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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2021

Non-local corrections to the typical medium theory of Anderson localization

We use the recently developed finite cluster typical medium approach to study the Anderson localization transition in three dimensions. Applying our method to the box and binary alloy disorder distributions, we find a fast convergence with the cluster size. We demonstrate the importance of the typical medium environment and the non-local spatial correlations for the proper characterization of the localization transition. As the cluster size increases, our typical medium cluster method recovers the correct critical disorder strength for the transition. Our findings highlight the importance of the non-local cluster corrections for capturing the localization behavior of the mobility edge trajectories. Our results demonstrate that the typical medium cluster approach developed here provides a consistent and systematic description of the Anderson localization transition in the framework of the effective medium embedding schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling bicarbonate formation in an alkaline solution with multi-level quantum mechanics/molecular dynamics simulations

Understanding carbonate speciation and how it may be modulated is essential for the advancement of carbon dioxide (CO 2 ) capture and storage technologies, which often rely on the transformation of CO 2 into carbonate, e.g. via the formation of carbonate minerals. To date, few atomic-level, quantum-mechanics-based simulations have been carried out to characterize how carbonic acid (H 2 CO 3 ) and bicarbonate ($HCO^{-}_{3}$) form in aqueous solution, and how pH affects this process. Recently, Martirez and Carter utilized rare-event sampling density functional theory molecular dynamics simulations in combination with multi-level embedded correlated wavefunction theory, thus accounting for both solvent dynamics and electron correlation accurately, to elucidate the mechanism of H 2 CO 3 formation in neutral solution (J. Am. Chem. Soc., 145, 12561, 2023). Here, we perform a complementary simulation using the same method to map out the energetics of $HCO^{-}_{3}$ formation from dissolved CO 2 in basic solution. We find that, as in H 2 CO 3 formation, including water dynamics is important to obtain an accurate prediction of the energetics for the aforementioned reaction. Furthermore, only with MD did we identify the correct pathway for the reaction, in which water – not hydroxide – acts as the initial nucleophile and only at the transition state does it lose a proton.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Identification of dislocation-related and point-defects in III-As layers for silicon photonics applications

Abstract The aim of this paper is to identify, analyze and compare the defects present in III-As, as a function of dislocation density, and as a function of the presence/absence of quantum dots (QDs). Such materials are of fundamental importance for the development of lasers and photodiodes for silicon photonics. The study is based on an extensive deep-level transient spectroscopy investigation, carried out on GaAs pin diodes grown on Si and on GaAs (that differ in the dislocation density), with and without embedded QDs. The original results described in this paper demonstrate that: (a) we were able to identify four different defects within the device grown on Si (three electron and one hole traps) and one defect (hole trap) in the device on GaAs, common to both samples; (b) all the majority carrier traps identified are located near midgap, i.e. are efficient non-radiative recombination centers; (c) such defects are absent (or non-detectable) in the sample grown on GaAs substrate, having a very low dislocation density; (d) the presence of QDs does not result in additional defects within the semiconductor material; (e) the analysis of the capture kinetics revealed that two of the identified traps are related to point defects, whereas the other two traps can be associated with point defects located near a dislocation; (f) a comparison with previous reports indicate that the detected traps are related to native III-As defects, or to oxygen-related complexes.

Physics↗
DOE OSTI2026

C–C Bond Formation during Electrochemical CO 2 Reduction on Pristine Cu(100) Unlikely to Involve Adsorbed CO at Any Potential

Formation of hydrocarbons containing two or more carbon atoms (C 2+ ) during heterogeneous electrochemical CO and CO 2 reduction (ECOR and ECO 2 R) only occurs, among pure metals, on Cu electrodes. Moreover, the activity and selectivity is facet dependent, with Cu(100) generally preferentially forming ethylene over methane. Previously, we found via quantum-mechanics-based modeling that, unlike standard density functional theory, more accurate correlated wavefunction methods predict that non-electroactive coupling pathways involving two adsorbed COs (*CO) or a *CO and a *COH to form C–C bonds on Cu(100) are kinetically inhibited, with the former also thermodynamically unfavorable. Here, we extend that embedded complete active space second order perturbation theory (ECASPT2) study, further showing that electrochemical coupling of two *COs to form an anionic dimer [OC*–*CO] (1+δ)– , followed by protonation to form [OC*–*COH] δ− , is not kinetically competitive with the reduction of *CO to *COH at relevant ECO/CO 2 R potentials. Our simulations therefore suggest that the ability of Cu(100) to electrochemically synthesize C 2+ molecules from CO and CO 2 is unlikely to be via *CO, at least on pristine Cu(100). Instead, hydrogenated CO species (*COH, *CH x OH, or *CH x ) are most likely to be the key intermediates in C–C bond formation.

