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At least 181 records · Page 10

Theoretical investigation of the role of clay edges in prebiotic peptide bond formation. II - Structures and thermodynamics of the activated complex species

Molecular orbital calculations are used to study amino acid activation by anhydride formation in neutral phosphates and in tetrahedral silicate and aluminate sites on clay edges. The results agree with previous ab initio studies of Luke et al. (1984) on the reactant species. Relative heats of formation of the anhydrides indicate the extent of anhydride formation to be the greatest for Al and the least for phosphate, which is the same order as the stability of hydrolysis.

Collins, Jack R.↗

express: Extensible, high-level workflows for swifter ab initio materials modeling

In this work, we introduce an open-source Julia project, express, an extensible, lightweight, high-throughput, high-level workflow framework that aims to automate ab initio calculations for the materials science community. express is shipped with well-tested workflow templates, including structure optimization, equation of state (EOS) fitting, phonon spectrum (lattice dynamics) calculation, and thermodynamic property calculation in the framework of the quasi-harmonic approximation (QHA). It is designed to be highly modularized so that its components can be reused across various occasions, and customized workflows can be built on top of that. Users can also track the status of workflows in real-time, and rerun failed jobs thanks to the data lineage feature express provides. Finally, two working examples, i.e., all workflows applied to lime and akimotoite, are also presented in the code and this paper.

36 MATERIALS SCIENCE↗

In-Situ Atomic-Scale Revelation of Amorphous Metallic Iron Formation during Hydrogen-Driven Reduction of Iron Oxides

The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.

36 MATERIALS SCIENCE↗

The Novel Hybrid Ab Initio Model of High-Performance Structural Alloys Design for Fossil Energy Power Plants

The current project developed a novel HT-CALPHAD/DFT approach, which can quickly design new high-performance structural alloys for the application of FE power plants. The PI will mainly take charge of high-throughput DFT simulations and computational thermodynamics of the selected multicomponent alloy systems for the FE power plant applications. At the end of the project, a novel hybrid model based on high throughput CALPHAD/DFT simulations and computational thermodynamics will be developed to provide guidance on how to identify multi-component new high-performance structural alloys with much less computational effort needed. It will address the extensive computation time needed for DFT on the new alloys design. In addition, it will also address the well-known headache of DFT, i.e. how to make the accurate prediction of the high-temperature equilibria. The novel hybrid model the PI proposed will not only be applied to the design of high-performance structural alloys in FE power plants but in many different applications, such as nuclear reactors. This hybrid modeling approach includes four sections: 1) HT-CALPHAD modeling of Al-Co-Cr-Ni-Fe system with FCC and BCC phase. In this section, 3561 non-equiatomic compositions were randomly generated in order to investigate the phase stability of single FCC and BCC phases. Meanwhile, we proposed a data screening procedure to screen out the good candidates within these compositions, considering the temperature range, average density, and melting temperature, etc. 2) Investigation of FCC-Cr lattice stability in Fe-Cr system. We systematically assessed the reliability of FCC-Cr lattice stability derived by DFT and CALPHAD approaches. Meanwhile, the Fe-Cr binary system was chosen as a case study to verify the Cr lattice stability obtained by both approaches. 3) High-throughput DFT modeling on elastic properties of Al-Co-Cr-Ni-Fe systems. We predicted and established the FCC quinary elastic constant database of the Al-Co-Cr-Fe-Ni systems at 0K by using special quasi-random structure (SQS) approach. The predictions will start with pure elements of Al-Co-Cr-Fe-Ni system and will be continued with binaries, ternaries, quaternaries, and finally the quinary compositions. 3) Modeling of temperature-dependent elastic properties in Al-Co-Cr-Ni-Fe systems. In this part, we predict the thermal expansion coefficient and elastic stiffness coefficient as a function of temperature by applying quasiharmonic approximation. With this approach, the elastic properties of HEAs at elevate temperature can be estimated.

