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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Performance Prediction of High‐Entropy Perovskites La 0.8 Sr 0.2 Mn x Co y Fe z O 3 with Automated High‐Throughput Characterization of Combinatorial Libraries and Machine Learning

Perovskite oxides form a large family of materials with applications across various fields, owing to their structural and chemical flexibility. Efficient exploration of this extensive compositional space is now achievable through automated high-throughput experimentation combined with machine learning. In this study, we investigate the composition–structure–performance relationships of high-entropy La 0.8 Sr 0.2 Mn x Co y Fe z O 3±𝞭 perovskite oxides (0 < x, y, z <1; x+y+z≈1) for application as oxygen electrodes in Solid Oxide Cells. Following the deposition of a continuous compositional map using thin-film combinatorial pulsed laser deposition, compositional, structural, and performance properties are characterized using six different techniques with mapping capabilities. Random forests effectively model electrochemical performance, consistently identifying Fe-rich oxides as optimal compounds with the lowest area-specific resistance values for oxygen electrodes at 700 °C. Additionally, the models identify a statistical correlation between oxygen sublattice distortion—derived from spectral analysis of Raman-active modes—and enhanced performance.

high entropy oxides↗
DOE OSTI2022

High-Throughput Ion Irradiation and Microstructural Characterization of Multi-Principal-Element Alloys

Multi-principal-element alloys (MPEAs) have garnered interest in the nuclear community for their apparent resistance to microstructural damage under irradiation. While both experimentation and simulation have demonstrated reduced hardening and void swelling in MPEAs, the relationship between composition and irradiation response is still poorly understood since a rich experimental database for MPEAs does not yet exist. In this work, to accelerate the generation of experimental irradiation-response data for MPEAs, high-throughput synthesis, irradiation, and characterization techniques have been employed. Specifically, additive manufacturing has been used to produce arrays of various MPEAs (1-cm2 coupons), which have been subsequently irradiated using 4-MeV Ni2+ ions to a peak damage of 200 dpa at 500 °C. Hardening and void swelling have been assessed using nanoindentation and trenching via plasma focused ion beam (PFIB), respectively. Trends in the experimental data relating hardening and void swelling behavior to composition have been analyzed using different machine learning approaches.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

High-Throughput Strategies that Encompass Experiments and Machine Learning to Predict the Mechanical Properties of Additive Manufactured Aerospace Alloys

Small Punch Test (SPT) uses a thin disk of material to predict mechanical properties. While SPT has existed for decades, it has been used largely as a qualitative evaluator of mechanical properties. Recent advances in computational modeling have enabled the extraction of uniaxial stress-strain response from the measured SPT load-displacement data. Due to small sample volumes and unidirectional testing, SPT is conducive to high-throughput automation and ideally suited to extract properties from high-cost materials. Aerospace alloys have been of recent interest to the Additive Manufacturing (AM) community due to AM’s unique ability to fabricate complex designs not possible, or extremely arduous, with conventional manufacturing. In this research, SPT, coupled with Materials Informatics and computational modeling, is used to develop relevant Process-Structure-Property relationships to decrease the cost and time of process optimization for AM aerospace alloys, namely Inconel 718, Inconel 625, and Niobium C103.

High-throughput Testing↗
DOE OSTI2020

Laser metal deposition of refractory high-entropy alloys for high-throughput synthesis and structure-property characterization

Progress in materials development is often paced by the time required to produce and evaluate a large number of alloys with different chemical compositions. This applies especially to refractory high-entropy alloys (RHEAs), which are difficult to synthesize and process by conventional methods. To evaluate a possible way to accelerate the process, high-throughput laser metal deposition was used in this work to prepare a quinary RHEA, TiZrNbHfTa, as well as its quaternary and ternary subsystems by in-situ alloying of elemental powders. Compositionally graded variants of the quinary RHEA were also analyzed. Our results show that the influence of various parameters such as powder shape and purity, alloy composition, and especially the solidification range, on the processability, microstructure, porosity, and mechanical properties can be investigated rapidly. The strength of these alloys was mainly affected by the oxygen and nitrogen contents of the starting powders, while substitutional solid solution strengthening played a minor role.

additive manufacturing↗
DOE OSTI2023

High-throughput mass spectrometry analysis using immediate drop-on-demand technology coupled with an open port sampling interface