Martirez, John Mark P. [Princeton Plasma Physics L↗
DOE OSTI2021

Excited-state potentials for modelling dense plasmas from first principles

The modelling of dense plasmas using finite-temperature density functional theory has proven very successful in determining transport properties and the equation of state of systems where quantum many-body effects and correlations play a key role in their structure. Here we show how excited-state projector augmented- wave potentials can be used to extend these calculations to explicitly model core-hole states, allowing for the calculation of the electronic structure of a range of integer charge configurations embedded in a dense plasma environment. Our excited-state potentials show good agreement with all-electron calculations at finite-temperatures, motivating their use as an efficient approach in modelling from first principles both the structure of strongly-coupled non-equilibrium plasmas and their interaction with intense X-rays.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Controlled Organization of Inorganic Materials Using Biological Molecules for Activating Therapeutic Functionalities

Precise control over the assembly of biocompatible three-dimensional (3D) nanostructures would allow for programmed interactions within the cellular environment. Nucleic acids can be used as programmable crosslinkers to direct the assembly of quantum dots (QDs) and tuned to demonstrate different interparticle binding strategies. In this work, morphologies of self-assembled QDs are evaluated via gel electrophoresis, transmission electron microscopy, small-angle X-ray scattering, and dissipative particle dynamics simulations, with all results being in good agreement. The controlled assembly of 3D QD organizations is demonstrated in cells via the colocalized emission of multiple assembled QDs, and their immunorecognition is assessed via enzyme-linked immunosorbent assays. RNA interference inducers are also embedded into the interparticle binding strategy to be released in human cells only upon QD assembly, which is demonstrated by specific gene silencing. The programmability and intracellular activity of QD assemblies offer a strategy for nucleic acids to imbue the structure and therapeutic function into the formation of complex networks of nanostructures, while the photoluminescent properties of the material allow for optical tracking in cells in vitro.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

Simulations of carbon dioxide (CO 2 ) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO 2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. Here, we show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

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

Determination of Pion and Kaon Structure Using the Sullivan Process at Moderate to large Fractional Momentum

Significant progress has been made in describing the structure of hadrons in terms of Quantum ChromoDynamics (QCD) degrees of freedom. The recently developed framework of Generalized Parton Distribtions (GPDs) may provide the path towards three-dimensional imaging of the hadronic structure. Integrating the GPDs over the fractional momentum (x), the form factors are obtained which are integrally related to understanding the emergent hadron mass-generating mechanism (EHM) embedded in QCD and the mass-scale that characterizes the proton [Roberts (2016)]. The Sullivan process, in which one scatters electrons off the proton?s virtual meson cloud and thus creates a meson target, is used to probe this structure. Studies of kaon electroproduction offer unique opportunities in this. The last two decades saw a dramatic improvement in the precision of charged meson form factor data, and new results have become available on the transition form factor. The KaonLT experiment (E12-09-011) carried out in Hall C at Jefferson Lab (Jlab) was designed to measure longitudinal/transverse (L/T) separated kaon cross sections required to access form factors and GPDs [Bosted et al. (2008)]. KaonLT aimed to confirm the exclusive kaon electroproduction mechanism, which is essential for determining the kaon form factor and investigating GPDs. The results obtained from this experiment have provided the highest Q2 for L-T separated kaon electroproduction cross section, and it is the first time that a separated kaon cross-section measurement has been carried out above W = 2:2GeV.

Trotta, Richard↗
DOE OSTI2025

Electronic structure theory with molecular point group symmetries on quantum annealers

Quantum computation has the potential to revolutionize quantum chemistry through major speedups in computation times and an exponential reduction in computational resources. Here, we combine the symmetry-adapted Jordan–Wigner encoding based on the full Boolean symmetry group $\mathbb{Z}$$^{k}_{2}$ with our new implementation of the Xia–Bian–Kais (XBK) method for improving the efficiency of electronic structure theory calculations on quantum annealers, particularly by reducing the number of qubits needed to achieve the same accuracy. By providing a more extensive symmetry-adapted encoding (SAE) than previous work, we are able to simulate molecules larger than those previously reported that have been studied using methods developed for quantum annealers and without using an active space. We calculated the potential energy surfaces of H 2 , LiH, He 2 , H 2 O, O 2 , N 2 , Li 2 , F 2 , CO, BH 3 , NH 3 , and CH 4 , with the largest molecule in the STO-6G basis set requiring 16 qubits with our SAE, and compared them with full configuration interaction results. The application of SAE to the XBK method provides an exponential reduction in the size of the Hilbert space and scales well with the size of the problem. It does not introduce significant additional errors for even or large values of a key variational parameter that determines the number of ancilla qubits used in the XBK method’s Hamiltonian embedding, or for certain molecules such as He 2 and H 2 O. Here, we provide an explanation for this behavior and a recommendation on the usage of our method. In addition, we briefly discuss the potential of extracting electronic excited states from our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Relativistic self-consistent G W : Exact two-component formalism with one-electron approximation for solids