01 COAL, LIGNITE, AND PEAT↗

Iron Impurity Impairs the CO 2 Capture Performance of MgO: Insights from Microscopy and Machine Learning Molecular Dynamics

Magnesium oxide (MgO) is a promising sorbent for direct air capture (DAC) of carbon dioxide. Iron (Fe) is a common impurity in naturally occurring MgO and minerals used to produce MgO, yet a molecular-scale understanding of Fe-doping effects on carbonation is lacking. Here, in this study, we observed reduced carbonation performance in Fe-doped MgO experimentally. The energetics of adsorbing a (bi)carbonate ion on pristine and Fe-doped MgO(001) surfaces were further investigated using ab initio and machine learning potential molecular dynamics coupled with metadynamics simulations. Both pristine and Fe-doped surfaces exhibited a basic (OH – ) hydration layer, where the (bi)carbonate ion adsorption is thermodynamically favorable. However, the dissolution of surface Fe had smaller energy barriers and was more favorable than Mg. Leached Fe likely neutralized the near-surface basicity, yielding reduced reactivity on Fe-doped MgO. Our observations offer critical insights for material selection and emphasize the importance of evaluating the geologic origin of earth materials used for DAC.

36 MATERIALS SCIENCE↗

Li-Doped Ionic Liquid Electrolytes: From Bulk Phase to Interfacial Behavior

Ionic liquids have been proposed as candidate electrolytes for high-energy density, rechargeable batteries. We present an extensive computational analysis supported by experimental comparisons of the bulk and interfacial properties of a representative set of these electrolytes as a function of Li-salt doping. We begin by investigating the bulk electrolyte using quantum chemistry and ab initio molecular dynamics to elucidate the solvation structure of Li(+). MD simulations using the polarizable force field of Borodin and coworkers were then performed, from which we obtain an array of thermodynamic and transport properties. Excellent agreement is found with experiments for diffusion, ionic conductivity, and viscosity. Combining MD simulations with electronic structure computations, we computed the electrochemical window of the electrolytes across a range of Li(+)-doping levels and comment on the role of the liquid environment. Finally, we performed a suite of simulations of these Li-doped electrolytes at ideal electrified interfaces to evaluate the differential capacitance and the equilibrium Li(+) distribution in the double layer. The magnitude of differential capacitance is in good agreement with our experiments and exhibits the characteristic camel-shaped profile. In addition, the simulations reveal Li(+) to be highly localized to the second molecular layer of the double layer, which is supported by additional computations that find this layer to be a free energy minimum with respect to Li(+) translation.

molecular dynamics↗

Ab Initio Study of Atomic and Electronic Structure of Promising Ba4XMn3O12 (X = Nb, Ce, Pr) Oxides for Solar Thermochemical Hydrogen Production

The two-step metal oxide water-splitting cycle is one of the most viable approach for Solar Thermochemical Hydrogen (STCH) production. Challenges exist in finding suitable oxides that can satisfy thermodynamics of the STCH redox cycle under viable range of temperatures and partial pressures. Recently, BXM family members, i.e., Ba4NbMn3O12 (BNM), Ba4CeMn3O12 (BCM), Ba4PrMn3O12 (BPM) are discovered to exhibit promising STCH performance. However, the magnetic degrees of freedom of their experimental crystal structures is not characterized, and only hypothetical models exist for their electronic structure. We performed Monte-Carlo sampling for the magnetic spin arrangement of Mn atoms to provide explicit atomic structure models for their ground state 12R polytype and determined the most stable spin configuration for each member after structure relaxation using density functional theory (DFT) calculations. We also elucidate the most stable charge configuration (Mn3+/Mn4+ arrangement) for BNM among the existing hypothesis in literature. We investigate these strongly correlated oxides using different levels of theory (DFT+U, Hybrid-DFT) to develop better understanding of their electronic structure. These calculations allowed us to develop a model based on molecular orbital interactions that help explain the observed changes in their experimental x-ray spectroscopy measurements. Thereby, help link differences in electronic structure of BXM family members to their varying water-splitting behavior. These structure models will further facilitate future in-depth defect studies to model STCH redox cycle of these oxides.

atomic and magnetic structure↗

Localized high concentration electrolytes decomposition under electron-rich environments

Localized high concentration electrolytes have been proposed as an effective route to construct stable solid–electrolyte interphase (SEI) layers near Li-metal anodes. However, there is still a limited understanding of decomposition mechanisms of electrolyte components during SEI formation. In this work, we investigate reactivities of lithium bis(fluorosulfonyl)imide (LiFSI, salt), 1,2-dimethoxyethane (DME, solvent) and tris(2,2,2-trifluoroethyl)orthoformate (TFEO, diluent) species in DME+TFEO mixed solvents and 1M LiFSI/DME/TFEO solutions. By supplying excess of electrons into the simulation cell, LiFSI is initially reduced via a 4-electron charge transferring reaction yielding F - and N(SO 2 ) 2 3- . The local solvation environment has little effect on the subsequent TFEO reaction, which typically requires 6 |e| to decompose into F - , HCOO - , CH2CF and - OCH 2 CF 3 . Besides, TFEO dehydrogenation reaction mechanism under the attack of anions is also identified. Unlike salt and diluent, DME shows good stability with any excess of electrons. Here, the energetics of most relevant reactions are characterized. Most reactions are thermodynamically favorable with low activation barriers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energetics of high temperature degradation of fentanyl into primary and secondary products

