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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tuning Enzyme Thermostability via Computationally Guided Covalent Stapling and Structural Basis of Enhanced Stabilization

Enhancing the thermostability of enzymes without impacting their catalytic function represents an important yet challenging goal in protein engineering and biocatalysis. We recently introduced a novel method for enzyme thermostabilization that relies on the computationally guided installation of genetically encoded thioether “staples” into a protein via cysteine alkylation with the noncanonical amino acid O-2-bromoethyl tyrosine (O2beY). Here, we demonstrate the functionality of an expanded set of electrophilic amino acids featuring chloroacetamido, acrylamido, and vinylsulfonamido side-chain groups for protein stapling using this strategy. Using a myoglobin-based cyclopropanase as a model enzyme, our studies show that covalent stapling with pchloroacetamido-phenylalanine (pCaaF) provides higher stapling efficiency and enhanced stability (thermodynamic and kinetic) compared to the other stapled variants and the parent protein. Interestingly, molecular simulations of conformational flexibility of the cross-links show that the pCaaF staple allows fewer energetically feasible conformers than the other staples, and this property may be a broader indicator of stability enhancement. Using this strategy, pCaaF-stapled variants with significantly enhanced stability against thermal denaturation (ΔT m ' = +27 °C) and temperature-induced heme loss (ΔT 50 = +30 °C) were obtained while maintaining high levels of catalytic activity and stereoselectivity. Crystallographic analyses of singly and doubly stapled variants provide key insights into the structural basis for stabilization, which includes both direct interactions of the staples with protein residues and indirect interactions through adjacent residues involved in heme binding. This work expands the toolbox of protein stapling strategies available for protein stabilization.

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

Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices

This Methods/Protocols article is intended for materials scientists interested in performing machine learning-centered research. Herein, we cover broad guidelines and best practices regarding the obtaining and treatment of data, feature engineering, model training, validation, evaluation and comparison, popular repositories for materials data and benchmarking data sets, model and architecture sharing, and finally publication. In addition, we include interactive Jupyter notebooks with example Python code to demonstrate some of the concepts, workflows, and best practices discussed. Overall, the data-driven methods and machine learning workflows and considerations are presented in a simple way, allowing interested readers to more intelligently guide their machine learning research using the suggested references, best practices, and their own materials domain expertise.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning

Metal halide perovskite (MHP) derivatives, a promising class of optoelectronic materials, have been synthesized with a range of dimensionalities that govern their optoelectronic properties and determine their applications. We demonstrate a data-driven approach combining active learning and high-throughput experimentation to discover, control, and understand the formation of phases with different dimensionalities in the morpholinium (morph) lead iodide system. Using a robot-assisted workflow, we synthesized and characterized two novel MHP derivatives that have distinct optical properties: a one-dimensional (1D) morphPbI 3 phase ([C 4 H 10 NO][PbI 3 ]) and a two-dimensional (2D) (morph) 2 PbI 4 phase ([C 4 H 10 NO] 2 [PbI 4 ]). To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. Querying the ML model uncovered the reaction parameters that have the most significant effects on dimensionality control. Based on these insights, we discuss possible reaction schemes that may selectively promote the formation of morph-Pb-I phases with different dimensionalities. The data-driven approach presented here, including the use of additives to manipulate dimensionality, will be valuable for controlling the crystallization of a range of materials over large reaction-composition spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Meniscus Guided Coating and Evaporative Crystallization of UiO-66 Metal Organic Framework Thin Films

