Efficient DFT prediction of chemical and structural stability using van der Waals correction: application for A3B2Ga3O12garnets (A = Lu, Y and B = Al, Sc)

Several seamless van der Waals (vdW) correction methods available for a wide range of systems could be expected to enhance stability predictions by accounting for the vdW effect. The stability of material can be evaluated using chemical potential phase diagram (CPD) which reveals the elemental chemical potential conditions for a successful synthesis. In this work, viability of various vdW correction approaches in improving the accuracy of stability prediction for A3B2Ga3O12garnets (A = Lu, Y and B = Al, Sc) has been studied. From the results, we have found that vdW-df-cx, Grimme-D3, vdW-df-c09, and vdW-df2-c09 significantly improve ΔHprediction with MAPE of >5.0% lower than PBE, which exhibit their potential for stability prediction based on the CPD analysis. For CPD construction whose reliability is based on ΔHprediction, vdW-df-cx which can minimize the MAPE in ΔH, relative to experimental data, is selected as the best method among all studied vdW approaches. A more accurate description of total energy of O2molecule and the competing compounds with layered structure can be also acquired by incorporating vdW interaction. However, the MAPE in lattice constant reveals that there is no significant improvement of lattice constant prediction for the studied garnets and their competing compounds. The vdW method which gives the MAPE in lattice constant slightly lower than that of PBE is vdW-df2-b86r. Although we found that the vdW corrections can improve material stability prediction, there is still room for the development of a novel DFT-based vdW method capable of accurately predicting both the lattice constant and ΔHof solids, including complex materials like garnets.

Low-Temperature Predicted Structures of Ag2S (Silver Sulfide)

Silver sulfide phases, such as body-centered cubic argentite and monoclinic acanthite, are widely known. Traditionally, acanthite is regarded as the only low-temperature phase of silver sulfide. However, the possible existence of other low-temperature phases of silver sulfide cannot be ruled out. Until now, there have been only a few suggestions about low-temperature Ag2S phases that differ from monoclinic acanthite. The lack of a uniform approach has hampered the prediction of such phases. In this work, the use of such an effective tool as an evolutionary algorithm for the first time made it possible to perform a broad search for the model Ag2S phases of silver sulfide, which are low-temperature with respect to cubic argentite. The possibility of forming Ag2S phases with cubic, tetragonal, orthorhombic, trigonal, monoclinic, and triclinic symmetry is considered. The calculation of the cohesion energy and the formation enthalpy show, for the first time, that the formation of low-symmetry Ag2S phases is energetically most favorable. The elastic stiffness constants cij of all predicted Ag2S phases are computed, and their mechanical stability is determined. The densities of the electronic states of the predicted Ag2S phases are calculated. The prediction of low-temperature Ag2S structures indicates the possibility of synthesizing new silver sulfide phases with improved properties.

Ab initio calculations of the interaction potentials and thermodynamic functions for ArN and ArN. J Comput Chem 2023;44:1189-1198. [PMID: 36708239 DOI: 10.1002/jcc.27078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Argon compounds play an important role in the mass spectrometry with inductively coupled plasma and other applications. At the same time, there is a little knowledge of their electronic terms and thermodynamic functions due to the complexity of experimental observations. In this work, the ab initio simulations are performed to obtain the interatomic interaction potentials for the ground and excited states of ArN and ArN⁺ . Using these potentials, the vibrational-rotational partition functions and thermodynamic properties in the gas phase are calculated for these molecules at the temperature range of 298.15-10,000 K. The errors of the thermodynamic functions associated with the approximation of interatomic interaction potentials are estimated.

Regulation of Quantum Wells Width Distribution in Quasi-2D Perovskite Films for High-Performance Photodetectors

Dynamic optimization of the quantum-well (QW) width distribution in quasi-2D halide perovskite thin films is an effective approach for tuning the properties of photoelectric devices. Here, that the QWs width distribution in quasi-2D perovskite films can be controlled only by using hydroiodic acid (HI) as an additive is demonstrated. A uniform distribution of the colloidal particle size in the quasi-2D perovskite precursor solution is achieved through the formation of soluble iodoplumbate coordination complexes, PbI₃ ^- from the reaction of HI with PbI₂ , resulting in an improved phase purity in the final film. Density functional theory calculations indicate that the ideal n value quasi-2D perovskite reaction pathway through the PbI₃ ^- complex has a lower enthalpy of formation than the random nucleation pathway without the HI additive. Benefiting from this merit, a high-quality quasi-2D perovskite film with optimized phase purity delivered a balanced carrier diffusion length and improved carrier mobility. The resultant photodetectors exhibited a light on/off ratio of 50 000, a responsivity of 0.96 A W^-1 , and a detectivity of 5.7 × 10¹² Jones at 532 nm. In addition, the state-of-the-art device maintained more than 80% of its initial photocurrent after 720 h of storage at 30% relative humidity.

