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Results for “crystal structure optimization”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Growth of zinc selenide single crystals by physical vapor transport in microgravity

The goals of this research were the optimization of growth parameters for large (20 mm diameter and length) zinc selenide single crystals with low structural defect density, and the development of a 3-D numerical model for the transport rates to be expected in physical vapor transport under a given set of thermal and geometrical boundary conditions, in order to provide guidance for an advantageous conduct of the growth experiments. In the crystal growth studies, it was decided to exclusively apply the Effusive Ampoule PVT technique (EAPVT) to the growth of ZnSe. In this technique, the accumulation of transport-limiting gaseous components at the growing crystal is suppressed by continuous effusion to vacuum of part of the vapor contents. This is achieved through calibrated leaks in one of the ground joints of the ampoule. Regarding the PVT transport rates, a 3-D spectral code was modified. After introduction of the proper boundary conditions and subroutines for the composition-dependent transport properties, the code reproduced the experimentally determined transport rates for the two cases with strongest convective flux contributions to within the experimental and numerical error.

Rosenberger, Franz↗
DOE OSTI2024

Effective optimization of atomic decoration in giant and superstructurally ordered crystals with machine learning

Crystals with complicated geometry are often observed with mixed chemical occupancy among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar systems possessing exact occupancy on all the sites can exhibit superstructural ordering, dramatically inflating the unit cell size. In this work, a crystal graph convolutional neural network (CGCNN) is used to predict optimal atomic decorations on fixed crystalline geometries. This is achieved with a site permutation search (SPS) optimization algorithm based on Monte Carlo moves combined with simulated annealing and basin-hopping techniques. Our approach relies on the evidence that, for a given chemical composition, a CGCNN estimates the correct energetic ordering of different atomic decorations, as predicted by electronic structure calculations. This provides a suitable energy landscape that can be optimized according to site occupation, allowing the prediction of chemical decoration in crystals exhibiting mixed or disordered occupancy, or superstructural ordering. Verification of the procedure is carried out on several known compounds, including the superstructurally ordered clathrate compound Rb8Ga27Sb16 and vacancy-ordered perovskite Cs2SnI6, neither of which was previously seen during the neural network training. In addition, the critical temperature of an order–disorder phase transition in solid solution CuZn is probed with our SPS routines by sampling site configuration trajectories in the canonical ensemble. This strategy provides an accurate method for determining favorable decoration in complex crystals and analyzing site occupation at unprecedented speed and scale.

Chemistry↗
DOE OSTI2025

Enhanced domain dynamics in alternating current poled rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 single crystals

Abstract The understanding of domain dynamics in ferroelectric materials is crucial for optimizing their performance in piezoelectric and electro‐optic applications. Although previous studies have focused on static domain structures and macroscopic characteristics, the time‐resolved approach of domains remains largely unexplored. In this study, we compare the dynamic responses of direct current (DC) and alternating current (AC) poled [001]‐oriented rhombohedral Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 (PMN–PT) single crystals using X‐ray photon correlation spectroscopy (XPCS) during the application of external electric fields. Our results demonstrate that the AC‐poled sample exhibit enhanced reconfiguration of domain variants in response to driving fields compared to the DC‐poled counterpart, as evidenced by accelerated correlation decay and faster relaxation time. This phenomenon is attributed to enhanced reversible domain wall motion achieved through AC poling, which facilitates field‐induced domain realignment. These findings provide insight into the relationship between dynamics and macroscopic properties in relaxor‐PT single crystals for high‐performance applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) of zwitterionic organic HCl salts

In this work, we benchmark quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) for determining the crystal structures of two zwitterionic organic HCl salts, L-ornithine HCl ( Orn ) and L-histidine HCl·H 2 O ( Hist ). These salts present an interesting challenge for QNMRX-CSP, as gas-phase geometry optimizations used to generate starting structures for the organic zwitterionic fragments fail to capture their correct solid-state geometries. To overcome this limitation, geometry optimizations using the COSMO water-solvation model are employed to generate initial structural models. Using this approach, QNMRX-CSP yields structural models of the two zwitterionic organic HCl salts that closely match experimentally determined crystal structures. In addition, the application of QNMRX-CSP to Hist represents a further step toward the de novo structural determination of solvated organic HCl salts, as Hist is the first benchmark system of this type to include a water molecule as a component of its crystal structure. This work is significant for its potential application to the structural determination of active pharmaceutical ingredients, which often feature complex organic components and solvated solid forms.