Rationale: The sampling throughput of immediate drop-on-demand technology (I.DOT) coupled with an open port sampling interface (OPSI) is limited by software communication. To enable much-needed high-throughput mass spectrometry (MS) analysis capabilities, a novel software was developed that allows for flexible sample selection from a 96-well plate and for maximized analysis throughput using I.DOT/OPSI-MS coupling. Methods: Wells of a 96-well I.DOT plate were filled with propranolol solution and were used to test maximum sampling throughput strategies to minimize analysis time. Demonstration of chemical reaction monitoring was done using acid-catalyzed ring closure of 2,3-diaminonaphthalene (DAN) with nitrite to form 2,3-naphthotriazole (NAT). Analytes were detected in positive electrospray ionization mode using selected reaction monitoring. Results: A maximum throughput of 1.54 s/sample (7.41 min/96-well plate with three technical replicates) was achieved, and it was limited by the peak width of the MS signal resulting in an occasional slight overlap between the peaks. Further, relative standard deviation was 10 ± 1% with all tested sampling strategies. Chemical reaction monitoring of DAN to NAT using nitrite was successfully accomplished with 2 s/sample throughout showing almost complete transformation in 10 min with no signal overlap. Conclusions: This work illustrates the development of a noncontact, automated I.DOT/OPSI-MS system with improved throughput achieved through an optimized software interface. Its achievable analysis time and precision make it a viable approach for drug discovery and in situ reaction monitoring studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Development and evaluation of an agar capture system (ACS) for high-throughput screening of insoluble particulate substrates with bacterial growth and enzyme activity assays

In this work, we describe a method for containing insoluble particulates for use as substrates in either bacterial growth or enzyme assays. This method was designed for high-throughput screening of environmental or engineered bacteria. Benchmarking this method with several model bacteria uncovered phenotypes not observable with the particulate substrates alone.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Accelerated creep profiling: a high-throughput thermal- and stress-gradient approach applied to additive and wrought stainless steel

Here, this study investigates logarithmic creep behavior at temperatures near room temperature in wrought and additively manufactured (AM) 316 L austenitic stainless steel. A novel high-throughput (HiTp) methodology employed thermal gradients to obtain stress- and temperature-dependence of creep behavior. The findings, based on 104 two-week creep tests, reveal significant differences in creep response between wrought and AM materials. Compared to the wrought material, the AM material exhibited a higher activation energy and a lower activation volume. These differences were attributed to the materials’ distinct microstructural features, e.g., dislocation cell structures and precipitate distributions, which alter the susceptibility to dislocation glide creep, particularly at stresses below the yield stress. The HiTp methodology provides both an accelerated determination of low-temperature creep mechanisms, offering critical data for the design and optimization of alloys in near-ambient, high stress applications.

316 L Stainless steel↗
DOE OSTI2022

Revisit the VEC criterion in high entropy alloys (HEAs) with high-throughput ab initio calculations: A case study with Al-Co-Cr-Fe-Ni system

Valence electron concentration (VEC) was treated as a useful parameter to predict the stability of solid solution phases. However, the available experimental data to support this criterion is far from enough. In the current study, the high-throughput ab initio modeling is applied to investigate the relative stability of FCC and BCC single crystals of the Al-Co-Cr-Fe-Ni high entropy alloys (HEAs) by using the special quasi-random structure (SQS) approach. Furthermore, the predictions start with pure elements of the Al-Co-Cr-Fe-Ni system and are continued with binaries, ternaries, and quaternary compositions, which come up with 180 compositions (360 structures). After that, the reliability of the VEC criterion is testified. The results show that the VEC criterion not only works for the stable structure but also works effectively for metastable structure when both FCC and BCC are not thermodynamic stable. However, it is found that the old VEC criterion proposed by Guo et al. fails to work effectively for compositions containing high concentrations of light-weight metals such as Al at VEC<5. To solve this problem, the present work proposes a new VEC rule to define the stability of FCC and BCC structures at the ground state. With the implementation of the new VEC rule, the effectiveness of the VEC rule (EVEC) of both FCC and BCC structures is enhanced, especially for pure elements and binary compositions, indicating that this rule does not only work effectively for multicomponent systems but also works for low-order systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-throughput search for magnetic topological materials using spin-orbit spillage, machine learning, and experiments

Magnetic topological insulators and semi-metals have a variety of properties that make them attractive for applications including spintronics and quantum computation. Here, we use systematic high-throughput density functional theory calculations to identify magnetic topological materials from the ≈ 40000 three-dimensional materials in the JARVIS-DFT database. First, we screen materials with net magnetic moment > 0.5 μB and spin-orbit spillage > 0.25, resulting in 25 insulating and 564 metallic candidates. The spillage acts as a signature of spin-orbit induced band-inversion. Then, we carry out calculations of Wannier charge centers, Chern numbers, anomalous Hall conductivities, surface bandstructures, and Fermi-surfaces to determine interesting topological characteristics of the screened compounds. We also train machine learning models for predicting the spillage, bandgaps, and magnetic moments of new compounds, to further accelerate the screening process. We experimentally synthesize and characterize a few candidate materials to support our theoretical predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

