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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2024

Simple Scattering: Lipid nanoparticle structural data repository

Lipid nanoparticles (LNPs) are being intensively researched and developed to leverage their ability to safely and effectively deliver therapeutics. To achieve optimal therapeutic delivery, a comprehensive understanding of the relationship between formulation, structure, and efficacy is critical. However, the vast chemical space involved in the production of LNPs and the resulting structural complexity make the structure to function relationship challenging to assess and predict. New components and formulation procedures, which provide new opportunities for the use of LNPs, would be best identified and optimized using high-throughput characterization methods. Recently, a high-throughput workflow, consisting of automated mixing, small-angle X-ray scattering (SAXS), and cellular assays, demonstrated a link between formulation, internal structure, and efficacy for a library of LNPs. As SAXS data can be rapidly collected, the stage is set for the collection of thousands of SAXS profiles from a myriad of LNP formulations. In addition, correlated LNP small-angle neutron scattering (SANS) datasets, where components are systematically deuterated for additional contrast inside, provide complementary structural information. The centralization of SAXS and SANS datasets from LNPs, with appropriate, standardized metadata describing formulation parameters, into a data repository will provide valuable guidance for the formulation of LNPs with desired properties. To this end, we introduce Simple Scattering, an easy-to-use, open data repository for storing and sharing groups of correlated scattering profiles obtained from LNP screening experiments. Here, we discuss the current state of the repository, including limitations and upcoming changes, and our vision towards future usage in developing our collective knowledge base of LNPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Iron( IV ) alkyl complexes: electronic structure contributions to Fe–C bond homolysis and migration reactions that form N–C bonds from N 2

High-valent iron alkyl complexes are rare, as they are prone to Fe–C bond homolysis. Here, we describe an unusual way to access formally iron(IV) alkyl complexes through double silylation of iron(I) alkyl dinitrogen complexes to form an NNSi 2 group. Spectroscopically validated computations show that the disilylehydrazido(2−) ligand stabilizes the formal iron(IV) oxidation state through a strongly covalent Fe–N π-interaction, in which one π-bond fits an “inverted field” description. This means that the two bonding electrons are localized more on the metal than the ligand, and thus an iron(II) resonance structure is a significant contributor, similar to the previously-reported phenyl analogue. However, in contrast to the phenyl complex which has an S = 1 ground state, the ground state of the alkyl complex is S = 2, which places one electron in the π* orbital, leading to longer and weaker Fe–N bonds. The reactivity of these hydrazido(2−) complexes is dependent on the steric and electronic properties of the specific alkyl group. When the alkyl group is the bulky trimethylsilylmethyl, the formally iron(IV) species is stable at room temperature and no migration of the alkyl ligand is observed. However, the analogous complex with the smaller methyl ligand does indeed undergo migration of the carbon-based ligand to the NNSi 2 group to form a new N–C bond. This migration is followed by isomerization of the hydrazido ligand, and the product exists as two isomers that have distinct η 1 and η 2 binding of the hydrazido group. Lastly, when the alkyl group is benzyl, the Fe–C bond homolyzes to give a three-coordinate hydrazido(2−) complex which is likely due to the greater stability of a benzyl radical compared to that for methyl or trimethylsilylmethyl. These studies demonstrate the availability of a hydrocarbyl migration pathway at formally iron(IV) centers to form new N–C bonds directly to N 2 , though product selectivity is highly dependent on the identity of the migrating group.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Synthesis, Structural Characterization and Chemical Bonding of Sr 7 Li 6 Sn 12 and its Quaternary Derivatives with Eu and Alkaline Earth Metal (Mg, Ca, Ba) Substitutions. A Tale of Seven Li‐Containing Stannides and Two Complex Crystal Structures

