by means of calculated transition contribution maps. Based on the results of our calculations, we predict an increased visible-light-driven photoresponse in N- and S-doped and the N+S-codoped TiO2 nanotubes, enhancing the efficiency of hydrogen production in water-splitting applications.

Atomic Structure Optimization with Machine-Learning Enabled Interpolation between Chemical Elements

We introduce a computational method for global optimization of structure and ordering in atomic systems. The method relies on interpolation between chemical elements, which is incorporated in a machine-learning structural fingerprint. The method is based on Bayesian optimization with Gaussian processes and is applied to the global optimization of Au-Cu bulk systems, Cu-Ni surfaces with CO adsorption, and Cu-Ni clusters. The method consistently identifies low-energy structures, which are likely to be the global minima of the energy. For the investigated systems with 23-66 atoms, the number of required energy and force calculations is in the range 3-75.

Unified Treatment of Magnons and Excitons in Monolayer CrI_{3} from Many-Body Perturbation Theory

We present first principles calculations of the two-particle excitation spectrum of CrI_{3} using many-body perturbation theory including spin-orbit coupling. Specifically, we solve the Bethe-Salpeter equation, which is equivalent to summing up all ladder diagrams with static screening, and it is shown that excitons as well as magnons can be extracted seamlessly from the calculations. The resulting optical absorption spectrum as well as the magnon dispersion agree very well with recent measurements, and we extract the amplitude for optical excitation of magnons resulting from spin-orbit interactions. Importantly, the results do not rely on any assumptions of the microscopic magnetic interactions such as Dzyaloshinskii-Moriya (DM), Kitaev, or biquadratic interactions, and we obtain a model independent estimate of the gap between acoustic and optical magnons of 0.3 meV. In addition, we resolve the magnon wave function in terms of band transitions and show that the magnon carries a spin that is significantly smaller than ℏ. This highlights the importance of terms that do not commute with S^{z} in any Heisenberg model description.

Plasmon Assisted Highly Efficient Visible Light Catalytic CO2 Reduction Over the Noble Metal Decorated Sr-Incorporated g-C3N4

The photocatalytic performance of g-C₃N₄ for CO₂ conversion is still inadequate by several shortfalls including the instability, insufficient solar light absorption and rapid charge carrier's recombination rate. To solve these problems, herein, noble metals (Pt and Au) decorated Sr-incorporated g-C₃N₄ photocatalysts are fabricated via the simple calcination and photo-deposition methods. The Sr-incorporation remarkably reduced the g-C₃N₄ band gap from 2.7 to 2.54 eV, as evidenced by the UV-visible absorption spectra and the density functional theory results. The CO₂ conversion performance of the catalysts was evaluated under visible light irradiation. The Pt/0.15Sr-CN sample produced 48.55 and 74.54 µmol h^-1 g^-1 of CH₄ and CO, respectively. These amounts are far greater than that produced by the Au/0.15Sr-CN, 0.15Sr-CN, and CN samples. A high quantum efficiency of 2.92% is predicted for the Pt/0.15Sr-CN sample. Further, the stability of the photocatalyst is confirmed via the photocatalytic recyclable test. The improved CO₂ conversion performance of the catalyst is accredited to the promoted light absorption and remarkably enhanced charge separation via the Sr-incorporated mid gap states and the localized surface plasmon resonance effect induced by noble metal nanoparticles. This work will provide a new approach for promoting the catalytic efficiency of g-C₃N₄ for efficient solar fuel production.

Assessment of the Accuracy of Density Functionals for Calculating Oxygen Reduction Reaction on Nitrogen-Doped Graphene

Experimental studies of the oxygen reduction reaction (ORR) at nitrogen-doped graphene electrodes have reported a remarkably low overpotential, on the order of 0.5 V, similar to Pt-based electrodes. Theoretical calculations using density functional theory have lent support to this claim. However, other measurements have indicated that transition metal impurities are actually responsible for the ORR activity, thereby raising questions about the reliability of both the experiments and the calculations. To assess the accuracy of the theoretical calculations, various generalized gradient approximation (GGA), meta-GGA, and hybrid functionals are employed here and calibrated against high-level wave-function-based coupled-cluster calculations (CCSD(T)) of the overpotential as well as self-interaction corrected density functional calculations and published quantum Monte Carlo calculations of O adatom binding to graphene. The PBE0 and HSE06 hybrid functionals are found to give more accurate results than the GGA and meta-GGA functionals, as would be expected, and for a low dopant concentration, 3.1%, the overpotential is calculated to be 1.0 V. The GGA and meta-GGA functionals give a lower estimate by as much as 0.4 V. When the dopant concentration is doubled, the overpotential calculated with hybrid functionals decreases, while it increases in GGA functional calculations. The opposite trends result from different potential-determining steps, the *OOH species being of central importance in the hybrid functional calculations, while the reduction of *O determines the overpotential obtained in GGA and meta-GGA calculations. The results presented here are mainly based on calculations of periodic representations of the system, but a comparison is also made with molecular flake models that are found to give erratic results due to finite size effects and geometric distortions during energy minimization. The presence of the electrolyte has not been taken into account explicitly in the calculations presented here but is estimated to be important for definitive calculations of the overpotential.