We present a formulation of relativistic self-consistent GW for solids based on the exact two-component formalism with one-electron approximation (X2C1e) and nonrelativistic Coulomb interactions. Our theory allows us to study scalar relativistic effects, spin-orbit coupling, and the interplay of relativistic effects with electron correlation without adjustable parameters. Our all-electron implementation is fully ab initio and does not require a pseudopotential constructed from atomic calculations. We examine the effect of the X2C1e approximation by comparison to the established four-component formalism and reach an excellent agreement. The simplicity of X2C1e enables the construction of higher order theories, such as embedding theories, on top of perturbative calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Many-body factorization and position–momentum equivalence of nuclear short-range correlations

While mean-field approximations, such as the nuclear shell model, provide a good description of many bulk nuclear properties, they fail to capture the important effects of nucleon–nucleon correlations such as the short-distance and high-momentum components of the nuclear many-body wave function1. Here, we study these components using the effective pair-based generalized contact formalism and ab initio quantum Monte Carlo calculations of nuclei from deuteron to 40 Ca. We observe a universal factorization of the many-body nuclear wave function at short distance into a strongly interacting pair and a weakly interacting residual system. The residual system distribution is consistent with that of an uncorrelated system, showing that short-distance correlation effects are predominantly embedded in two-body correlations. Spin- and isospin-dependent ‘nuclear contact terms’ are extracted in both coordinate and momentum space for different realistic nuclear potentials. The contact coefficient ratio between two different nuclei shows very little dependence on the nuclear interaction model. These findings thus allow extending the application of mean-field approximations to short-range correlated pair formation by showing that the relative abundance of short-range pairs in the nucleus is a long-range (that is, mean field) quantity that is insensitive to the short-distance nature of the nuclear force.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Engineering Robust Metallic Zero-Mode States in Olympicene Graphene Nanoribbons

Metallic graphene nanoribbons (GNRs) represent a critical component in the toolbox of low-dimensional functional materials technology serving as 1D interconnects capable of both electronic and quantum information transport. The structural constraints imposed by on-surface bottom-up GNR synthesis protocols along with the limited control over orientation and sequence of asymmetric monomer building blocks during the radical step-growth polymerization have plagued the design and assembly of metallic GNRs. Here, we report the regioregular synthesis of GNRs hosting robust metallic states by embedding a symmetric zero-mode (ZM) superlattice along the backbone of a GNR. Tight-binding electronic structure models predict a strong nearest-neighbor electron hopping interaction between adjacent ZM states, resulting in a dispersive metallic band. First-principles density functional theory-local density approximation calculations confirm this prediction, and the robust, metallic ZM band of olympicene GNRs is experimentally corroborated by scanning tunneling spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Trapping-induced quantum beats in a van-der-Waals heterostructure microcavity observed by two-dimensional micro-spectroscopy

Spatial confinement has been frequently engineered to control the flow and relaxation dynamics of exciton polaritons. While widely investigated in GaAs microcavities, exciton-polariton coupling between discretized polariton modes arising from spatially confined 2D crystals been has been less exhaustively studied. Here, we use coherent 2D photoluminescence-detected micro-spectroscopy to detect oscillating 2D peaks exclusively from a spatial trap in a microcavity with an embedded van-der-Waals heterostructure at room temperature. We observe a wide variation of oscillatory phases as a function of spectral position within the 2D spectrum, which suggests the existence of a coupling between the discretized polariton modes. The latter is accompanied by the generation of coherent phonons.

Materials Science↗
DOE OSTI2021

Inkjet-Based 3D Printing: From Quantum Dots to Steel Tools

Inkjet-based additive manufacturing (AM) technologies are highly versatile among manufacturing processes due to their ability to shape any material in powder or ink form. The two inkjet-based AM technologies are binder jetting and material jetting, and as each of their names suggest, the former uses inkjet to deposit binder into the actual build material and the latter uses inkjet to deposit the actual build material. With each of these technologies comes unique opportunities in the form of embedding functional components within the build, creating material gradients within parts by selectively layering feedstocks, shaping non-weldable materials, and creating low-cost tooling with conformal cooling channels. Dr. Amy Elliott at Oak Ridge National Laboratory has explored a variety of materials and approaches with inkjet-based manufacturing technologies, focusing on industry-relevant applications such as injection molding tooling and mining drills.

Elliott, Amy↗
DOE OSTI2023

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic arrangements in an amorphous CoFeB ribbon extracted via an analysis of radial distribution functions

Here we discuss the atomic structure of amorphous ferromagnetic FeCoB alloys, which are used widely in spintronics applications. Specifically, we obtain the pair-distribution functions for various atomic pairs based on high-energy x-ray diffraction data taken from an amorphous Co 20 Fe 61 B 19 specimen. We start our reverse Monte Carlo cycles to determine the disordered structure with a two-phase model in which a small amount of cobalt is mixed with Fe 23 B 6 as a second phase. The structure of the alloy is found to be heterogeneous, where the boron atoms drive disorder through the random occupation of the atomic network. Our analysis also indicates the presence of small cobalt clusters that are embedded in the iron matrix and percolating the latter throughout the structure. This morphology can explain the enhanced spin polarization observed in amorphous magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