In this paper, we discuss the synthesis and the structural characterization of the new ternary compound Sr 7 Li 6 Sn 12 and its six quaternary derivatives, where alkaline earth metals (Ca, Mg, Ba) and the rare earth metal Eu are substituted, yielding crystalline phases of monoclinic or orthorhombic symmetry. The title compounds were synthesized via high‐temperature solid‐state reactions of the corresponding elements. The crystal structures were determined by single‐crystal X‐ray diffraction methods. The (Sr,Ca) 7 Li 6 Sn 12 and Eu 7 (Mg,Li) 6 Sn 12 phases represent a new structure type (space group P 2/ m , No. 10) while Sr 7 Li 6 Sn 12 and the rest of the title phases crystallize in the orthorhombic base‐centered space group Cmmm (No. 65) which is similar to the Eu 7 Li 8– x Sn 10+ x ( x ≈ 2.0) phase with the Ce 7 Li 8 Ge 10 structure type (Pearson code oC 50). Careful examination of the resulting structures shows intricate disordering between Li and Sn atoms, which is governed by the total number of valence electrons. The discussion of experimental results is also supported by DFT electronic structure calculations.

Osman, Hussien H.↗
DOE OSTI2025

Trans-Influence in Dinuclear Pt(III) Complexes: Electronic Structure, σ-Donation, and Pt–Pt Spin–Spin Coupling

This study investigates the trans influence in dinuclear platinum(III) complexes using a combined approach of ab initio molecular dynamics and natural localized molecular orbital (NLMO) analysis. Focusing on pivalamidate-bridged Pt III complexes with axial ligands of varying σ-donation strength, it is quantified how ligand−metal interactions propagate through the Pt−Pt bond, and how they affect bond polarization, axial water coordination, and 1 J PtPt spin−spin coupling constants. NLMO analysis reveals quantitatively that strong σ-donating ligands polarize the Pt−Pt bond, shifting the electron density toward the opposite platinum center. The polarization mechanism is identified as the primary reason for the observed reduction of 1 J PtPt , because the bond polarization diminishes the transmission of the nuclear magnetic spin-induced electron spin density through the Pt−Pt bond. Additionally, the destabilization of axial water coordination at the opposite Pt site can be rationalized through a polarizationinduced Pt IV − Pt II -like mixed-valence character.

Ab initio molecular dynamics↗
DOE OSTI2022

Exploiting dissipative reactions to perform in-beam γ-ray spectroscopy of the neutron-deficient isotopes 38,39 Ca

The neutron-deficient Ca isotopes continue to attract attention due to their importance for testing isospin symmetry and their relevance in capture reactions of interest for nova nucleosynthesis and the shape of light curves in Type I x-ray bursts. To date, spectroscopic information on 38,39 Ca is largely limited to data on lower-spin excited states. Here, we report in-beam γ-ray spectroscopy of complementary higher-spin, complex-structure states in 39 Ca populated in fast-beam-induced, momentum-dissipative processes leading to neutron pickup onto excited configurations of the projectile, 9 Be( 38 Ca*, 39 Ca + γ)X. Such a dissipative reaction was recently characterized for the case of inelastic scattering of 38 Ca off 9 Be, 9 Be( 38 Ca, 38 Ca + γ)X. Additional data and discussion on the nuclear structure of 38 Ca is also presented. Furthermore, an explanation for the more-complex-structure states, populated with small cross sections in one-nucleon knockout reactions, and observed in the tails of their longitudinal momentum distributions, is also offered.

20 ≤ A ≤ 38↗
DOE OSTI2024

Stable vacua with realistic phenomenology and cosmology in heterotic M-theory satisfying Swampland conjectures

We recently described a protocol for computing the potential energy in heterotic M-theory for the dilaton, complex structure and Kähler moduli. This included the leading order non-perturbative contributions to the complex structure, gaugino condensation and worldsheet instantons assuming a hidden sector that contains an anomalous U(1) structure group embedded in E8. In this paper, we elucidate, in detail, the mathematical and computational methods required to utilize this protocol. These methods are then applied to a realistic heterotic M-theory model, the B – L MSSM, whose observable sector is consistent with all particle physics requirements. Within this context, it is shown that the dilaton and universal moduli can be completely stabilized at values compatible with every phenomenological and mathematical constraint — as well as with ΛCDM cosmology. We also show that the heterotic M-theory vacua are consistent with all well-supported Swampland conjectures based on considerations of string theory and quantum gravity, and we discuss the implications of dark energy theorems for compactified theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

