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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Conformer-Specific Dissociation Dynamics in Dimethyl Methylphosphonate Radical Cation

The dynamics of the dimethyl methylphosphonate (DMMP) radical cation after production by strong field adiabatic ionization have been investigated. Pump-probe experiments using strong field 1300 nm pulses to adiabatically ionize DMMP and a 800 nm non-ionizing probe induce coherent oscillations of the parent ion yield with a period of about 45 fs. The yields of two fragments, PO 2 C 2 H 7 + and PO 2 CH 4 + , oscillate approximately out of phase with the parent ion, but with a slight phase shift relative to each other. We use electronic structure theory and nonadiabatic surface hopping dynamics to understand the underlying dynamics. The results show that while the cation oscillates on the ground state along the P=O bond stretch coordinate, the probe excites population to higher electronic states that can lead to fragments PO 2 C 2 H 7 + and PO 2 CH 4 + . The computational results combined with the experimental observations indicate that the two conformers of DMMP that are populated under experimental conditions exhibit different dynamics after being excited to the higher electronic states of the cation leading to different dissociation products. These results highlight the potential usefulness of these pump-probe measurements as a tool to study conformer-specific dynamics in molecules of biological interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Dynamics of HCN, HNC, and HNCO Formation in the 193 nm Photodissociation of Formamide

Formamide (NH 2 CHO) is the simplest molecule containing a peptide linkage [-NH-C($=$O)-], and it plays an essential role in the study of prebiotic chemistry. Exposure to UV irradiation allows formamide to decompose and act as a prebiotic feedstock in the formation of nucleobases and other necessary starting materials. The photodissociation mechanism of gaseous formamide at 193 nm is studied using (a) chirped-pulse Fourier transform millimeter-wave spectroscopy in the 260-290 GHz spectral region in a room-temperature flow-tube reactor at 1 mu bar pressure, (b) a combination of electronic structure theory, transition state theory, and quasiclassical trajectories, and (c) the Active Thermochemical Tables. The HCN and HNC photoproducts of hydrogenated (NH 2 CHO) and deuterated (NH 2 CDO and ND 2 CHO) formamide precursors are examined to gain insight into the photodissociation mechanism. Here, the theoretical investigation has characterized the main pathway leading to each of the HCN/HNC isomers from the precursor isotopologues. The theoretical branching ratio [HNC]/[HCN] = 2.1 for nascent photofragments agrees with the experiment. The effect of the postphotolysis HNC ↔ HCN isomerization on the [HNC]/[HCN] ratio is predicted. We report the experimental branching ratio [HNCO]: ([HNC] + [HCN]) = 12 ± 3 and propose that most of HNCO originates from dissociation on the S-1 electronic state of formamide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Determining the Ensemble N -Representability of Reduced Density Matrices

The N-representability problem for reduced density matrices remains a fundamental challenge in electronic structure theory. Following our previous work that employs a unitary-evolution algorithm based on an adaptive derivative-assembled pseudo-Trotter variational quantum algorithm to probe pure-state N-representability of reduced density matrices [J. Chem. Theory Comput. 2024, 20, 9968], in this work we propose a practical framework for determining the ensemble N-representability of a p-body matrix. This is accomplished using a purification strategy that embeds an ensemble state into a pure state defined on an extended Hilbert space, such that the reduced density matrices of the purified state reproduce those of the original ensemble. By iteratively applying variational unitaries to an initial purified state, the proposed algorithm minimizes the Hilbert-Schmidt distance between its p-body reduced density matrix and a specified target p-body matrix, which serves as a measure of the N-representability of the target. This methodology facilitates both error correction of defective ensemble reduced density matrices and quantum-state reconstruction on a quantum computer, offering a route for density-matrix refinement. We validate the algorithm with numerical simulations on systems of two, three, and four electrons in both simple models as well as molecular systems at finite temperature, demonstrating its robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Symmetry breaking forms split-off flat bands in quantum oxides controlling metal versus insulator phases

The crystal structure used as input to electronic structure calculation of conventionally bonded solids consists primarily of the standard crystallographic degrees of freedom. Quantum solids sometimes have additional microscopic degrees of freedom (m-DOF) nested within the crystallographic structure. These might include local motifs including positional (Peierls dimers, deformed octahedra, Jahn-Teller distortions), magnetic (local moment configurations) and dipolar (local ferroelectric configurations). Such motifs can be observed experimentally via local probes that avoid averaging, and theoretically as distinct total energy lowering features relative to more simplified “average crystallographic structures”. Here we examine the ability of electronic structure methods independent of strong correlation physics to explain the broad phenomenology of metal-insulator selectivity in quantum oxides by energy-lowering symmetry breaking. We do this by avoiding the restriction of considering only (i) electron-electron interactions in a fixed unresponsive lattice—as done in Mott strong correlation explanations—allowing, however, (ii) local positional and magnetic motifs that coexist within a crystallographic landscape. We find in a broad range of quantum oxides with different symmetry breaking modes the formation of split-off flat bands that can also control metallic versus insulating characteristics. The split-off band effect is common to magnetic and non-magnetic materials, including both binary and ternary oxides. One finds that when such local symmetry breaking motifs are considered in mean-field-like (e.g. density functional theory) electronic structure calculations of quantum oxides, they explain many of the observed trends in metal vs insulator phases discussed otherwise in prior literature via strong correlation in symmetry unbroken view.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