Fentanyl is a synthetic opioid used for managing chronic pain. Due to its higher potency (50–100×) than morphine, fentanyl is also an abused drug. A sensor that could detect illicit fentanyl by identifying its thermally degraded fragments would be helpful to law enforcement. While experimental studies have probed the thermal degradation of fentanyl, little theoretical work has been done to understand the mechanism. Here, we studied the thermal degradation pathways of fentanyl using extensive ab initio molecular dynamics simulations combined with enhanced sampling via multiple-walker metadynamics. We calculated the free energy profile for each bond suggested earlier as a potential degradation point to map the thermodynamic driving forces. In conclusion, we also estimated the forward attempt rate of each bond degradation reaction to gain information about degradation kinetics.

Poudel, Bharat↗

Temperature and density dependent pair potential for deuterium under shock

Large-scale classical molecular dynamics (CMD) simulations naturally include the microscopic physics necessary for atomistic modeling of shock release at the ablator-fuel interface in an inertial confinement fusion (ICF) capsule. Here, the multi-megabar shocks utilized in ICF experiments can drive the deuterium fuel from ambient to electron volt temperatures (T) and multi-fold compression. Modeling interatomic interactions over such an extreme range of conditions is challenging for empirical bond order potentials. We generate a pair potential for deuterium with explicit temperature and mass density dependence from ab initio density functional theory molecular dynamics using the iterative Boltzmann inversion method. This potential accurately reproduces the radial distribution functions and pressures from DFT in CMD equilibrium simulations across a wide range of thermodynamic conditions, yet fails to return the expected Hugoniot relations when used in direct CMD shock simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electronic and molecular structure of carbon grains

Clusters of carbon atoms have been studied with large-scale ab initio calculations. Planar, single-sheet graphite fragments with 6 to 54 atoms were investigated, as well as the spherical C(sub 60) Buckminsterfullerene molecule. Polycyclic aromatic hydrocarbons (PAHs) have also been considered. Thermodynamic differences between diamond- and graphite-like grains have been studied in particular. Saturation of the peripheral bonds with hydrogen is found to provide a smooth and uniform convergence of the properties with increasing cluster size. For the graphite-like clusters the convergence to bulk values is much slower than for the three-dimensional complexes.

Almloef, Jan↗

Evaluation of two-particle properties within finite-temperature self-consistent one-particle Green’s function methods: Theory and application to GW and GF2

One-particle Green’s function methods can model molecular and solid spectra at zero or non-zero temperatures. One-particle Green’s functions directly provide electronic energies and one-particle properties, such as dipole moment. However, the evaluation of two-particle properties, such as $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$, can be challenging because they require a solution of the computationally expensive Bethe–Salpeter equation to find two-particle Green’s functions. We demonstrate that the solution of the Bethe–Salpeter equation can be completely avoided. Applying the thermodynamic Hellmann–Feynman theorem to self-consistent one-particle Green’s function methods, we derive expressions for two-particle density matrices in a general case and provide explicit expressions for GF2 and GW methods. Such density matrices can be decomposed into an antisymmetrized product of correlated one-electron density matrices and the two-particle electronic cumulant of the density matrix. Cumulant expressions reveal a deviation from ensemble representability for GW, explaining its known deficiencies. We analyze the temperature dependence of $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$ for a set of small closed-shell systems. Interestingly, both GF2 and GW show a non-zero spin contamination and a non-zero fluctuation of the number of particles for closed-shell systems at the zero-temperature limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unlocking AlN Piezoelectric Performance with Earth‐Abundant Dopants