The relevance of electronic perturbations in the warm dense electron gas

Warm dense matter (WDM) has emerged as one of the frontiers of both experimental physics and theoretical physics and is a challenging traditional concept of plasma, atomic, and condensed-matter physics. While it has become common practice to model correlated electrons in WDM within the framework of Kohn-Sham density functional theory, quantitative benchmarks of exchange-correlation (XC) functionals under WDM conditions are yet incomplete. Here, we present the first assessment of common XC functionals against exact path-integral Monte Carlo calculations of the harmonically perturbed thermal electron gas. This system is directly related to the numerical modeling of x-ray scattering experiments on warm dense samples. Our assessment yields the parameter space where common XC functionals are applicable. More importantly, we pinpoint where the tested XC functionals fail when perturbations on the electronic structure are imposed. We indicate the lack of XC functionals that take into account the needs of WDM physics in terms of perturbed electronic structures.

Multifunctional Electrocatalysis on Single-Site Metal Catalysts: A Computational Perspective

Multifunctional electrocatalysts are vastly sought for their applications in water splitting electrolyzers, metal-air batteries, and regenerative fuel cells because of their ability to catalyze multiple reactions such as hydrogen evolution, oxygen evolution, and oxygen reduction reactions. More specifically, the application of single-atom electrocatalyst in multifunctional catalysis is a promising approach to ensure good atomic efficiency, tunability and additionally benefits simple theoretical treatment. In this review, we provide insights into the variety of single-site metal catalysts and their identification. We also summarize the recent advancements in computational modeling of multifunctional electrocatalysis on single-site catalysts. Furthermore, we explain each modeling step with open-source-based working examples of a standard computational approach.

The Role of Oxygenic Groups and sp3 Carbon Hybridization in Activated Graphite Electrodes for Vanadium Redox Flow Batteries

Graphite felt is a widely used electrode material for vanadium redox flow batteries. Electrode activation leads to the functionalization of the graphite surface with epoxy, OH, C=O, and COOH oxygenic groups and changes the carbon surface morphology and electronic structure, thereby improving the electrode's electroactivity relative to the untreated graphite. In this study, density functional theory (DFT) calculations are conducted to evaluate functionalization's contribution towards the positive half-cell reaction of the vanadium redox flow battery. The DFT calculations show that oxygenic groups improve the graphite felt's affinity towards the VO²⁺ /VO₂ ⁺ redox couple in the following order: C=O>COOH>OH> basal plane. Projected density-of-states (PDOS) calculations show that these groups increase the electrode's sp³ hybridization in the same order, indicating that the increase in sp³ hybridization is responsible for the improved electroactivity, whereas the oxygenic groups' presence is responsible for this sp³ increment. These insights can aid the selection of activation processes and optimization of their parameters.

Bandgap of two-dimensional materials: Thorough assessment of modern exchange-correlation functionals

The density-functional theory (DFT) approximations that are the most accurate for the calculation of bandgap of bulk materials are hybrid functionals, such as HSE06, the modified Becke-Johnson (MBJ) potential, and the GLLB-SC potential. More recently, generalized gradient approximations (GGAs), such as HLE16, or meta-GGAs, such as (m)TASK, have also proven to be quite accurate for the bandgap. Here, the focus is on two-dimensional (2D) materials and the goal is to provide a broad overview of the performance of DFT functionals by considering a large test set of 298 2D systems. The present work is an extension of our recent studies [T. Rauch, M. A. L. Marques, and S. Botti, Phys. Rev. B 101, 245163 (2020); Patra et al., J. Phys. Chem. C 125, 11206 (2021)]. Due to the lack of experimental results for the bandgap of 2D systems, G₀W₀ results were taken as reference. It is shown that the GLLB-SC potential and mTASK functional provide the bandgaps that are the closest to G₀W₀. Following closely, the local MBJ potential has a pretty good accuracy that is similar to the accuracy of the more expensive hybrid functional HSE06.

