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NASA NTRS2002

Glennan Microsystems Initiative

During the 2001-2002 award period, we performed research on Pt/Ti/bare 6H-SiC and bare 4H-SiC interfaces in order to identify their electronic properties as a function of surface preparation. The overall aim of this work is to optimize the electronic properties of metal contacts to SiC as well as the active SiC material itself as a function of surface preparation and subsequent processing. Initially, this work has involved identifying bare surface, subsurface, and metal induced gap states at the metal-SiC contact and correlating energies and densities of deep levels with Schottky barrier heights. We used low energy electron-excited nanoluminescence (LEEN) spectroscopy, X-ray photoemission spectroscopy (XPS), and Secondary Ion Mass Spectrometry (SIMS) in order to correlate electronic states and energy bands with chemical composition, bonding, and crystal structure. A major development has been the discovery of polytype transformations that occur in 4H-SiC under standard microelectronic process conditions used to fabricate SiC devices. Our results are consistent with the stacking fault generation, defect formation, and consequent degradation of SiC recently reported for state-of-the-art ABB commercial diodes under localized electrical stress. Our results highlight the importance of -optimizing process conditions and material properties - anneal times, temperatures and doping to control such structural changes within epitaxial SiC layers. Thus far, we have established threshold times and temperatures beyond which 4H-SiC exhibits 3C-SiC transformation bands for a subset of dopant concentrations and process conditions. On the basis of this temperature time behavior, we have been able to establish an activation energy of approximately 2.5 eV for polytype transformation and dislocation motion. Work continues to establish the fundamental mechanisms underlying the polytype changes and its dependence on material parameters.

Brillson, Leonard J.↗

DOE OSTI2024

TaZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-zirconium (Ta-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Ta and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 80, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10 and between 81 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW 4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file 5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file 7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996) (4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗

DOE OSTI2025

Development and Evaluation of Embrittlement Resistant Alloys for Advanced LWR Cladding

The primary challenge preventing the deployment of reactor designs that leverage wrought FeCrAl as an advanced light-water reactor (LWR) cladding is irradiation hardening and embrittlement. Wrought FeCrAl alloys experience a loss of post-irradiation ductility and fracture toughness under low-temperature neutron irradiation (< 350°C) resulting from the combined effects of dislocation loop formation and the irradiation-enhanced precipitation of Cr-rich alpha-prime precipitates throughout the microstructure. Over the past decade, significant improvements in our understanding regarding the effect of Cr and Al content have been enabled through neutron irradiations, but even optimized wrought alloys such as C26M remain vulnerable to brittle failure during storage, transportation, and handling following irradiation. This report summarizes multiple irradiation campaigns initiated over the past 7 years and provides recent insights into the effect of (1) minor alloying composition, (2) alloy processing strategy, (3) crystal structure, and (4) the use of advanced oxide dispersion strengthened (ODS) alloys. The first irradiation campaign irradiated body-centered cubic FeCrAl alloy C26M with and without elements such as Mo and Y. It also included face-centered cubic alumina-forming austenitic (AFA) alloys that have a steeper neutronic penalty but that have far superior high-temperature strength than wrought FeCrAl. Finally, this campaign compared conventional wrought C26M with the same material produced using modern powder metallurgical hotisostatic pressing (PM-HIP). The second irradiation campaign, initiated in 2018, irradiated wrought and FeCrAl-ODS materials up to 50 dpa to assess their irradiation resistance to high-doses. The results of this work indicate that wrought C26M suffers significant degradation following neutron irradiation at LWR-relevant temperatures regardless of Mo and Y content. The PM-HIP variant appears to be more resilient to irradiation-induced ductility loss in comparison with wrought variants but still loses almost all ductility by 8 dpa. Notably, the AFAs retained at least 5% total elongation after irradiation at the same dose and temperature condition, although additional deterioration may be expected at higher fluence levels. FeCrAl-ODS materials show the greatest promise as a transformative longer-term accident-tolerant fuel (LT-ATF) cladding material. The extruded 106ZY10C alloy retained 10% total elongation after 16 dpa irradiation and retained 8% total elongation after 50 dpa. Additional challenges with FeCrAl-ODS alloys also remain, including optimization of end cap joining methodologies, enhancement of fracture toughness, scaling production to prove economic viability, and optimizing post-pilger heat treatments to maximize ductility and irradiation resistance. This series of irradiations demonstrates the efficacy of the LWR testbed available within the United States for the rapid irradiation and down-selection of LT-ATF candidates. As the country rapidly accelerates its timeline for the deployment of advanced reactor concepts, the effective utilization of the High Flux Isotope Reactor for separate-effects style irradiations should continue to be prioritized to answer the final questions pertaining to LT-ATF candidates necessary for the deployment of advanced boiling water reactors and small modular reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Sm 2 Ru 3 Sn 5 : A Noncentrosymmetric Cubic Member of the Ln 2 M 3 X 5 Family