Thin-film fabrication of metal organic frameworks (MOFs) has been explored for a range of applications, including separations, catalysis, sensing, and charge transport. However, many fabrication techniques have obstacles, including slow crystallization, control over film thickness, and control over crystallinity. Recently, a meniscus-guided coating technique, called solution shearing, has been shown to create MOF thin films within minutes and with control over the film thickness. However, there have been no previous reports of solution shearing based evaporative crystallization of zirconium-based MOFs, which have been widely studied for the aforementioned applications. In this work, for the first time, we show that (i) the zirconium 1,4-dicarboxybenzene MOF, UiO-66, can be formed using evaporative crystallization during solution shearing, and (ii) a wide range of parameters can be tuned to control the film thickness, coverage, and crystallinity. Finally, we bring the solution shearing technique closer to separation applications by growing a full film of UiO-66 crystals up to the resolution of scanning electron microscopy (SEM) on anodic alumina oxide (AAO). This is the first instance of UiO-66 crystals being formed using an evaporative crystallization-based flow coating method, and solution shearing shows the promise to be applicable to form large area zirconium-based MOF crystals in a rapid manner (within seconds to minutes).

42 ENGINEERING↗
DOE OSTI2021

Theory-Guided Inelastic Neutron Scattering of Crystalline Alkaline Aluminate Salts Bearing Principal Motifs of Solution-State Species

Aluminate salts precipitated from caustic alkaline solutions exhibit a correlation between the anionic speciation and the identity of the alkali cation in the precipitate, with the aluminate ions occurring either in monomeric (Al(OH) 4 – ) or dimeric (Al 2 O(OH) 6 2– ) forms. The origin of this correlation is poorly understood as are the roles that oligomeric aluminate species play in determining the solution structure, prenucleation clusters, and precipitation pathways. Characterization of aluminate solution speciation with vibrational spectroscopy results in spectra that are difficult to interpret because the ions access a diverse and dynamic configurational space. To investigate the Al(OH) 4 – and Al 2 O(OH) 6 2– anions within a well-defined crystal lattice, inelastic neutron scattering (INS) and Raman spectroscopic data were collected and simulated by density functional theory for K 2 [Al 2 O(OH) 6 ], Rb 2 [Al 2 O(OH) 6 ], and Cs[Al(OH) 4 ]·2H 2 O. These structures capture archetypal solution aluminate species: the first two salts contain dimeric Al 2 O(OH) 6 2– anions, while the third contains the monomeric Al(OH) 4 – anion. Here, comparisons were made to the INS and Raman spectra of sodium aluminate solutions frozen in a glassy state. In contrast to solution systems, the crystal lattice of the salts results in well-defined vibrations and associated resolved bands in the INS spectra. The use of a theory-guided analysis of the INS of this solid alkaline aluminate series revealed that differences were related to the nature of the hydrogen-bonding network and showed that INS is a sensitive probe of the degree of completeness and strength of the bond network in hydrogen-bonded materials. Results suggest that the ionic size may explain cation-specific differences in crystallization pathways in alkaline aluminate salts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Activation of CO 2 by Actinide Cations (Th + , U + , Pu + , and Am + ) as Studied by Guided Ion Beam and Triple Quadrupole Mass Spectrometry

Reactions of CO 2 with Th+ have been studied using guided ion beam tandem mass spectrometry (GIBMS) and with An + (An + = Th + , U + , Pu + , and Am + ) using triple quadrupole inductively coupled plasma mass spectrometry (QQQ-ICP-MS). Additionally, the reactions ThO + + CO and ThO + + CO 2 were examined using GIBMS. Modeling the kinetic energy dependent GIBMS data allowed determination of bond dissociation energies (BDEs) for D o (Th + -O) and D o (OTh + -O) that are in reasonable agreement with previous GIBMS measurements. The QQQ-ICP-MS reactions were studied at higher pressures where multiple collisions between An + and the neutral CO 2 occur. As a consequence, both AnO + and AnO 2 + products were observed for all An + except Am + , where only AmO + was observed. Here, the relative abundances of the observed monoxides compared to the dioxides are consistent with previous reports of the AnO n + (n = 1, 2) BDEs. Comparison of the periodic trends of the group 4 transition metal, lanthanide (Ln), and actinide atomic cations in reactions with CO 2 (a formally spin-forbidden reaction for most M + ground states), and O 2 (a spin unrestricted reaction) indicate that spin conservation plays a minor role, if any, for the heavier An + metals. Further correlation of Ln + and An + + CO 2 reaction efficiencies with the promotion energy (E p ) to the first electronic state with two valence d-electrons (E p (5d 2 ) for Ln + and E p (6d 2 ) for An + ) indicates that the primary limitation in the activation of CO 2 is the energetic cost to promote from the electronic ground state of the atomic metal ion to a reactive state.