SparcleQC: Automated Input File Creation for QM/MM Studies of Protein:Ligand Complexes

SparcleQC is a Python package that, given a protein:ligand complex in the Protein Data Bank (PDB) file format, can create quantum mechanics/molecular mechanics (QM/MM)-like input files for the electronic structure theory packages PSI4, QChem, and NWChem. The resulting input files include quantum mechanical representations of the ligand and a small section of the protein, surrounded by point charges that represent the rest of the protein. Creation of these QM/MM input files includes cutting and capping the QM subregion, obtaining point charges for the protein, and adjusting charges at the QM/MM boundary; and each of these tasks are automated by the software. In this article, we describe the details of SparcleQC’s procedure, show examples of the Python API, and explain additional features that are helpful in protein:ligand interaction studies. Finally, we show that SparcleQC enables automated preparation of input files for QM/MM calculations, which can return can return accurate interaction energies in minutes, while a fully quantum mechanical computation on the protein:ligand complex could take days, if it is even possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Capturing Correlation Effects in Positron Binding to Atoms and Molecules

A major challenge in contemporary electronic structure theory involves the development of methods to describe in a balanced manner the contribution of correlation effects to energy differences. This challenge can be even greater for multicomponent systems containing more than one type of quantum particle. In the present work, we describe a flexible code for carrying out self-consistent field and configuration interaction (CI) calculations on multicomponent systems and use it to generate trial wave functions for use in diffusion Monte Carlo (DMC) calculations of the positron affinity of Be, Be 2 , Be 4 , Mg, CS 2 , and benzene. The resulting positron affinities (PAs) are in good agreement with the best values from the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An Accurate, Affordable Density Functional Tight-Binding Model for Excited State Hydrocarbon Polymer Molecular Dynamics

We have developed a density functional tight-binding model for hydrocarbon excited state dynamics by referencing to high-level electronic structure theory and incorporating a many-body repulsive energy. We then validate our model against n-octane geometry optimizations, bond dissociation scans, and vibrational frequencies. Our model is approximately 10 3 times more efficient than hybrid time-dependent density functional theory calculations with comparable accuracy. In conclusion, our efforts enable longer timescale excited state simulations of photochemistry and scattering of incident radiation.

Chemical calculations↗
DOE OSTI2025

Untangling Sources of Error in the Density-Functional Many-Body Expansion

The many-body expansion provides a framework for data-driven applications of electronic structure theory, including parametrization of classical force fields and machine learning. In this article, we demonstrate that its use significantly amplifies quadrature grid errors when modern density-functional approximations are employed. Standard grids that work well in conventional density-functional calculations result in runaway error accumulation when used with the many-body expansion. At the same time, delocalization error is also exacerbated, leading to exaggerated estimates of nonadditive n-body interactions. This is illustrated for anion–water clusters using the SCAN, r2SCAN, ωB97X-V and ωB97M-V functionals. By employing dense quadrature grids, the inherent self-interaction error is exposed, which can then be mitigated using a variety of other strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Is the Matrix Completion of Reduced Density Matrices Unique?

Reduced density matrices are central to describing observables in many-body quantum systems. In electronic structure theory, the two-particle reduced density matrix (2-RDM) suffices to determine the energy and other key properties. Recent work has used matrix completion, leveraging the low-rank structure of RDMs and approximate theoretical models, to reconstruct the 2-RDM from partial data and thus reduce the computational cost. However, matrix completion is, in general, an under-determined problem. Revisiting Rosina’s theorem (Rosina, M. Queen’s Papers on Pure and Applied Mathematics , 1968, No. 11, 369), we here show that the matrix completion is unique under certain conditions, identifying the subset of 2-RDM elements that enables its exact reconstruction from incomplete information. Building on this, we introduce a hybrid quantum–stochastic algorithm that achieves exact matrix completion, demonstrated through applications to the Fermi–Hubbard model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Discovering Ni/Cu Single-Atom Alloy as a Highly Active and Selective Catalyst for Direct Methane Conversion to Ethylene: A First-Principles Kinetic Study