An optimized synthetic method is presented for Sm 2 Ru 3 Sn 5 and investigate its physical properties and electronic structure. Sm 2 Ru 3 Sn 5 is prepared by arc-melting stoichiometric ratios of the elements and is confirmed by single crystal and powder X-ray diffraction. An antiferromagnetic transition is observed at T N = 3.8 K. A modified Curie-Weiss fit to the data in the range 50–150 K yields a Curie-Weiss temperature: θ CW = −36.6 K and an effective magnetic moment: μ eff = 0.83 μ B , in agreement with a Sm 3+ oxidation state. Field-dependent magnetization up to H = 7 T at 2 K shows a maximum response of 0.06 μ B , which is significantly lower than the expected Sm 3+ saturation moment (0.71 μ B ). Resistivity measurements indicate metallic behavior, and analysis of the magnetic entropy from the heat capacity reveals a doublet ground state due to crystal electric field splitting. The electronic structure and density of states are calculated with density function theory and further supported by the local density approximation with dynamical mean-field theory. Finally, the experimental and computational results highlight localized Sm 3+ moments and suggest a possible interplay between Ruddelman–Kitel–Kasuya–Yosida and Kondo interactions, positioning Sm 2 Ru 3 Sn 5 as a promising material for studying topology and complex physical phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Agentic framework for programmatic crystal structure generation using a fine-tuned worker–supervisor large language model

Platinum group metals (PGMs) underpin many catalytic technologies but face severe supply constraints, motivating the search for alternative materials and computational methods to accelerate discovery. While atomistic simulation tools such as Pymatgen and ASE have streamlined structure manipulation, they require detailed inputs, limiting accessibility for experimentalists and slowing early-stage exploration. Here, in this study, we present an AI-driven agentic framework that orchestrates worker–supervisor large language models (LLMs). The worker translates natural-language prompts of varying abstraction into valid crystallographic structures using a compact LLM fine-tuned with low-rank adaptation on a curated text–code–CIF dataset, emphasizing energy-efficient training. Benchmarking against the baseline CodeGen-350M-mono model shows that fine-tuning reduces hallucination rates from 100% to as low as 5% and improves structural match accuracy to up to 82% for fully specified inputs. Accuracy declines with decreasing prompt detail but remains nontrivial even when only stoichiometry and space group are provided, underscoring the LLM’s capacity for crystallographic inference. The supervisor Claude LLM evaluates the outputs and triggers iterative refinement through the worker’s built-in structure manipulation capabilities (e.g., supercell scaling, strain, vacancy, and substitution operations). We further demonstrate use cases for technologically relevant catalysts, including IrO 2 , pyrochlore Pb 2 Ir 2 O 7 , Ni 2 FeO 4 , and Ni 3 Mo, where the framework generates physically consistent structures that can be refined via geometry optimization. This work introduces a low-energy, language-driven pathway for integrating human and machine intelligence in materials design, paving the way for AI-assisted synthesis planning and high-throughput screening of complex oxides.