Testing the r2SCAN Density Functional for the Thermodynamic Stability of Solids with and without a van der Waals Correction

A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The r2SCAN revision of the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) balances numerical stability with high general accuracy. To assess the r2SCAN description of solid-state thermodynamics, we evaluate the formation and decomposition enthalpies, equilibrium volumes, and fundamental band gaps of more than 1000 solids using r2SCAN, SCAN, and PBE, as well as two dispersion-corrected variants, SCAN+rVV10 and r2SCAN+rVV10. We show that r2SCAN achieves accuracy comparable to SCAN and often improves upon SCAN's already excellent accuracy. Although SCAN+rVV10 is often observed to worsen the formation enthalpies of SCAN and makes no substantial correction to SCAN's cell volume predictions, r2SCAN+rVV10 predicts marginally less accurate formation enthalpies than r2SCAN, and slightly more accurate cell volumes than r2SCAN. The average absolute errors in predicted formation enthalpies are found to decrease by a factor of 1.5 to 2.5 from the GGA level to the meta-GGA level. Smaller decreases in error are observed for decomposition enthalpies. For formation enthalpies r2SCAN improves over SCAN for intermetallic systems. For a few classes of systems-transition metals, intermetallics, weakly bound solids, and enthalpies of decomposition into compounds-GGAs are comparable to meta-GGAs. In total, r2SCAN and r2SCAN+rVV10 can be recommended as stable, general-purpose meta-GGAs for materials discovery.

Calibrating DFT Formation Enthalpy Calculations by Multifidelity Machine Learning

The application of machine learning to predict materials properties measured by experiments are valuable yet difficult due to the limited amount of experimental data. In this work, we use a multifidelity random forest model to learn the experimental formation enthalpy of materials with prediction accuracy higher than the Perdew-Burke-Ernzerhof (PBE) functional with linear correction, PBEsol, and meta-generalized gradient approximation (meta-GGA) functionals (SCAN and r²SCAN), and it outperforms the hotly studied deep neural network-based representation learning and transfer learning. We then use the model to calibrate the DFT formation enthalpy in the Materials Project database and discover materials with underestimated stability. The multifidelity model is also used as a data-mining approach to find how DFT deviates from experiments by explaining the model output.

Some Nitrogen Rich Energetic Material Synthesis by Nucleophilic Substitution Reaction from Polynitro Aromatic Compounds

Three new nitrogen-rich energetic compounds, N-(5-chloro-2,4-dinitrophenyl)hydrazine (1), N-(5-chloro-2,4-dinitrophenyl)guanidine (2) and N-(5-chloro-2,4-dinitrophenyl)-4-aminopyrazole (3) prepared by the nucleophilic substitution reaction of 1,3-dichloro-4,6-dinitrobenzene with hydrazine, guanidinium carbonate and 4-aminopyrazole. The compounds were characterized by 1H NMR, 13C NMR, IR and mass spectroscopy. Only compound 2 could be prepared in a suitable crystal and molecular model was determined by X-ray analysis. Compounds were investigated by TG and DSC. Thermal degradation and thermokinetic behavior were investigated by Ozawa-Flynn-Wall and Kissinger-Akahira-Sunose techniques. Compounds were observed to be prone to exothermical thermal decomposition. HOMO and LUMO levels, theoretical formation enthalpy and electrostatic maps were calculated by Gaussian09. The detonation velocity and pressure were calculated by Kamlet-Jacobs equation. The compounds were assayed for antimicrobial properties.

Molecular Energies Derived from Deep Learning: Application to the Prediction of Formation Enthalpies Up to High Energy Compounds

Total electronic energies and frequencies predicted using the deep learning models ANI-1x and ANI-1ccx are converted to gas-phase formation enthalpies Δ_f H⁰ using an atom equivalent (AE) scheme for a database of CHNO compounds. As expected from the accuracy of those models in predicting reference DFT frequencies and DLPNO-CCSD(T)/CBS energies, this procedure usually outperforms DFT-based AE schemes. However, for some compounds, including energetic molecules, significant deviations from experiment are observed, larger than obtained using DFT procedures. A close examination of the GDB-11 database from which the training data was drawn reveals that many structures of interest in the energetic materials community are excluded from this extensive compilation primarily focused on drug discovery and designed with stability constraints in mind. This points to the urgent need to set up a comparable database including energetic species of interest for the design of energetic materials such as propellants or explosives.