High temperature transition aluminas in gamma-Al2O3: Review

High temperature treated transition aluminas display adsorptive and catalytic properties that are in many ways comparable to those of their low temperature counterpart gamma-Al2O3. While being important industrial catalysts as well as catalytic supports, their very basic crystallographic and structural characteristics remain poorly understood and thus actively studied. In this review, we critically examine the crystallography and structural complexity of these materials. Specifically, we address the crystallography of delta- and theta-Al2O3 polymorphs and show how structural intergrowth and disorder are accommodated in these phases. The structural complexity at the scale of overall microstructure is also examined, and the challenges and recent progress in quantification of the structure at ensemble level are discussed. Most pertinently to catalysis, we review the surfaces properties of high temperature treated Al2O3 and discuss the implications for understanding attributes relevant to heterogeneous catalysis.

Kovarik, Libor↗
DOE OSTI2021

Stereoselective synthesis of a 4-α-glucoside of valienamine and its X-ray structure in complex with Streptomyces coelicolor GlgE1-V279S

Glycoside hydrolases (GH) are a large family of hydrolytic enzymes found in all domains of life. As such, they control a plethora of normal and pathogenic biological functions. Thus, understanding selective inhibition of GH enzymes at the atomic level can lead to the identification of new classes of therapeutics. In these studies, we identified a 4-α-glucoside of valienamine (8) as an inhibitor of Streptomyces coelicolor (Sco) GlgE1-V279S which belongs to the GH13 Carbohydrate Active EnZyme family. The results obtained from the dose–response experiments show that 8 at a concentration of 1000 µM reduced the enzyme activity of Sco GlgE1-V279S by 65%. The synthetic route to 8 and a closely related 4-α-glucoside of validamine (7) was achieved starting from readily available D-maltose. A key step in the synthesis was a chelation-controlled addition of vinylmagnesium bromide to a maltose-derived enone intermediate. X-ray structures of both 7 and 8 in complex with Sco GlgE1-V279S were solved to resolutions of 1.75 and 1.83 Å, respectively. Structural analysis revealed the valienamine derivative 8 binds the enzyme in an E 2 conformation for the cyclohexene fragment. Also, the cyclohexene fragment shows a new hydrogen-bonding contact from the pseudo-diaxial C(3)–OH to the catalytic nucleophile Asp 394 at the enzyme active site. Asp 394, in fact, forms a bidentate interaction with both the C(3)–OH and C(7)-OH of the inhibitor. In contrast, compound 7 disrupts the catalytic sidechain interaction network of Sco GlgE1-V279S via steric interactions resulting in a conformation change in Asp 394. These findings will have implications for the design other aminocarbasugar-based GH13-inhibitors and will be useful for identifying more potent and selective inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗
DOE OSTI2023

Technical Lignin Fractionation: A Powerful Tool for Lignin Structure Homogenization and Its Application

Extracted lignin as a by-product of pulping and bio-refining processes is the main available bio-phenolic polymer. The structural complexity, polydispersity, and black color of lignin are the main limiting factors for its application. Preparation of lignin with lower structural complexity and polydispersity through lignin fractionation is one of the primary solutions to engineer lignin into a value-added material. Sequential lignin fractionation was developed based on pH reduction from alkaline to acidic using mineral acids and was recently optimized using carbon dioxide as a pH controller. The partial solubility of lignin in organic solvents is another promising method for lignin fractionation. Organic solvents with different polarity and solubility factors are able to fractionate lignin, yielding a more homogeneous chemical structure. As a modification of the lignin fractionation process, the use of solvents, water/organic solvent mixtures, such as alcohols, and acetic acid from room to high temperature has been proposed as a greener method for lignin fractionation. Using membrane technology is another promising method and current results indicate its good potential for lignin recovery and fractionation.