AI agent↗

DOE OSTI2025

Phase-field predictions of the influence of cooling rates during AM on the Evolution of Microstructures in Nickel-Based Single Crystal Superalloys

Additive manufacturing of single crystals made of Ni-based superalloys offers major cost savings for gas turbine engines with the inclusion of internal cooling channels. However, the lack of understanding of the effect of transient thermal conditions on solidification grain structure during additive manufacturing hinders the potential for process control to maintain the single crystal quality. The use of high-fidelity simulations through high performance computing to predict the evolution of the solidification microstructure will enhance the abilities to tailor the microstructures through process optimization. Phase field simulations are used to determine the effect local thermal conditions and defects on the stability of the solidification morphology, specifically with respect to the onset of columnar-to-equiaxed transition that results in the loss of the single crystal. The results are expected to be instrumental for developing future surrogate models to speed up the integration of design and manufacturing of turbine blades under the harsh in-service conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A New Family of Ternary Intermetallic Compounds with Dualistic Atomic Ordering – The ZIP Phases

A new family of nanostructured ternary intermetallic compounds − named the ZIP phases − is introduced in this work. The ZIP phases exhibit dualistic atomic ordering, i.e., they form two structural variants: one with the fcc diamond cubic structure (space group Fd$\bar{3}$m) and one with the hexagonal structure (space group P6 3 /mmc). They are also characterized by metallic behavior, ionic bonding, and atomic zigzagging. Powder metallurgical routes involving pressure-assisted densification are adopted to demonstrate ZIP phase synthesis in the Nb-Si-Ni, Nb-Si-Co, Ta-Si-Ni, V-Si-Ni, and Nb-Si-Fe ternary systems. Crucially, reactive hot pressing is capable of producing high-purity ZIP phase materials after the judicious, elemental system-specific optimization of the processing route. Synthesis of phase-pure materials – demonstrated in the Nb-Si-Ni ternary system by the synthesis of quasi phase-pure Nb 3 SiNi 2 and Ni 3 SiNb 2 ZIP phase-based materials – is a steppingstone to the prospective exploitation of the ZIP phases. Characterization of Nb 3 SiNi 2 and Ni 3 SiNb 2 involves crystal structure determination, spatially resolved chemical analysis, and determination of select thermal, electrical, magnetic, mechanical, and physical properties. Density functional theory is used to assess the stability of Nb 3 SiNi 2 & Ni 3 SiNb 2 and derivative binary compounds at different temperatures, also exploring the exfoliation of these two ZIP phases along specific surfaces to produce 2D derivatives.

Intermetallic compounds (IMCs)↗

NASA NTRS2022

Laser Patterning Assisted Devitrification and Domain Engineering of Amorphous and Nanocrystalline Alloys

We have investigated laser-patterning and devitrification as a novel method to realize emergent properties in modified regions at the ribbon surface consisting of periodic localized laser spots thermally treated under rapid heating and cooling conditions. Fe-based amorphous ribbons were annealed for systematically varied laser power. Extremely high heating and cooling rates on the order of 10(exp 8)-10(exp 10)K/s have been estimated by finite element analysis simulations. Observations suggest surface melting followed by rapid solidification fast enough to quench and form an amorphous structure upon cooling. Diffusion of heat occurs from the laser irradiated surface region so that a finite volume of material surrounding this region rises in temperature above the crystallization temperature relevant for conventional isothermal annealing experiments. The underlying mechanism of laser annealing and consequences of heat transients involved are discussed in terms of impacts upon micro/nanostructure, residual stresses, and magnetic domain structure surrounding the laser irradiated region. The study illustrates the potential to exploit spatially optimized phase transformations in a scalable manufacturing process of amorphous and nanocrystalline alloys to locally access otherwise inaccessible extreme heating and cooling rates.

Amorphous ribbons↗

DOE OSTI2024

Small‐Molecule Mixed Ionic‐Electronic Conductors for Efficient N‐Type Electrochemical Transistors: Structure‐Function Correlations

