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

Revisiting Aspirin Polymorphic Stability Using a Machine Learning Potential

In this study, we present a systematic computational investigation to analyze the long-debated free energy stability of two well-known aspirin polymorphs, denoted as Form I and Form II. Specifically, we developed a strategy to collect training configurations covering diverse interatomic interactions between representative functional groups in aspirin crystals. Utilizing a state-of-the-art neural network interatomic potential (NNIP) model, we trained an accurate machine learning potential to simulate aspirin crystal dynamics under finite temperature conditions with ∼0.46 kJ/mol/molecule accuracy. Employing the trained NNIP model, we performed thermodynamic integration to assess the free energy difference between aspirins I and II, accounting for the anharmonic effects in a large supercell consisting of 512 molecules. For the first time, our results convincingly demonstrated that Form I is more stable than Form II at 300 K, ranging from 0.74 to 1.83 kJ/mol/molecule, aligning with experimental observations. Unlike the majority of previous simulations based on (quasi)harmonic approximations in a small super cell, which often found degenerate energies between aspirins I and II, our findings underscore the importance of anharmonic effects in determining polymorphic stability ranking. Furthermore, we proposed the use of the rotational degrees of freedom of methyl and ester/phenyl groups in aspirin crystals as characteristic motions to highlight rotational entropic contribution that favors the stability of Form I. From the structural perspective, we also found that the subtle free energy difference can be used to explain the distinct thermal expansion responses as observed in both experimental and simulation data. Beyond the aspirin polymorphism, we anticipate that such entropy-driven stabilization can be broadly applicable to many other organic systems, suggesting that our approach holds great promise for stability studies in small-molecule drug design.

Benchmarking Periodic Density Functional Theory Calculations for Spin-State Energies in Spin-Crossover Systems

Spin energetics is one of the biggest challenges associated with energy calculations for electronic structure methods. The energy differences of the spin states in spin-crossover compounds are very small, making them one of the most difficult systems to calculate. Few methods provide accurate results for calculating these energy differences. In addition, studies have usually focused on calculating energetics of single molecules, while spin-crossover properties are usually experimentally studied in the solid phase. In this paper, we have used periodic boundary conditions employing methods based on density functional theory to calculate the high- and low-spin energy differences for a test case of 20 extended systems. Compounds with different metals and ligands have been selected, and the results indicate that a semiquantitative description of the energy differences can be obtained with the combination of geometry optimization using the PBE functional including many-body dispersion approach and the use of meta-GGA functionals, such as r2SCAN but especially KTBM24, for the energy calculation. Other hybrid functionals, such as TPSSh, give generally good results, but the calculation of the exact exchange with periodic boundary conditions involves a huge increase in computer time and computational resources. It makes the proposed nonhybrid functional approach (KTBM24//PBE+MB) a great advantage for the study of periodic systems.

Accurate state energetics in spin-crossover systems using pure density functional theory

The energy difference between different spin states of systems with transition metals is an outstanding challenge for electronic structure calculation methods. The small energy difference between high- and low-spin states in spin-crossover systems makes most post-Hartree-Fock or density functional theory-based methods provide inaccurate values. A test case of twenty systems showing spin transitions has been used to evaluate the accuracy of a new family of training meta-GGA (Generalized Gradient Approximation) functionals. One of the functionals of this new family provides comparable or even better values than the best functional reported so far for this type of system, the TPSSh hybrid meta-GGA functional, but without having to use the exact exchange term. It also improves the results obtained with the r2SCAN meta-GGA functional, which was the best alternative to the TPSSh hybrid functional. This makes it possible to calculate the spin energetics of any kind of compound, especially large systems or periodic structures where the exact exchange requires large computational resources.