Influence of Cr, Mn, Co and Ni Addition on Crystallization Behavior of Al13Fe4 Phase in Al-5Fe Alloys Based on ThermoDynamic Calculations

Alloying is an effective method to refine coarse grains of an Al₁₃Fe₄ phase and strengthen Al-Fe alloys. However, the grain refinement mechanism remains unclear in terms of the thermodynamics. Herein, the influence of M-element, i.e., Cr, Mn, Co and Ni, addition on the activity of Al and Fe atoms, Gibbs free energy of the Al₁₃Fe₄ nucleus in Al-Fe melt and the formation enthalpy of an Al₁₃Fe₄ phase in Al-Fe alloys is systematically investigated using the extended Miedema model, Wilson equation, and first-principle calculations, respectively. The results reveal that the addition of different M elements increases the activity of Fe atoms and reduces the Gibbs free energy of the Al₁₃Fe₄ nucleus in Al-Fe melt, where the incorporation of Ni renders the most obvious effect, followed by Mn, Co, and Cr. Additionally, the formation enthalpy decreases in the following order: Al₇₈(Fe₂₃Cr) > Al₇₈(Fe₂₃Mn) > Al₁₃Fe₄ > Al₇₈(Fe₂₃Ni) > Al₇₈(Fe₂₃Co), where the formation enthalpy of Al₇₈(Fe₂₃Ni) is close to Al₇₈(Fe₂₃Co). Moreover, the presence of Ni promotes the nucleation of the Al₁₃Fe₄ phase in Al-Fe alloys, which reveals the mechanism of grain refinement from a thermodynamics viewpoint.

Calorimetric Studies of Magnesium-Rich Mg-Pd Alloys

Solution calorimetry with liquid aluminum as the bath was conducted to measure the enthalpy of a solution of magnesium and palladium as well as the standard formation enthalpies of selected magnesium-palladium alloys. These alloys were synthesized from pure elements, which were melted in a resistance furnace that was placed in a glove box containing high-purity argon and a very low concentration of impurities, such as oxygen and water vapor. A Setaram MHTC 96 Line evo drop calorimeter was used to determine the energetic effects of the solution. The enthalpies of the Mg and Pd solutions in liquid aluminum were measured at 1033 K, and they equaled −8.6 ± 1.1 and −186.8 ± 1.1 kJ/mol, respectively. The values of the standard formation enthalpy of the investigated alloys with concentrations close to the Mg₆Pd, ε, Mg₅Pd₂, and Mg₂Pd intermetallic phases were determined as follows: −28.0 ± 1.2 kJ/mol of atoms, −32.6 ± 1.6 kJ/mol of atoms, −46.8 ± 1.4 kJ/mol of atoms, and −56.0 ± 1.6 kJ/mol of atoms, respectively. The latter data were compared with existing experimental and theoretical data from the literature along with data calculated using the Miedema model.

Structural and thermodynamic limits of layer thickness in 2D halide perovskites

In the fast-evolving field of halide perovskite semiconductors, the 2D perovskites (A')₂(A) _n-1M _n X_3n+1 [where A = Cs⁺, CH₃NH₃ ⁺, HC(NH₂)₂ ⁺; A' = ammonium cation acting as spacer; M = Ge²⁺, Sn²⁺, Pb²⁺; and X = Cl^-, Br^-, I^-] have recently made a critical entry. The n value defines the thickness of the 2D layers, which controls the optical and electronic properties. The 2D perovskites have demonstrated preliminary optoelectronic device lifetime superior to their 3D counterparts. They have also attracted fundamental interest as solution-processed quantum wells with structural and physical properties tunable via chemical composition, notably by the n value defining the perovskite layer thickness. The higher members (n > 5) have not been documented, and there are important scientific questions underlying fundamental limits for n To develop and utilize these materials in technology, it is imperative to understand their thermodynamic stability, fundamental synthetic limitations, and the derived structure-function relationships. We report the effective synthesis of the highest iodide n-members yet, namely (CH₃(CH₂)₂NH₃)₂(CH₃NH₃)₅Pb₆I₁₉ (n = 6) and (CH₃(CH₂)₂NH₃)₂(CH₃NH₃)₆Pb₇I₂₂ (n = 7), and confirm the crystal structure with single-crystal X-ray diffraction, and provide indirect evidence for "(CH₃(CH₂)₂NH₃)₂(CH₃NH₃)₈Pb₉I₂₈" ("n = 9"). Direct HCl solution calorimetric measurements show the compounds with n > 7 have unfavorable enthalpies of formation (ΔH _f), suggesting the formation of higher homologs to be challenging. Finally, we report preliminary n-dependent solar cell efficiency in the range of 9-12.6% in these higher n-members, highlighting the strong promise of these materials for high-performance devices.