Abstract The increasing demand for high‐performance piezoelectric materials and toxicity and thermal stability issues of the widely used lead zirconate titanates (PZT) have spurred a search for better alternatives in electronic devices. In comparison to PZT, group III nitrides such as aluminum nitride (AlN), are only weakly piezoelectric, but doping AlN with scandium (Sc) improves the piezoelectric response by nearly 500%. Relative to PZT, doped‐AlN piezoelectric materials are advantageous because they are far more compatible with complementary metal–oxide–semiconductor (CMOS) materials, and they maintain both piezoelectric and thermodynamic stability up to very high temperatures. Unfortunately, rare‐earth metals are notoriously expensive, and fabricating stable films with rare‐earth dopants is also challenging, limiting their use in industrial applications. In this work, ab initio calculations are combined with targeted fabrication and experimentation to identify alternative earth‐abundant dopants for AlN from the periodic table d‐block. Amongst the 23 elements screened, it is found that group IVB metals, titanium, zirconium, and hafnium induce large piezoelectric enhancements comparable to Sc. This improvement is traced to shifts in the atomic sublattice structure and changes in the local charge states. In demonstrating a highly accessible and affordable path for technological adaptation of AlN‐based piezoelectrics, this work provides the foundation for sustainable, next‐generation electronics.

Startt, Jacob↗

Prediction of stability constants of metal–ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal–ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R 2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R 2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R 2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. Here we showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure Factors for Hot Neutron Matter from Ab Initio Lattice Simulations with High-Fidelity Chiral Interactions

We present the first ab initio lattice calculations of spin and density correlations in hot neutron matter using high-fidelity interactions at next-to-next-to-next-to-leading order in chiral effective field theory. These correlations have a large impact on neutrino heating and shock revival in core-collapse supernovae and are encapsulated in functions called structure factors. Unfortunately, calculations of structure factors using high-fidelity chiral interactions were well out of reach using existing computational methods. In this Letter, we solve the problem using a computational approach called the rank-one operator (RO) method. The RO method is a general technique with broad applications to simulations of fermionic many-body systems. It solves the problem of exponential scaling of computational effort when using perturbation theory for higher-body operators and higher-order corrections. Using the RO method, we compute the vector and axial static structure factors for hot neutron matter as a function of temperature and density. Here, the ab initio lattice results are in good agreement with virial expansion calculations at low densities but are more reliable at higher densities. Random phase approximation codes used to estimate neutrino opacity in core-collapse supernovae simulations can now be calibrated with ab initio lattice calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Theoretical Investigation of Delafossite-Cu 2 ZnSnO 4 as a Promising Photovoltaic Absorber

In the quest for efficient and cost-effective photovoltaic absorber materials beyond silicon, considerable attention has been directed toward exploring alternatives. One such material, zincblende-derived Cu2ZnSnS4 (CZTS), has shown promise due to its ideal band gap size and high absorption coefficient. However, challenges such as structural defects and secondary phase formation have hindered its development. In this study, we examine the potential of another compound, Cu2ZnSnO4 (CZTO), with a similar composition to CZTS as a promising alternative. Employing ab initio density function theory (DFT) calculations in combination with an evolutionary structure prediction algorithm, we identify that the crystalline phase of delafossite structure is the most stable among the 900 (meta)stable CZTO. Its thermodynamic stability at room temperature is also confirmed by the molecular dynamics study. Excitingly, this new phase of CZTO displays a direct band gap where the dipole-allowed transition occurs, making it a strong candidate for efficient light absorptions. Furthermore, the estimation of spectroscopic limited maximum efficiency (SLME) directly demonstrates the high potential of delafossite-CZTO as a photovoltaic absorber. Our numerical results suggest that delafossite-CZTO holds promise for future photovoltaic applications.

14 SOLAR ENERGY↗

The elphbolt ab initio solver for the coupled electron-phonon Boltzmann transport equations

elphbolt is a modern Fortran (2018 standard) code for efficiently solving the coupled electron–phonon Boltzmann transport equations from first principles. Using results from density functional and density functional perturbation theory as inputs, it can calculate the effect of the non-equilibrium phonons on the electronic transport (phonon drag) and non-equilibrium electrons on the phononic transport (electron drag) in a fully self-consistent manner and obeying the constraints mandated by thermodynamics. It can calculate the lattice, charge, and thermoelectric transport coefficients for the temperature gradient and electric fields, and the effect of the mutual electron–phonon drag on these transport properties. The code fully exploits the symmetries of the crystal and the transport-active window to allow the sampling of extremely fine electron and phonon wave vector meshes required for accurately capturing the drag phenomena. The corray feature of modern Fortran, which offers native and convenient support for parallelization, is utilized. The code is compact, readable, well-documented, and extensible by design.

electron drag↗