Quantitative predictive theories through integrating quantum, statistical, equilibrium, and nonequilibrium thermodynamics

Today's thermodynamics is largely based on the combined law for equilibrium systems and statistical mechanics derived by Gibbs in 1873 and 1901, respectively, while irreversible thermodynamics for nonequilibrium systems resides essentially on the Onsager Theorem as a separate branch of thermodynamics developed in 1930s. Between them, quantum mechanics was invented and quantitatively solved in terms of density functional theory (DFT) in 1960s. These three scientific domains operate based on different principles and are very much separated from each other. In analogy to the parable of the blind men and the elephant articulated by Perdew, they individually represent different portions of a complex system and thus are incomplete by themselves alone, resulting in the lack of quantitative agreement between their predictions and experimental observations. Over the last two decades, the author's group has developed a multiscale entropy approach (recently termed as zentropy theory) that integrates DFT-based quantum mechanics and Gibbs statistical mechanics and is capable of accurately predicting entropy and free energy of complex systems. Furthermore, in combination with the combined law for nonequilibrium systems presented by Hillert, the author developed the theory of cross phenomena beyond the phenomenological Onsager Theorem. The zentropy theory and theory of cross phenomena jointly provide quantitative predictive theories for systems from electronic to any observable scales as reviewed in the present work.

A computational study of the negative LiIn modified anode and its interaction with β-Li3PS4 solid-electrolyte for battery applications

All-solid-state lithium batteries (ASSLBs) have sparked interest due to their far superior energy density compared to current commercial material, but the heightened reactivity of the negative Li electrode can compromise the long-term cyclability of the cell, calling for the introduction of passivating layers or alloy anodes. In this article, we aim to explain the outstanding stability of LiIn alloy-based anodes over extended cycling by comparing its bulk and interface properties to Li-metal. Using density functional theory, we conducted an in-depth analysis of the LiIn surfaces' formation and subsequent structural stability in interfaces with the solid electrolyte β-Li3PS4. Several LiIn facets are shown to possess sufficient structural stability, with the (110) surface being the most stable. The stable interfaces established with the β-Li3PS4(100) surface featured favorable adhesion energy, low strain energy, and little reconstruction. By comparing these interface properties with the bulk properties of Li-metal and LiIn, we highlighted the influence of the cohesion energy, Fermi energy level, and band position of the two materials in the long-term stability of their anodes under battery conditions.

Participation of electrochemically inserted protons in the hydrogen evolution reaction on tungsten oxides

Understanding the mechanisms by which electrodes undergo the hydrogen evolution reaction (HER) is necessary to design better materials for aqueous energy storage and conversion. Here, we investigate the HER mechanism on tungsten oxide electrodes, which are stable in acidic electrolytes and can undergo proton-insertion coupled electron transfer concomitant with the HER. Electrochemical characterization showed that anhydrous and hydrated tungsten oxides undergo changes in HER activity coincident with changes in proton composition, with activity in the order HxWO3·H2O > HxWO3 > HxWO3·2H2O. We used operando X-ray diffraction and density functional theory to understand the structural and electronic changes in the materials at high states of proton insertion, when the oxides are most active towards the HER. H0.69WO3·H2O and H0.65WO3 have similar proton composition, structural symmetry, and electronic properties at the onset of the HER, yet exhibit different activity. We hypothesize that the electrochemically inserted protons can diffuse in hydrogen bronzes and participate in the HER. This would render the oxide volume, and not just the surface, as a proton and electron reservoir at high overpotentials. HER activity is highest in HxWO3·H2O, which optimizes both the degree of proton insertion and solid-state proton transport kinetics. Our results highlight the interplay between the HER and proton insertion-coupled electron transfer on transition metal oxides, many of which are non-blocking electrodes towards protons.

Performance of Density Functionals for Excited-State Properties of Isolated Chromophores and Exciplexes: Emission Spectra, Solvatochromic Shifts, and Charge-Transfer Character