Abstract The fundamental challenge in electron‐transporting organic mixed ionic‐electronic conductors (OMIECs) is simultaneous optimization of electron and ion transport. Beginning from Y6‐type/U‐shaped non‐fullerene solar cell acceptors, we systematically synthesize and characterize molecular structures that address the aforementioned challenge, progressively introducing increasing numbers of oligoethyleneglycol (OEG; g) sidechains from 1 g to 3 g, affording OMIECs 1gY, 2gY, and 3gY, respectively. The crystal structure of 1gY preserves key structural features of the Y n series: a U‐shaped/planar core, close π–π molecular stacking, and interlocked acceptor groups. Versus inactive Y6 and Y11, all of the new glycolated compounds exhibit mixed ion‐electron transport in both conventional organic electrochemical transistor (cOECT) and vertical OECT (vOECT) architectures. Notably, 3gY with the highest OEG density achieves a high transconductance of 16.5 mS, an on/off current ratio of ~10 6 , and a turn‐on/off response time of 94.7/5.7 ms in vOECTs. Systematic optoelectronic, electrochemical, architectural, and crystallographic analysis explains the superior 3gY‐based OECT performance in terms of denser n gY OEG content, increased crystallite dimensions with decreased long‐range crystalline order, and enhanced film hydrophilicity which facilitates ion transport and efficient redox processes. Finally, we demonstrate an efficient small‐molecule‐based complementary inverter using 3gY vOECTs, showcasing the bioelectronic applicability of these new small‐molecule OMIECs.

Cho, Yongjoon↗

DOE OSTI2024

Small‐Molecule Mixed Ionic‐Electronic Conductors for Efficient N‐Type Electrochemical Transistors: Structure‐Function Correlations

Cho, Yongjoon↗

DOE OSTI2025

Automated workflow for non-empirical Wannier-localized optimal tuning of range-separated hybrid functionals

Here, we introduce an automated workflow for generating non-empirical Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functionals. WOT-SRSH functionals have been shown to yield highly accurate fundamental band gaps, band structures, and optical spectra for bulk and 2D semiconductors and insulators. Our workflow automatically and efficiently determines the WOT-SRSH functional parameters for a given crystal structure and composition, approximately enforcing the correct screened long-range Coulomb interaction and an ionization potential ansatz. In contrast to previous manual tuning approaches, our tuning procedure relies on a new search algorithm that only requires a few hybrid functional calculations with minimal user input. We demonstrate our workflow on 23 previously studied semiconductors and insulators, reporting the same high level of accuracy. By automating the tuning process and improving its computational efficiency, the approach outlined here enables applications of the WOT-SRSH functional to compute spectroscopic and optoelectronic properties for a wide range of materials.

Gant, Stephen E. [University of California, Berkel↗

DOE OSTI2024

Strategically designed metal-free deep-ultraviolet birefringent crystals with superior optical properties

Finding new birefringent materials with deep-ultraviolet (DUV, λ < 200 nm) transparency is urgent, as current commercial materials cannot meet the rapidly growing demands in related application fields. Herein, three guanidinium-based compounds, C(NH 2 ) 3 CH 3 SO 3 , β-C(NH 2 ) 3 Cl, and γ-C(NH 2 ) 3 Cl, all featuring [C(NH 2 ) 3 ·X] ∞ (X = CH 3 SO 3 and Cl) pseudo layers, were designed through structural motif tailoring. Theoretical calculations indicate that these metal-free compounds all possess broad bandgaps (6.49–6.71 eV, HSE06) and remarkable birefringence (cal. 0.166–0.211 @ 1064 nm). Centimeter-sized C(NH 2 ) 3 CH 3 SO 3 crystals have been grown using a feasible aqua-solution method. Subsequently, to further optimize the properties, β/γ-C(NH 2 ) 3 Cl was remolded by further tailoring the [C(NH 2 ) 3 ] + cationic unit and the acceptor Cl - anion, and then the fourth compound NH 2 COF was theoretically constructed. Interestingly, NH 2 COF exhibits the desired coexistence of a wider bandgap (7.87 eV, HSE06) and giant birefringence (cal. 0.241 @ 1064 nm) attributed to its higher density of well-aligned birefringence-active groups (BAGs). Furthermore, among these four designed compounds, C(NH 2 ) 3 CH 3 SO 3 has been experimentally synthesized and exhibits a short UV cutoff edge. Centimeter-sized crystals have been grown using a feasible aqueous solution method. This study provides an effective strategy to optimize the density of BAGs for large birefringence and offers valuable insights into the strategic design of metal-free DUV birefringent crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1982