bond activation↗
DOE OSTI2022

Sequential Bond Dissociation Energies of Th + (CO) x , x = 3–6: Guided Ion Beam Collision-Induced Dissociation and Quantum Computational Studies

Collision-induced dissociation (CID) of [Th,xC,xO] + , x = 3–6, with Xe is performed using a guided ion beam tandem mass spectrometer (GIBMS). Products are formed exclusively by the loss of CO ligands. Analyses of the kinetic energy-dependent CID product cross sections yield bond dissociation energies (BDEs) of (CO) x–1 Th + –CO at 0 K as 1.09 ± 0.05, 0.82 ± 0.07, 0.63 ± 0.05, and 0.70 ± 0.05 eV, respectively. Different structures of [Th,xC,xO] + were explored using various electronic structure methods, and BDEs for CO ligand loss from precursor [Th,xC,xO] + complexes were computed. Both experimental and theoretical results corroborate that the structures of [Th,xC,xO] + , x = 3–6, formed experimentally are homoleptic thorium cation carbonyl complexes, Th + (CO) x . The nonmonotonic trend in experimental BDEs is reproduced theoretically, although ambiguities in the spin states of the x = 4–6 complexes (doublet or quartet) remain. BDEs calculated at the coupled cluster with single, double, and perturbative triple excitations (CCSD(T))/cc-pVXZ//B3LYP/cc-PVXZ (X = T and Q) level and a complete basis set (CBS) extrapolation agree reasonably well with the experimental values for all complexes. Thorium oxide ketenylidene carbonyl cations, OTh + CCO(CO) y , y = 1–4, were calculated to be the most stable structures of [Th,xC,xO] + , x = 3–6, respectively; however, these are not observed in our experiment. Potential energy profiles (PEPs) having either quartet or doublet spin calculated at the B3LYP/cc-pVQZ level suggest that the failure to observe OTh + CCO(CO) y , y = 1–4, is the result of a barrier corresponding to the C–C bond formation, making the formation of OTh + CCO(CO) y inaccessible kinetically under the present experimental conditions.

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

A Guide to Nonaqueous Electrochemistry of f-Element Complexes

Electrochemistry is a powerful tool for assessing and understanding the redox chemistry of molecular complexes. Cyclic voltammetry enables the f-element community to study molecules in unusually high or low oxidation states, which potentially pose important broad-scope questions of electronic structure. In the pursuit of boundary-pushing compounds, reactive air- and moisture-sensitive species are often encountered, which can be challenging to characterize, especially when they are chemically incompatible with certain solvents, electrolytes, or electrodes or when their potentials lie outside of common electrochemical windows. Nonaqueous solvents and pseudo reference electrodes complicate many of the standard practices in acquiring high-quality and reproducible electrochemical data. This guide presents a detailed discussion of selecting appropriate cell conditions and referencing and addresses metrics for evaluating electrochemical and chemical reversibility. These methodological approaches have been extended to best practices for the electrochemical analysis of radioactive transuranic complexes.