High-Throughput Screening of Strong Electron–Phonon Couplings in Ternary Metal Diborides

Here, we perform a high-throughput screening on phonon-mediated superconductivity in a ternary metal diboride structure with alkali, alkaline earth, and transition metals. We find 17 ground states and 78 low-energy metastable phases. From fast calculations of zone-center electron–phonon coupling, 43 compounds are revealed to show electron–phonon coupling strength higher than that of MgB 2 . An anticorrelation between the energetic stability and electron–phonon coupling strength is identified. We suggest two phases, i.e., Li 3 ZrB 8 and Ca 3 YB 8 , to be synthesized, which show reasonable energetic stability and superconducting critical temperature.

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

Enhancing 2‐Pyrone Synthase Efficiency by High‐Throughput Mass‐Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation

Abstract Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass‐spectrometry based high‐throughput quantitative method to screen new mutants of 2‐pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli . From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest k cat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis‐Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in‐cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.

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

Discovery of Stable Surfaces with Extreme Work Functions by High‐Throughput Density Functional Theory and Machine Learning

Abstract The work function is the key surface property that determines the energy required to extract an electron from the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. This work presents a high‐throughput workflow using density functional theory (DFT) to calculate the work function and cleavage energy of 33,631 slabs (58,332 work functions) that are created from 3,716 bulk materials. The number of calculated surface properties surpasses the previously largest database by a factor of ≈27. Several surfaces with an ultra‐low (<2 eV) and ultra‐high (>7 eV) work function are identified. Specifically, the (100)‐Ba‐O surface of BaMoO 3 and the (001)‐F surface of Ag 2 F have record‐low (1.25 eV) and record‐high (9.06 eV) steady‐state work functions. Based on this database a physics‐based approach to featurize surfaces is utilized to predict the work function. The random forest model achieves a test mean absolute error (MAE) of 0.09 eV, comparable to the accuracy of DFT. This surrogate model enables rapid predictions of the work function (≈ 10 5 faster than DFT) across a vast chemical space and facilitates the discovery of material surfaces with extreme work functions for energy conversion and electronic device applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cryptate binding energies towards high throughput chelator design: metadynamics ensembles with cluster–continuum solvation

A tiered forcefield/semiempirical/meta-GGA pipeline together with a thermodynamic scheme designed with error cancellation in mind was developed to calculate binding energies of [2.2.2] cryptate complexes of mono- and divalent cations. Stable complexes of Na, K, Rb, Ca, Zn and Pb were generated, revealing consistent cation–N lengths but highly variable cation–O lengths and an amine stacking mechanism potentially augmenting the cation size selectivity. Metadynamics, used for searching the high-dimensional potential energy surface, together with a cluster–continuum model for affordable – yet accurate – solvation modeling, enabled the discovery of more stable geometries than those previously reported. Similar solvation energy curve shapes for lone vs. coordinated ions enabled rapid solvation convergence via the cancellation of errors stemming from finite cluster sizes. In conclusion, an R 2 of 0.850 vs. experimental aqueous binding energies was obtained, validating this scheme as the backbone of a high-throughput workflow for chelator design.

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

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗
DOE OSTI2023

Tuning and high throughput experimental screening of eutectic electrolytes with co-solvents for redox flow batteries

Eutectic solvents, with high salt concentrations and suppressed volatility, are promising alternatives to aqueous and volatile organic electrolytes for grid-scale energy storage devices such as redox flow batteries (RFBs). However, it is not known a priori which hydrogen bond acceptors and donors would form a eutectic solvent and at which compositions of these mixtures would yield desirable properties for RFBs. Specifically, the known deep eutectic solvents generally have high viscosities and low ionic conductivities, especially in the landscape of RFB electrolytes. We report a high throughput experimental (HTE) study was carried out to assess the properties of eutectic solvents based on choline chloride as the hydrogen bond acceptor and ethylene glycol and aniline as the hydrogen bond donors. In addition, water, acetonitrile, and dimethyl sulfoxide as co-solvents were examined in terms of tuning the viscosity, conductivity, and solubility of two redox-active species: methyl viologen dichloride hydrate (MVCl 2 ·H 2 O, or MV for simplicity) and 2,1,3-benzothiadiazole (BTZ) that are relevant to RFBs. The HTE framework enabled the development of a rapid and comprehensive understanding of the design of new eutectic electrolytes incorporating co-solvents to improve the physicochemical and electrochemical properties for RFBs.

25 ENERGY STORAGE↗