Fleischer, Carl H. [Florida State Univ., Tallahass↗
DOE OSTI2025

Two-step spin-coating of vacancy-ordered double perovskites enables growth of thin films for electronic devices

Vacancy-ordered double perovskites (VODPs), such as Cs 2 TeX 6 (X = Cl, Br, I), are lead-free alternatives to conventional metal-halide perovskites (MHPs). One limitation of VODPs is the lack of processes to form thin films relevant for physical characterization and electronic devices. A two-step spin-coating method was developed for synthesizing high-quality films of Cs 2 TeBr 6 . Independently depositing CsBr and TeBr 4 enables high precursor concentrations and control over crystallization kinetics. By optimizing the spin-coating parameters, conversion of precursors to phase pure films was observed using structural and surface characterization methods. The growth of mixed-halide systems was investigated using alternative salts including CsCl and CsI. The formation of halide alloys was found to depend on the existence of routes to byproducts. Lastly, single carrier diodes of Cs2TeBr6 were designed following valence band characterization with photoelectron spectroscopy. Temperature-dependent space-charge-limited current measurements revealed that transport occurs by hopping and the hole mobility is 3.2 × 10 −5 cm 2 V −1 s −1 near room temperature. As a result, the insights from the 2-step procedure provide a pathway towards making semiconducting devices from VODPs.

Kuklinski, Owen [University of California, Santa B↗
DOE OSTI2026

Coarse-Grained Simulations of Polyrotaxane Hydrogels under Quiescent and Shear Conditions

Cyclodextrin-based polyrotaxanes (PR) form hydrogels in water through cyclodextrin (CD) aggregation and crystallization. These networks can break under shear flows, making them versatile platforms for extrusion-based 3D printing. To optimize the material properties of 3D-printed PR gels, a microscopic understanding of the structural evolution during 3D printing is necessary. Here, we employ coarse-grained (CG) simulations to reveal the PR assembly process at the molecular level. Our simulations reproduce the experimental crystal morphologies of PR at varying concentrations and chain lengths under quiescent conditions. Using nonequilibrium simulations, we show shear flow ruptures crystalline domain connectivity in PR gels and stacks the lamellae in the gradient direction, allowing the materials to flow during 3D printing. After the cessation of flow, the anisotropic crystal alignment and absence of available dangling PR diminish the intercrystal connectivity. The printed materials are therefore mechanically weaker than the pristine hydrogels, in agreement with experimental results. Nonetheless, by relating the microscopic structural evolution with viscoelastic properties of PR gels and solutions, we elucidate how flow conditions and sample composition affect the 3D printing performance of PR hydrogels.

Smith, Cameron D. [Dartmouth College, Hanover, NH ↗
DOE OSTI2026

AI-assisted rapid crystal structure generation towards a target local environment

In material design, traditional crystal structure prediction approaches are expensive as they require extensive structural sampling through expensive energy minimization methods. Emerging artificial intelligence (AI) generative models have shown great promise in rapidly generating realistic crystals, but they typically handle only a few tens of atoms per unit cell. To overcome this limitation, we introduce a symmetry-informed approach, the Local Environment Geometry-Oriented Crystal Generator (LEGO-xtal). Our method generates initial structures using AI models trained on an augmented dataset, and then optimizes them using structure descriptors rather than energy-based optimization. We demonstrate its effectiveness by expanding from 25 known low-energy sp2 carbon allotropes to over 1700, all within 0.5 eV/atom of the ground-state energy of graphite. This framework offers a generalizable strategy for the targeted design of materials with modular building blocks, such as metal-organic frameworks and battery materials.

Ridwan, Osman Goni [University of North Carolina a↗
DOE OSTI2024

Tuning Catalytically Active Single Sites in Nonstoichiometric, Mixed Metal Oxides for Oxygen Electrocatalysis (Final Technical Report)

The objective of the proposed work is to employ controlled synthesis, advanced characterization, detailed electrochemical testing and theoretical calculations to develop a framework that would guide the design of robust, non-stoichiometric mixed metal oxides for oxygen electrocatalysis. In this research plan, we focus around the idea of tuning the metal ion composition and environment to create single atom centers with the utmost electrocatalytic activity. We hypothesized that tuning the cationic sites in nonstoichiometric mixed metal oxides will lead to single 4d/5d metal surface sites with optimal catalytic activity for low temperature oxygen reduction (ORR) and oxygen evolution (OER) at solid/liquid interfaces. We will focus on different crystal structures of these oxides including Ruddlesden-Popper (R-P) oxides, simple perovskites and pyrochlores due to their flexibility in accommodating different metal cation dopants, and the fact that they represent variations in the cationic arrangements in non-stoichiometric mixed metal oxide structures, which will lead to an understanding of how bulk crystal structure effects catalytic activity and stability of these systems.