Oxygen Vacancies Nucleate Charged Domain Walls in Ferroelectrics

We study the influence of oxygen vacancies on the formation of charged 180° domain walls in ferroelectric BaTiO_{3} using first principles calculations. We show that it is favorable for vacancies to assemble in crystallographic planes, and that such clustering is accompanied by the formation of a charged domain wall. The domain wall has negative bound charge, which compensates the nominal positive charge of the vacancies and leads to a vanishing density of free charge at the wall. This is in contrast to the positively charged domain walls, which are nearly completely compensated by free charge from the bulk. The results thus explain the experimentally observed difference in electronic conductivity of the two types of domain walls, as well as the generic prevalence of charged domain walls in ferroelectrics. Moreover, the explicit demonstration of vacancy driven domain wall formation implies that specific charged domain wall configurations may be realized by bottom-up design for use in domain wall based information processing.

X-ray Spectroscopy Fingerprints of Pristine and Functionalized Graphene

In this work, we demonstrate how to identify and characterize the atomic structure of pristine and functionalized graphene materials from a combination of computational simulation of X-ray spectra, on the one hand, and computer-aided interpretation of experimental spectra, on the other. Despite the enormous scientific and industrial interest, the precise structure of these 2D materials remains under debate. As we show in this study, a wide range of model structures from pristine to heavily oxidized graphene can be studied and understood with the same approach. We move systematically from pristine to highly oxidized and defective computational models, and we compare the simulation results with experimental data. Comparison with experiments is valuable also the other way around; this method allows us to verify that the simulated models are close to the real samples, which in turn makes simulated structures amenable to several computational experiments. Our results provide ab initio semiquantitative information and a new platform for extended insight into the structure and chemical composition of graphene-based materials.

Migdal Effect in Semiconductors

When a nucleus in an atom undergoes a collision, there is a small probability of an electron being excited inelastically as a result of the Migdal effect. In this Letter, we present the first complete derivation of the Migdal effect from dark matter-nucleus scattering in semiconductors, which also accounts for multiphonon production. The rate of the Migdal effect can be expressed in terms of the energy loss function of the material, which we calculate with density functional theory methods. Because of the smaller gap for electron excitations, we find that the rate for the Migdal effect is much higher in semiconductors than in atomic targets. Accounting for the Migdal effect in semiconductors can therefore significantly improve the sensitivity of experiments such as DAMIC, SENSEI, and SuperCDMS to sub-GeV dark matter.

A transferable active-learning strategy for reactive molecular force fields

Predictive molecular simulations require fast, accurate and reactive interatomic potentials. Machine learning offers a promising approach to construct such potentials by fitting energies and forces to high-level quantum-mechanical data, but doing so typically requires considerable human intervention and data volume. Here we show that, by leveraging hierarchical and active learning, accurate Gaussian Approximation Potential (GAP) models can be developed for diverse chemical systems in an autonomous manner, requiring only hundreds to a few thousand energy and gradient evaluations on a reference potential-energy surface. The approach uses separate intra- and inter-molecular fits and employs a prospective error metric to assess the accuracy of the potentials. We demonstrate applications to a range of molecular systems with relevance to computational organic chemistry: ranging from bulk solvents, a solvated metal ion and a metallocage onwards to chemical reactivity, including a bifurcating Diels-Alder reaction in the gas phase and non-equilibrium dynamics (a model SN2 reaction) in explicit solvent. The method provides a route to routinely generating machine-learned force fields for reactive molecular systems.

High-harmonic generation in metallic titanium nitride

High-harmonic generation is a cornerstone of nonlinear optics. It has been demonstrated in dielectrics, semiconductors, semi-metals, plasmas, and gases, but, until now, not in metals. Here we report high harmonics of 800-nm-wavelength light irradiating metallic titanium nitride film. Titanium nitride is a refractory metal known for its high melting temperature and large laser damage threshold. We show that it can withstand few-cycle light pulses with peak intensities as high as 13 TW/cm², enabling high-harmonics generation up to photon energies of 11 eV. We measure the emitted vacuum ultraviolet radiation as a function of the crystal orientation with respect to the laser polarization and show that it is consistent with the anisotropic conduction band structure of titanium nitride. The generation of high harmonics from metals opens a link between solid and plasma harmonics. In addition, titanium nitride is a promising material for refractory plasmonic devices and could enable compact vacuum ultraviolet frequency combs.

A review on the use of DFT for the prediction of the properties of nanomaterials

Nanostructured materials have gained immense attraction because of their extraordinary properties compared to the bulk materials to be used in a plethora of applications in myriad fields. In this review article, we have discussed how the Density Functional Theory (DFT) calculation can be used to explain some of the properties of nanomaterials. With some specific examples here, it has been shown that how closely the different properties of nanomaterials (such as optical, optoelectronics, catalytic and magnetic) predicted by DFT calculations match well with the experimentally determined values. Some examples were discussed in detail to inspire the experimental scientists to conduct DFT-based calculations along with the experiments to derive a better understanding of the experimentally obtained results as well as to predict the properties of the nanomaterial. We have pointed out the challenges associated with DFT, and potential future perspectives of this new exciting field.