Electrodes↗
DOE OSTI2020

Guided Ion Beam and Quantum Chemical Investigation of the Thermochemistry of Thorium Dioxide Cations: Thermodynamic Evidence for Participation of f Orbitals in Bonding

Kinetic energy dependent reactions of ThO + with O 2 are studied using a guided ion beam tandem mass spectrometer. The formation of ThO 2 + in the reaction of ThO + with O 2 is observed to be slightly endothermic and also exhibits two obvious features in the cross section. These kinetic energy dependent cross sections were modeled to determine a 0 K bond dissociation energy of D 0 (OTh + - O) = 4.94 ± 0.06 eV. This value is slightly larger but within experimental uncertainty of less precise previously reported experimental values. The higher energy feature in the ThO 2 + cross section was also analyzed and suggests formation of an excited state of the product ion lying 3.1 ± 0.2 eV above the ground state. Additionally, the thermochemistry of ThO 2 + was explored by quantum chemical calculations, including a full Feller-Peterson-Dixon (FPD) composite approach with correlation contributions up to CCSDT(Q) and four-component spin-orbit corrections, as well as more approximate CCSD(T) calculations including semiempirical estimates of spin-orbit energy contributions. The FPD approach predicts D 0 (OTh + -O) = 4.87 ± 0.04 eV, in good agreement with the experimental value. Analogous FPD results for ThO+, ThO, and ThO 2 are also presented, including ionization energies for both ThO and ThO 2 . The ThO 2 + bond energy is larger than those of its transition metal congeners, TiO 2 + and ZrO 2 + , which can be attributed partially to an actinide contraction, but also to contributions from the participation of f orbitals on thorium that are unavailable to the transition metal systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Reactions of U + with H 2 , D 2 , and HD Studied by Guided Ion Beam Tandem Mass Spectrometry and Theory

The kinetic energy-dependent reactions of the atomic actinide uranium cation (U + ) with H 2 , D 2 , and HD were examined by guided ion beam tandem mass spectrometry. An average 0 K bond dissociation energy of D 0 (U + – H) = 2.48 ± 0.06 eV is obtained by analysis of the endothermic product ion cross sections. Quantum chemistry calculations were performed for comparison with experimental thermochemistry, including high-level CASSCF–CASPT2–RASSI calculations of the spin–orbit corrections. CCSD(T) and the CASSCF levels show excellent agreement with experiment, whereas B3LYP and PBE0 slightly overestimate and the M06 approach badly underestimates the bond energy for UH + . Theory was also used to investigate the electronic structures of the reaction intermediates and potential energy surfaces. The experimental product branching ratio for the reaction of U + with HD indicates that these reactions occur primarily via a direct reaction mechanism, despite the presence of a deep-well for UH 2 + formation according to theory. The reactivity and hydride bond energy for U + are compared with those for transition metal, lanthanide, and actinide cations, and periodic trends are discussed. Furthermore, these comparisons suggest that the 5f electrons on uranium are largely core and uninvolved in the reactive chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reactions of Atomic Thorium and Uranium Cations with SF 6 Studied by Guided Ion Beam Tandem Mass Spectrometry

The fundamental chemistry of the thorium and uranium fluorides continues to be an area of interest because of the use of thorium and uranium fluoride compounds in nuclear fuel systems. Here, we study the reaction of thorium cations with sulfur hexafluoride for the first time and revisit the reaction of uranium cations with sulfur hexafluoride. By using guided ion beam tandem mass spectrometry, we explore the reaction pathways that become accessible well above thermal energies (E ~ 0.04 eV). Overall, we find that both Th + and U + react very efficiently with SF 6 , approaching the collision limit at both thermal and elevated energies. Here, the primary products observed at low energies include Th 1–3 + , UF 1–4 + , and SF 1–4 + , all of which are formed in barrierless, exothermic processes. SF 5 + was also observed, although the pressure dependence of this channel reveals that SF 5 + forms exothermically through secondary reactions, which the energy dependences suggest result from reactions between ThF 2 + and UF 3 + with SF 6 . At higher energies, both AnF 3 + products are observed to decay to AnF + + F 2 and both SF 4 + and SF 2 + exhibit cross sections with endothermic features. For both systems, the rise in SF 4 + can be attributed to a secondary collision between AnF + with SF 6 on the basis of the pressure dependence of the SF 4 + channel at higher energies and the rise in SF 2 + appears to result from the decomposition of SF 3 + to SF 2 + + F.