08 HYDROGEN↗
DOE OSTI2024

Understanding interfacial crystallization dynamics on carbon fiber reinforced polypropylene composite manufacturing

Reinforcing polymers with discontinuous fibers improves mechanical properties, such as strength and stiffness, and in some cases achieve isotropic properties, rendering them suitable for various engineering applications. Matrix materials are generally highly engineered thermosets (e.g. crosslinked epoxies), bonded to the fiber periphery by proprietary surface and sizing chemistries. Semicrystalline thermoplastic matrices are less utilized due to poor fiber-matrix bonding resulting in inefficient interfacial load-transfer in reinforced composites. However, flexibility with melt-processing or molding conditions can be leveraged to promote non-covalent interfacial bonding between matrix and fiber via crystallization of the matrix onto fiber surface. In the present study, we utilize a co-mingle chopped carbon and isotactic polypropylene fibers to form isotropic composites, tailoring interfacial immobilized matrix or interphase morphology to optimize performance through precise control of thermal processing/molding windows. Calorimetry and optical microscopy were employed to investigate the impact of carbon fiber at various volume fractions (10, 20, and 30 %) on isotactic polypropylene crystallization and mechanical performance. Variations in mechanical properties correspond to the structural evolution of the interfacial region and are correlated to underlying microstructural attributes using wide-angle X-ray scattering, thermal analysis, and low-field nuclear magnetic resonance spectroscopy. These results provide a practical framework for the manufacturing of thermoplastic matrix composites. In conclusion, the results presented provide a guide for the strategic optimization of interphase design, showcasing tailorable tensile strengths which outperform any isotactic polypropylene carbon fiber composites previously reported in literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Preparing for successful protein crystallization experiments

Crystal-based structural methods, including X-ray crystallography, are frequently utilized for the determination of high-resolution structures of biomolecules. All crystal-based diffraction methods first require the preparation of biomolecular crystals, and careful sample preparation for crystallization experiments can increase the frequency of success. In this article, strategies to optimize factors that can impact crystallization are presented, from which buffers and reducing agents are most favorable to which crystallization techniques could be used.

36 MATERIALS SCIENCE↗
NASA NTRS1982

A study of fiber materials for use in temperature resistant fiber reinforced composites

This study has been directed at characterizing the micro-properties of candidate ceramics and glasses for use in making fibers used in fiber reinforced material composites. Particular emphasis has been given into developing techniques to guide the optimization of fiber properties. The Scanning Electron Microscope (SEM) and X-ray Diffractometer (XRD) have been used to help collate the method of synthesis, crystal structure and surface morphology with physical performance parameters. As a result, progress has been made in characterizing such materials. This increased understanding makes the previous research worthy of further study.

Bachowsky, M. J.↗
DOE OSTI2026

Viral Nuclease Inhibitors: Small molecule disruptors of the UL12 alkaline nuclease display broad anti-herpes virus activity

Herpes simplex virus 1 (HSV-1) UL12 encodes a highly conserved 5′ → 3′ alkaline exonuclease that is essential for the production of infectious virus. Together with the viral single-stranded DNA-binding/annealing protein ICP8, UL12 functions as a two-component recombinase that mediates recombination-dependent viral DNA replication. Here, we present the crystal structure of the catalytic domain of the HSV alkaline nuclease (UL12), which provides the first view of an α-herpesvirus alkaline nuclease. Using this structure, we optimized a series of small-molecule viral nuclease inhibitors (VNIs) that target the UL12 active site and potently inhibit UL12 exonuclease activity in vitro. We have thus established a robust platform for structure-based docking, SAR analysis and rational inhibitor design. Because UL12 orthologs are conserved across all human herpesviruses, we examined the activity of these compounds against the β- and γ-herpesvirus alkaline nucleases UL98 and SOX and found that they inhibit all three enzymes. The VNIs also exhibit antiviral activity against HSV-1 and HCMV in cell culture. EC 50 and IC 50 values were in the nanomolar to low micromolar range. Together, these findings establish herpesvirus alkaline nucleases as conserved, druggable antiviral targets and provide a foundation for the development of broad-spectrum anti-herpesvirus therapeutics, either as standalone agents or in combination with existing nucleoside analogs.