Sadeghifar, Hasan↗
DOE OSTI2021

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗
DOE OSTI2022

Predicting Oxygen Off-Stoichiometry and Hydrogen Incorporation in Complex Perovskite Oxides

Chemically and structurally complex solid compounds, including those with significant off-stoichiometry, are rapidly extending new material functionality across a variety of applications. Accelerated development of these compounds requires accurate predictions of material defect properties including effective defect formation energies and equilibrium defect concentrations. Traditional first-principles approaches typically examine dilute defect concentrations and relatively ordered atomic structures to identify the lowest energy defect sites. These approaches are rarely suitable for describing the disorder present in these systems and its influence on defect formation, which can lead to unphysically large predictions for defect concentrations. Here, we demonstrate a new method to accurately predict the temperature and pressure dependence of oxygen vacancy concentrations and proton interstitial concentrations in complex oxides. This method extends standard dilute defect calculations to incorporate atomic and magnetic disorder, employs the ensemble descriptions of defect sites resulting in improved predictions of defect formation energies, and accounts for effects beyond the dilute defect limit. To demonstrate our method, we show that the predicted defect concentrations in perovskites used as ceramic fuel cell cathodes, including Ba0.5Sr0.5Fe0.8Zn0.2O3-d, Ba0.5Sr0.5Co0.8Fe0.2O3-d, and BaCo1-x-y-zFexZryYzO3-d, are in good agreement with experimental values, thereby opening the door for predictive design of complex oxides by these applications.

DFT↗
DOE OSTI2025

Protein-ligand binding affinity prediction using multi-instance learning with docking structures

Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. Nevertheless, co-crystal complex structures are not readily available and the inaccurate predicted structures from molecular docking can degrade the accuracy of the machine learning methods. We introduce a novel structure-based inference method utilizing multiple molecular docking poses for each complex entity. Our proposed method employs multi-instance learning with an attention network to predict binding affinity from a collection of docking poses. We validate our method using multiple datasets, including PDBbind and compounds targeting the main protease of SARS-CoV-2. The results demonstrate that our method leveraging docking poses is competitive with other state-of-the-art inference models that depend on co-crystal structures. This method offers binding affinity prediction without requiring co-crystal structures, thereby increasing its applicability to protein targets lacking such data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Lightweight, strong, moldable wood via cell wall engineering as a sustainable structural material

Turning wood into honeycombs Wood is an attractive material for structural applications, but it usually works best as boards or sheets. Xiao et al . have developed a process for engineering hardwood that allows these sheets to be manipulated into complex structures (see the Perspective by Tajvidi and Gardner). The key is to manipulate the cell wall structure by shrinking and blasting open the fibers and vessels by drying and “water-shocking” them. This process creates a window wherein the wood can be manipulated without ripping or tearing. Honeycomb, corrugated, or other complex structures are locked in once the wood dries. —BG

Science & Technology - Other Topics↗
DOE OSTI2022

Disk Evolution Study through Imaging of Nearby Young Stars (DESTINYS): A Panchromatic View of DO Tau’s Complex Kilo-astronomical-unit Environment

While protoplanetary disks are often treated as isolated systems in planet formation models, observations increasingly suggest that vigorous interactions between Class II disks and their environments are not rare. DO Tau is a T Tauri star that has previously been hypothesized to have undergone a close encounter with the HV Tau system. As part of the DESTINYS ESO Large Programme, we present new Very Large Telescope (VLT)/SPHERE polarimetric observations of DO Tau and combine them with archival Hubble Space Telescope (HST) scattered-light images and Atacama Large Millimeter/submillimeter Array (ALMA) observations of CO isotopologues and CS to map a network of complex structures. The SPHERE and ALMA observations show that the circumstellar disk is connected to arms extending out to several hundred astronomical units. HST and ALMA also reveal stream-like structures northeast of DO Tau, some of which are at least several thousand astronomical units long. These streams appear not to be gravitationally bound to DO Tau, and comparisons with previous Herschel far-IR observations suggest that the streams are part of a bridge-like structure connecting DO Tau and HV Tau. We also detect a fainter redshifted counterpart to a previously known blueshifted CO outflow. While some of DO Tau's complex structures could be attributed to a recent disk–disk encounter, they might be explained alternatively by interactions with remnant material from the star formation process. These panchromatic observations of DO Tau highlight the need to contextualize the evolution of Class II disks by examining processes occurring over a wide range of size scales.

79 ASTRONOMY AND ASTROPHYSICS↗