Effect of doping Cr on NH3 adsorption and NO oxidation over the FexOy/AC surface: A DFT-D study

Activated carbon supported iron-based catalysts (Fe_xO_y/AC) show good deNO_x efficiency at low temperature. The doping of chromium (Cr) greatly improves the catalyst activity. However, the detailed effect of doping Cr over Fe_xO_y/AC surface at molecular level is still a grey area. In this study, the roles of Cr dopant on gas adsorption and NO oxidation were deeply investigated by a DFT-D3 method. Results show that the synergy of Cr-Fe bimetal improves the binding capacity of Fe₂O₃/AC and Fe₃O₄/AC surfaces after doping Cr. NH₃ can be adsorbed on Cr and Fe sites to form coordinated NH₃. Doping Cr greatly improves the NH₃ adsorption property on the Fe₃O₄/AC surface. NO molecule can combine with Cr, Fe, and O sites to form nitrosyl and nitrite. The doping of Cr increases the adsorption performance of NO on the Fe₂O₃/AC and Fe₃O₄/AC surfaces, especially for Fe₃O₄/AC surface. Furthermore, NO can be oxidized to NO₂ by adsorption oxygen or active O sites of Fe_xO_y clusters. The doping of Cr restrains the formation of insoluble chelating bidentate nitrates and greatly reduces the reaction energy barrier of NO oxidation on the Fe_xO_y/AC surface, which can promote the deNO_x reaction.

Selective Interactions between Free-Atom-like d-States in Single-Atom Alloy Catalysts and Near-Frontier Molecular Orbitals

In the limit of dilute alloying-the so-called "single-atom alloy" (SAA) regime-certain bimetallic systems exhibit weak mixing between constituent metal wave functions, resulting in sharp, single-atom-like electronic states localized on the dilute component of the alloy. This work shows that when these sharp states are appropriately positioned relative to given molecular orbitals, selective hybridization is enhanced, in accordance with intuitive principles of molecular orbital theory. We demonstrate the phenomenon for activation pathways of crotonaldehyde, a model α,β-unsaturated aldehyde relevant to a wide range of chemical manufacturing. This analysis suggests new possible strategies for selectivity control in heterogeneous catalysis.

Local current analysis on defective zigzag graphene nanoribbons devices for biosensor material applications

In this contribution, we aim at investigating the mechanism of biosensing in graphene-based materials from first principles. Inspired by recent experiments, we construct an atomistic model composed of a pyrene molecule serving as a linker fragment, which is used in experiment to attach certain aptamers, and a defective zigzag graphene nanoribbons (ZGNRs). Density functional theory including dispersive interaction is employed to study the energetics of the linker absorption on the defective ZGNRs. Combining non-equilibrium Green's function and the Landauer formalism, the total current-bias voltage dependence through the device is evaluated. Modifying the distance between the linker molecule and the nanojunction plane reveals a quantitative change in the total current-bias voltage dependence, which correlates to the experimental measurements. In order to illuminate the geometric origin of these variation observed in the considered systems, the local currents through the device are investigated using the method originally introduced by Evers and co-workers. In our new implementation, the numerical efficiency is improved by applying sparse matrix storage and spectral filtering techniques, without compromising the resolution of the local currents. Local current density maps qualitatively demonstrate the local variation of the interference between the linker molecule and the nanojunction plane.

Destructive quantum interference in heterocyclic alkanes: the search for ultra-short molecular insulators

Designing highly insulating sub-nanometer molecules is difficult because tunneling conductance increases exponentially with decreasing molecular length. This challenge is further enhanced by the fact that most molecules cannot achieve full conductance suppression with destructive quantum interference. Here, we present results for a series of small saturated heterocyclic alkanes where we show that conductance is suppressed due to destructive interference. Using the STM-BJ technique and density functional theory calculations, we confirm that their single-molecule junction conductance is lower than analogous alkanes of similar length. We rationalize the suppression of conductance in the junctions through analysis of the computed ballistic current density. We find there are highly symmetric ring currents, which reverse direction at the antiresonance in the Landauer transmission near the Fermi energy. This pattern has not been seen in earlier studies of larger bicyclic systems exhibiting interference effects and constitutes clear-cut evidence of destructive σ-interference. The finding of heterocyclic alkanes with destructive quantum interference charts a pathway for chemical design of short molecular insulators using organic molecules.