Sharma, Nidhi↗
DOE OSTI2026

High-Efficiency Solar-To-Fuel Photoelectrochemistry in Disordered Photonic Glass Electrodes (Final Technical Report)

This project investigated how photonic glass (PG) photoelectrodes—disordered arrangements of dielectric scatterers—can serve as scalable, tunable platforms for light trapping in photoelectrochemical (PEC) solar-to-fuel systems. By leveraging disorder-driven optical phenomena such as multiple scattering resonances and light localization, PG structures offer an alternative to conventional photonic crystals and inverse opals that require high structural precision. The scientific goals were to twofold: (1) develop approaches to predictive models for high performance PG electrodes based on light absorption simulations, and (2) fabricate, characterize, and optimize PG-based photoelectrodes for solar-to-hydrogen and solar-to-fuel photoelectrochemical applications. To overcome the complexity of ensemble optical simulations for disordered materials, the researchers developed a machine-learning-accelerated emulation of all configurations in the design space. With this approach, PG photoelectrodes based on a TiO2 semiconductor were designed to enhance PEC currents of up to one hundred times higher than the equivalent ultra-thin film photoanodes and several times higher than the equivalent photonic crystal. The research also explored integrated systems for electrochemical hydrogen production based on replacing water oxidation with the specific glycerol oxidation electrocatalysis. Overall, the project outlined an approach to a simple-to-fabricate photoelectrode system to drive photoelectrochemical reactions relevant to solar photochemical energy conversion.

14 SOLAR ENERGY↗
DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗
NASA NTRS1999

Characterization of Human Bone Alkaline Phosphatase in Pichia Pastoris

A soluble form of human bone alkaline phosphatase has been expressed in a recombinant strain of the methylotrophic yeast Pichia pastoris. We constructed a plasmid containing cDNA encoding for human bone alkaline phosphatase, with the hydrophobic carboxyl terminal portion deleted. Alkaline phosphatase was secreted into the medium to a level of 32mg/L when cultured in shake flasks, and enzyme activity was 12U/mg, as measured by a spectrophotometric assay. By conversion to a fermentation system, a yield of 880mg/L has been achieved with an enzyme activity of 968U/mg. By gel electrophoresis analysis, it appears that greater than 50% of the total protein in the fermentation media is alkaline phosphatase. Although purification procedures are not yet completely optimized, they are expected to include filtration, ion exchange and affinity chromatography. Our presentation will focus on the purification and crystallization results up to the time of the conference. Structural data should provide additional information on the role of alkaline phosphatase in normal bone mineralization and in certain bone mineralization anomalies.

Malone, Christine C.↗
DOE OSTI2025

Synthesizing intermetallic thermoelectric materials using metal flux growth method

With zero energy poverty by 2050 goals, exploring innovative energy technologies is essential. Thermoelectric materials (TEMs) have the potential to harness waste heat and convert it to electricity (e.g., for spacecraft power, sensors, and cryogenic cooling). Two limitations of thermoelectric compounds are their low efficiency and limited pool of materials. Optimizing the efficiency of TEMs is challenging due to the interdependent relationship between electrical and thermal conductivity. A deeper understanding of electronic properties and lattice thermal conductivity is necessary to “understand, predict and ultimately control” the thermoelectric properties of TEMs. Understanding the influence of light-atom-doping and intrinsic defects on the electronic properties of the f-element containing TEMs are important questions that need to be answered to design and synthesize TEMs with optimal parameters. The purpose of this work is to understand how doping f-element based TEMs with light elements, such as carbon and boron, would impact the crystal structure, bond lengths, band gaps, and thermoelectric characteristics. High-quality f¬-element containing intermetallic single crystals are grown in metal flux media. In molten metal flux growth method, one or more low-melting metals such as aluminum, gallium, tin, and bismuth are used in excess as the reaction medium. As these are solution-state reactions, we can use lower temperatures than solid-state reactions and isolate the kinetic products instead of the thermodynamically stable compound. Then these are characterized using X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, magnetization, electrical and thermal conductivities, and thermoelectric power.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2025

Local orthorhombic phase in zirconium oxide nanocrystals: insights from X-ray pair distribution function analysis

Zirconium dioxide (ZrO 2 ) and hafnium dioxide (HfO 2 ) have emerged as promising alternatives to conventional ferroelectric materials. Understanding the crystal phases of these oxides under different conditions is crucial for optimizing their properties. There are several theories for the (anti)ferroelectric properties; however, comprehensive analysis, particularly at the local structure level, is lacking. In this study, we investigate the local structure of ZrO 2 nanocrystals using X-ray pair distribution function (PDF) analysis, revealing an unexpected local orthorhombic distortion irrespective of crystallite size. This finding suggests the potential existence of an intermediate orthorhombic phase during the microscopic switching pathway observed in previous studies. Additionally, we explore the influence of crystallite size and surface effects on the PDF. These results contribute to a deeper understanding of the structural dynamics in ZrO 2 and offer insights for the design of next-generation ferroelectric materials.

Pokratath, Rohan (ORCID:0000000268383939)↗