Direct methane conversion to liquid fuels or value-added chemicals is a promising technology to utilize natural resources without resorting to further petroleum extraction. However, discovering efficient catalysts for this reaction is challenging due to either coke formation or unfavorable C-H bond activation. Herein, we design single-atom alloy (SAA) catalysts to simultaneously eliminate the above two bottlenecks based on mechanism-guided strategies: (1) the active single atom enables favorable C-H bond breaking and (2) the less reactive host metal facilitates C-C coupling and thus avoids strong binding of carbonaceous species. Employing electronic structure theory calculations, we screened the stability of multiple SAAs with 3d-5d transition metals atomically dispersed on a copper surface in terms of avoiding dopant aggregation and segregation. We then evaluated reactivities of the stable SAAs as catalysts for direct methane conversion to C2 products, including methane dehydrogenation and C-C coupling mechanisms. Combining selectivity analysis with kinetic modeling, we predicted that nickel dispersed on copper, i.e., Ni/Cu SAA, is a highly active and selective catalyst that can efficiently transform methane to ethylene. This work designs efficient SAA catalysts for direct methane activation and provides chemical insights into engineering compositions of SAAs to tune their catalytic performances.

Kothakonda, Manish↗
DOE OSTI2025

Unconventional low temperature decomposition of a saturated hydrocarbon over atomically-dispersed titanium-aluminum-boron catalyst

Sonochemically-synthesized atomically-dispersed titanium-aluminum-boron nanopowder (TiAlB NP) exhibits a remarkable low-temperature catalytic activation of aliphatic C-H bonds at 750 K followed by C-C bond activation thus emerging as a potent low-cost alternative to expensive platinum group metals. Here, the model saturated hydrocarbon, exo-tetrahydrodicyclopentadiene (C10H16), undergoes catalytic decomposition on TiAlB NPs in a chemical microreactor to produce 1,3-cyclopentadiene (c-C5H6), cyclopentene (c-C5H8), and molecular hydrogen (H2) as detected in situ via isomer-selective, single-photon ionization time-of-flight mass spectrometry. Extensive electronic structure theory calculations on model clusters of the catalyst decode a unique synergy among the atomic constituents of the catalyst and chemical bonding in this stepwise, retro Diels Alder reaction: Ti, although insensitive to C-H activation in its metallic state, initiates the catalysis via chemisorption of the hydrocarbon, adjacent B centers readily abstract hydrogen atoms and store them during the catalytic cycle, while Al stabilizes the catalyst structure yet providing space for critical docking sites for the departing hydrocarbons.

Biswas, Souvick↗
DOE OSTI2025

A foundation model for atomistic materials chemistry

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model-and its qualitative and at times quantitative accuracy-on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or "foundation" model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields.

Batatia, Ilyes↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2025

High-resolution spectroscopy of barium monofluoride: Odd isotopologues, hyperfine structure, and isotope shifts

Barium monofluoride (BaF) is a promising molecular species for precision tests of fundamental symmetries and interactions. We present a combined theoretical and experimental study of BaF spectra and isotope shifts, focusing in particular on the poorly understood odd isotopologues 137 BaF and 135 BaF. By comparing state-of-the-art ab initio calculations with high-resolution fluorescence and absorption spectroscopy data, we provide a benchmark for electronic structure theory and disentangle the hyperfine and rovibrational spectra of the five most abundant isotopologues, from 138 BaF to 134 BaF. The comprehensive knowledge gained enables a King plot analysis of the isotope shifts that reveals the odd-even staggering of the barium nuclear charge radii. It also paths the way for improved laser cooling of rare BaF isotopologues and crucially supports future measurements of nuclear anapole and Schiff moments.

Kogel, Felix [Univ. of Stuttgart (Germany)] (ORCID↗
DOE OSTI2025

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗
DOE OSTI2024

Iodide Double Perovskites and the Limits of their Structural Stability

AbstractWhile halide double perovskites A2M(I)M(III)X6 have attracted significant attention, examples involving iodides are rare. We examine the limits of the structural stability of iodide double perovskites, presenting the synthesis and single‐crystal structures of Cs2NaScI6 and Cs2NaYI6. Bypassing the common expectation that iodides have small band gaps, these compounds display optical gaps of 3.10 eV [M(III) = Sc] and 3.65 eV [M(III) = Y]. Cs2NaScI6 is the only iodide double perovskite to exhibit a cubic crystal structure at room temperature. Density functional theory‐based electronic structure calculations help understand the role of competing Cs3M(III)2I9 (3 : 2 : 9) phases and provide possible reasons for why iodide double perovskites based around In(III), Sb(III) and Bi(III) cations have proved elusive. We confirm design rules for halide double perovskites based around concepts of the tolerance factor and the radius ratio of the smaller, trivalent ion, but also point to situations such as what is observed for Cs2NaScI6 where a double perovskite can be trapped in a metastable structure.

Mulligan, Anya S.↗