This study assesses the performance of various meta-generalized gradient approximation (meta-GGA), global hybrid, and range-separated hybrid (RSH) density functionals in capturing the excited-state properties of organic chromophores and their excited-state complexes (exciplexes). Motivated by their uses in solar energy harvesting and photoredox CO2 reduction, we use oligo-(p-phenylenes) and their excited-state complexes with triethylamine as model systems. We focus on the fluorescence properties of these systems, specifically emission energies. We also consider solvatochromic shifts and wave function characteristics. The latter is described by using reduced quantities such as natural transition orbitals (NTOs) and exciton descriptors. The functionals are benchmarked against the experimental fluorescence spectra and the equation-of-motion coupled-cluster method with single and double excitations. Both in isolated chromophores and in exciplexes, meta-GGA functionals drastically underestimate the emission energies and exhibit significant exciton delocalization and anticorrelation between electron and hole motion. The performance of global hybrid functionals is strongly dependent on the percentage of exact exchange. Our study identifies RSH GGAs as the best-performing functionals, with ωPBE demonstrating the best agreement with experimental results. RSH meta-GGAs often overestimate emission energies in exciplexes and yield larger hole NTOs. Their performance can be improved by optimally tuning the range-separation parameter.

Selective Synthesis of Defect-Rich LaMnO3 by Low-Temperature Anion Cometathesis

The synthesis of complex oxides at low temperatures brings forward aspects of chemistry not typically considered. This study focuses on perovskite LaMnO3, which is of interest for its correlated electronic behavior tied to the oxidation state and thus the spin configuration of manganese. Traditional equilibrium synthesis of these materials typically requires synthesis reaction temperatures in excess of 1000 °C, followed by subsequent annealing steps at lower temperatures and different p(O2) conditions to manipulate the oxygen content postsynthesis (e.g., LaMnO3+x). Double-ion exchange (metathesis) reactions have recently been shown to react at much lower temperatures (500-800 °C), highlighting a fundamental knowledge gap for how solids react at lower temperatures. Here, we revisit the metathesis reaction, LiMnO2 + LaOX, where X is a halide or mixture of halides, using in situ synchrotron X-ray diffraction. These experiments reveal low reaction onset temperatures (ca. 450-480 °C). The lowest reaction temperatures are achieved by a mixture of lanthanum oxyhalide precursors: 2 LiMnO2 + LaOCl + LaOBr. In all cases, the resulting products are the expected alkali halide salt and defective La1-ϵMn1-ϵO3, where ϵ = x/(3 + x). We observe a systematic variation in defect concentration, consistent with a rapid stoichiometric local equilibration of the precursors and the subsequent global thermodynamic equilibration with O2 (g), as revealed by computational thermodynamics. Together, these results reveal how the inclusion of additional elements (e.g., Li and a halide) leads to the local equilibrium, particularly at low reaction temperatures for solid-state chemistry.

Comparing first-principles density functionals plus corrections for the lattice dynamics of YBa2Cu3O6

The enigmatic mechanism underlying unconventional high-temperature superconductivity, especially the role of lattice dynamics, has remained a subject of debate. Theoretical insights have long been hindered due to the lack of an accurate first-principles description of the lattice dynamics of cuprates. Recently, using the r2SCAN meta-generalized gradient approximation (meta-GGA) functional, we have been able to achieve accurate phonon spectra of an insulating cuprate YBa2Cu3O6 and discover significant magnetoelastic coupling in experimentally interesting Cu-O bond stretching optical modes [Ning et al., Phys. Rev. B 107, 045126 (2023)]. We extend this work by comparing Perdew-Burke-Ernzerhof and r2SCAN performances with corrections from the on-site Hubbard U and the D4 van der Waals (vdW) methods, aiming at further understanding on both the materials science side and the density functional side. We demonstrate the importance of vdW and self-interaction corrections for accurate first-principles YBa2Cu3O6 lattice dynamics. Since r2SCAN by itself partially accounts for these effects, the good performance of r2SCAN is now more fully explained. In addition, the performances of the Tao-Mo series of meta-GGAs, which are constructed in a different way from the strongly constrained and appropriately normed (SCAN) meta-GGA and its revised version r2SCAN, are also compared and discussed.