Continuous Czochralski growth. Development of advanced Czochralski growth process to produce low cost 150 kg silicon ingots from a single crucible for technology readiness

The improvement of growth rates using radiation shielding and investigation of the crucible melt interaction for improved yields were emphasized. Growth runs were performed from both 15 and 16 inch diameter crucibles, producing 30 and 37 kg ingots respectively. Efforts to increase the growth rate of 150 mm diameter ingots were limited by temperature instabilities believed to be caused by undesirable thermal convections in the larger melts. The radiation shield improved the growth rate somewhat, but the thermal instability was still evident, leading to nonround ingots and loss of dislocation-free structure. A 38 kg crystal was grown to demonstrate the feasibility of producing 150 kg with four growth cycles. After the grower construction phase, the Hamco microprocessor control system was interfaced to the growth facility, including the sensor for automatic control of seeding temperature, and the sensor for automatic shouldering. Efforts focused upon optimization of the seeding, necking, and shoulder growth automation programs.

Source record↗

NASA NTRS1976

The nature of surfaces and their influence in wear mechanisms

The wear of materials is strongly dependent upon the nature of the solid surfaces in contact, their properties and the nature of their films. Oxide films, orientation, crystal transformations, adhesive binding, crystal structure, hardness, and the presence of alloying agents are all shown to affect one or more of the forms of wear. The three most common forms of wear, adhesive, abrasive, and corrosive, are discussed in terms of the way each is affected by various material properties. Results presented indicate how wear can be optimized by concern for properties of materials.

Buckley, D. H.↗

NASA NTRS1977

The nature of surfaces and their influence in wear mechanisms

The wear of materials is strongly dependent upon the nature of the solid surfaces in contact, their properties and the nature of the films on them. Oxide films, orientation, crystal transformations, adhesive binding, crystal structure, hardness and the presence of alloying agents are all shown to effect one or more of the forms of wear. The three most common forms of wear, adhesive, abrasive, and corrosive, are discussed in terms of the way each is affected by various material properties. Results presented indicate how wear can be optimized by concern for properties of materials.

Buckley, D. H.↗

DOE OSTI2025

Structural Characterization of Linker Shielding in ADC Site-Specific Conjugates

Background/Objectives: Antibody–Drug Conjugates (ADCs) have rapidly evolved from early, rudimentary conjugates to highly targeted and precisely engineered molecules. Despite notable clinical successes, ADCs continue to face significant challenges, including aggregation and high hydrophobicity driven by high drug-to-antibody ratios (DARs), premature payload release, dose-limiting toxicities, and suboptimal pharmacokinetics. While site-specific linker–payload conjugation has improved ADC homogeneity and stability, the structural basis of antibody–linker interactions at specific sites remains underexplored. Methods: In this work, we present the crystal structures of trastuzumab Fab and Fc domains site-specifically conjugated with a cleavable linker–payload. Results: Our findings suggest that pockets within both Fab and Fc regions may interact with and shield the linker portion of the conjugate. Conclusions: These insights highlight the previously underappreciated potential of structure-based design to drive the optimization of ADC linker chemistry and facilitate the co-design of bespoke linker–payloads tailored to individual antibody conjugation sites.

Jaime-Garza, Maru [Discovery Chemistry, Merck & Co↗

NASA NTRS2005

E-Beam Processing of Polymer Matrix Composites for Multifunctional Radiation Shielding

Aliphatic polymers were identified as optimum radiation shielding polymeric materials for building multifunctional structural elements for in-space habitats. Conceptual damage tolerant configurations of polyolefins have been proposed, but many manufacturing issues relied on methods and materials which have sub-optimal radiation shielding characteristics (for example, epoxy matrix and adhesives). In the present approach, we shall investigate e-beam processing technologies for inclusion of high-strength aliphatic polymer reinforcement structures into a highly cross-linked polyolefin matrix. This paper reports the baseline thermo-mechanical properties of low density polyethylene and highly crystallized polyethylene.

Hou, Tan-Hung↗

DOE OSTI2024

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