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

NMR-Guided High-Temperature Electrolyte Design Using a Novel PF 5 Marker

The thermal degradation of electrolytes containing lithium hexafluorophosphate (LiPF 6 ) is a well-studied subject. However, practical application of the knowledge is difficult since the effects of the degradation process on battery performance are not well known. In this work, we propose a novel NMR experimental setup allowing direct observation of the effects of various perturbations on the electrolyte thermal degradation process, which guides the design and synthesis of new additives that improve lithium-ion battery performance at elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probing Molecular Assembly of Small Organic Molecules during Meniscus-Guided Coating Using Experimental and Molecular Dynamics Approaches

Evaporation-based thin-film coating processes are ubiquitous in fields such as organic electronics, dye coatings, and the pharmaceutical industry. Based on experimental observations of enhanced thin-film alignment during meniscus-guided coating (MGC), a molecular dynamics simulation was developed to describe the thin-film formation that occurs due to the interplay between evaporation and fluid dynamics. The process of solvent evaporation from solution is first examined, which leads to the formation of a solid thin film after evaporation is complete. Next, an MGC process was simulated by introducing a flow profile coupled with the evaporative system. In this work, we gain insights into how molecules respond and reorient in the presence of a flow profile. These results indicate that both the evaporation and the flow profile have an impact on orienting small molecules in a thin film during the MCG process. Combining experimental techniques with simulations helps enhance the understanding of the forces that are significant in directing molecular aggregation during coating processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Potent Noncovalent Inhibitors of the Main Protease of SARS-CoV-2 from Molecular Sculpting of the Drug Perampanel Guided by Free Energy Perturbation Calculations

Starting from our previous finding of 14 known drugs as inhibitors of the main protease (M pro ) of SARS-CoV-2, the virus responsible for COVID-19, we have redesigned the weak hit perampanel to yield multiple noncovalent, nonpeptidic inhibitors with ca. 20 nM IC 50 values in a kinetic assay. Free-energy perturbation (FEP) calculations for M pro -ligand complexes provided valuable guidance on beneficial modifications that rapidly delivered the potent analogues. The design efforts were confirmed and augmented by determination of high-resolution X-ray crystal structures for five analogues bound to M pro . Results of cell-based antiviral assays further demonstrated the potential of the compounds for treatment of COVID-19. In addition to the possible therapeutic significance, the work clearly demonstrates the power of computational chemistry for drug discovery, especially FEP-guided lead optimization.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Fitness Landscape-Guided Engineering of Locally Supercharged Virus-like Particles with Enhanced Cell Uptake Properties

Protein-based nanoparticles are useful models for the study of self-assembly and attractive candidates for drug delivery. Virus-like particles (VLPs) are especially promising platforms for expanding the repertoire of therapeutics that can be delivered effectively as they can deliver many copies of a molecule per particle for each delivery event. However, their use is often limited due to poor uptake of VLPs into mammalian cells. In this study, we use the fitness landscape of the bacteriophage MS2 VLP as a guide to engineer capsid variants with positively charged surface residues to enhance their uptake into mammalian cells. By combining mutations with positive fitness scores that were likely to produce assembled capsids, we identified two key double mutants with internalization efficiencies as much as 67-fold higher than that of wtMS2. Internalization of these variants with positively charged surface residues depends on interactions with cell surface sulfated proteoglycans, and yet, they are biophysically similar to wtMS2 with low cytotoxicity and an overall negative charge. Additionally, the best-performing engineered MS2 capsids can deliver a potent anticancer small-molecule therapeutic with efficacy levels similar to antibody-drug conjugates. Through this work, we were able to establish fitness landscape-based engineering as a successful method for designing VLPs with improved cell penetration. These findings suggest that VLPs with positive surface charge could be useful in improving the delivery of small-molecule- and nucleic acid-based therapeutics.

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

Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance

Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.

25 ENERGY STORAGE↗
DOE OSTI2023

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