Reworking the Tao-Mo exchange-correlation functional. I. Reconsideration and simplification

The revised, regularized Tao-Mo (rregTM) exchange-correlation density functional approximation (DFA) [A. Patra, S. Jana, and P. Samal, J. Chem. Phys. 153, 184112 (2020) and Jana et al., J. Chem. Phys. 155, 024103 (2021)] resolves the order-of-limits problem in the original TM formulation while preserving its valuable essential behaviors. Those include performance on standard thermochemistry and solid data sets that is competitive with that of the most widely explored meta-generalized-gradient-approximation DFAs (SCAN and r2SCAN) while also providing superior performance on elemental solid magnetization. Puzzlingly however, rregTM proved to be intractable for de-orbitalization via the approach of Mejía-Rodríguez and Trickey [Phys. Rev. A 96, 052512 (2017)]. We report investigation that leads to diagnosis of how the regularization in rregTM of the z indicator functions (z = the ratio of the von-Weizsäcker and Kohn-Sham kinetic energy densities) leads to non-physical behavior. We propose a simpler regularization that eliminates those oddities and that can be calibrated to reproduce the good error patterns of rregTM. We denote this version as simplified, regularized Tao-Mo, sregTM. We also show that it is unnecessary to use rregTM correlation with sregTM exchange: Perdew-Burke-Ernzerhof correlation is sufficient. The subsequent paper shows how sregTM enables some progress on de-orbitalization.

Temperature dependence of O solubility in liquid Na by atomistic simulation of Na(l)-Na2O(s) interfaces using corrected machine learning potential: a step towards simulating Na combustion

Liquid Na combustion is a significant safety concern in sodium-cooled fast reactors. Atomistic simulations are an alternative to experiments for studying detailed mechanisms of complex combustion processes. However, accurate simulations of the interfaces involved in combustion are challenging even for density functional theory (DFT), because the systematic error between different chemical systems cannot be fully cancelled. Herein, we report the achievement of a key milestone in atomistic simulation of liquid Na combustion, which involves the development of a machine learning (ML) moment tensor potential that allows accurate simulation of interface systems between liquid Na and solid Na2O. The ML potential is trained by using supervised and active learning to ensure DFT-level accuracy. An empirical correction is then applied to achieve experimental accuracy by reducing systematic error. Consequently, the basic properties of liquid Na and solid Na2O are accurately simulated. In addition, with empirical correction, experimental O solubility data for liquid Na at 350-900 K are reproduced by using interface molecular dynamics simulations and a thermodynamic model. The temperature dependence of the enthalpy and entropy of the Na2O solution and their effect on O solubility are evaluated. The results show that, despite the increase in solution enthalpy with temperature, O solubility increases more rapidly than the linear Arrhenius plot due to the effect of solution entropy. The results of this study indicate that, with appropriate correction, ML potentials can achieve near-experimental accuracy, beyond the accuracy of DFT, in interface simulations and material properties calculations, paving the way for sodium combustion simulations in the future.

Performance of the r2SCAN Functional in Transition Metal Oxides

We assess the accuracy and computational efficiency of the recently developed meta-generalized gradient approximation (metaGGA) functional, restored regularized strongly constrained and appropriately normed (r²SCAN), in transition metal oxide (TMO) systems and compare its performance against SCAN. Specifically, we benchmark the r²SCAN-calculated oxidation enthalpies, lattice parameters, on-site magnetic moments, and band gaps of binary 3d TMOs against the SCAN-calculated and experimental values. Additionally, we evaluate the optimal Hubbard U correction required for each transition metal (TM) to improve the accuracy of the r²SCAN functional, based on experimental oxidation enthalpies, and verify the transferability of the U values by comparing against experimental properties on other TM-containing oxides. Notably, including the U-correction with r²SCAN increases the lattice parameters, on-site magnetic moments, and band gaps of TMOs, apart from an improved description of the ground state electronic state in narrow band gap TMOs. The r²SCAN and r²SCAN+U calculated oxidation enthalpies follow the qualitative trends of SCAN and SCAN+U, with r²SCAN and r²SCAN+U predicting marginally larger lattice parameters, smaller magnetic moments, and lower band gaps compared to SCAN and SCAN+U, respectively. We observe the overall computational time (i.e., for all ionic+electronic steps) required for r²SCAN(+U) to be lower than SCAN(+U). Thus, the r²SCAN(+U) framework can offer a reasonably accurate description of the ground state properties of TMOs with better computational efficiency than SCAN(+U).