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Mehta, Apurva

Publications and source records attributed to Mehta, Apurva.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Domain Knowledge Guided Bayesian Optimization For Autonomous Alignment Of Complex Scientific Instruments

Bayesian Optimization (BO) is a powerful tool for optimizing complex non-linear systems. However, its performance degrades in high-dimensional problems with tightly coupled parameters and highly asymmetric objective landscapes, where rewards are sparse. In such needle-in-a-haystack scenarios, even advanced methods like trust-region BO (TurBO) often lead to unsatisfactory results. We propose a domain knowledge guided Bayesian Optimization approach, which leverages physical insight to fundamentally simplify the search problem by transforming coordinates to decouple input features and align the active subspaces with the primary search axes. We demonstrate this approach's efficacy on a challenging 12-dimensional, 6-crystal Split-and-Delay optical system, where conventional approaches, including standard BO, TuRBO and multi-objective BO, consistently led to unsatisfactory results. When combined with an reverse annealing exploration strategy, this approach reliably converges to the global optimum. The coordinate transformation itself is the key to this success, significantly accelerating the search by aligning input co-ordinate axes with the problem's active subspaces. As increasingly complex scientific instruments, from large telescopes to new spectrometers at X-ray Free Electron Lasers are deployed, the demand for robust high-dimensional optimization grows. Our results demonstrate a generalizable paradigm: leveraging physical insight to transform high-dimensional, coupled optimization problems into simpler representations can enable rapid and robust automated tuning for consistent high performance while still retaining current optimization algorithms.

FOS: Computer and information sciences↗
DOE OSTI2024

Superconducting phase diagram in Bi x Ni 1 – x thin films: The effects of Bi stoichiometry on superconductivity

The Bi-Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in Bi 3 ⁢Ni crystals. While Ni acts as a ferromagnetic element in such systems, the role of the strong spin-orbit coupling element Bi in superconductivity has remained unexplored. In this work, we systematically studied the effects of Bi stoichiometry on the superconductivity of Bi x ⁢Ni 1–x thin films (x ≈ 0.5–0.9) fabricated via a composition-spread approach. Here, the superconducting phase map of Bi x ⁢Ni 1–x thin films exhibited a superconducting composition region attributable to the intermetallic Bi 3 ⁢Ni phase with different amounts of excess Bi, revealed by synchrotron x-ray diffraction analysis. Interestingly, the mixed-phase region with Bi 3 ⁢Ni and Bi showed unusual increases in the superconducting transition temperature and residual resistance ratio as more Bi impurities were included, with the maximum T c (=4.2K) observed at x ≈ 0.79. A correlation analysis of structural, electrical, and magneto-transport characteristics across the composition variation revealed that the unusual superconducting “dome” is due to two competing roles of Bi: impurity scattering and carrier doping. We found that the carrier doping effect is dominant in the mild doping regime (0.74 ≤ x ≤ 0.79), while impurity scattering becomes more pronounced at larger Bi stoichiometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Physics constrained unsupervised deep learning for rapid, high resolution scanning coherent diffraction reconstruction

By circumventing the resolution limitations of optics, coherent diffractive imaging (CDI) and ptychography are making their way into scientific fields ranging from X-ray imaging to astronomy. Yet, the need for time consuming iterative phase recovery hampers real-time imaging. While supervised deep learning strategies have increased reconstruction speed, they sacrifice image quality. Furthermore, these methods’ demand for extensive labeled training data is experimentally burdensome. Here, we propose an unsupervised physics-informed neural network reconstruction method, PtychoPINN, that retains the factor of 100-to-1000 speedup of deep learning-based reconstruction while improving reconstruction quality by combining the diffraction forward map with real-space constraints from overlapping measurements. In particular, PtychoPINN gains a factor of 4 in linear resolution and an 8 dB improvement in PSNR while also accruing improvements in generalizability and robustness. This blend of performance and computational efficiency offers exciting prospects for high-resolution real-time imaging in high-throughput environments such as X-ray free electron lasers (XFELs) and diffraction-limited light sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effects of elevated-temperature deposition on the atomic structure of amorphous Ta 2 O 5 films

Brownian thermal noise as a result of mechanical loss in optical coatings will become the dominant source of noise at the most sensitive frequencies of ground-based gravitational-wave detectors. Experiments found, however, that a candidate material, amorphous Ta 2 O 5 , is unable to form an ultrastable glass and, consequently, to yield a film with significantly reduced mechanical loss through elevated-temperature deposition alone. X-ray scattering PDF measurements are carried out on films deposited and subsequently annealed at various temperatures. Inverse atomic modeling is used to analyze the short and medium range features in the atomic structure of these films. Furthermore, in silico deposition simulations of Ta 2 O 5 are carried out at various substrate temperatures and an atomic level analysis of the growth at high temperatures is presented. It is observed that upon elevated-temperature deposition, short range features remain identical, whereas medium range order increases. After annealing, however, both the short and medium range orders of films deposited at different substrate temperatures are nearly identical. A discussion on the surface diffusion and glass transition temperatures indicates that future pursuits of ultrastable low-mechanical-loss films through elevated temperature deposition should focus on materials with a high surface mobility, and/or lower glass transition temperatures in the range of achievable deposition temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metallic glass coating material

A metallic glass coating material is composed of an alloy of Fe, B, and one of the metals Nb, Mo, Zr, or W. The ratios of Fe, B, and the metal are predetermined using machine learning predictions and high-throughput experiments. In one example, the material is an alloy of Fe, Nb, Mo and B, of the form Fe x (Nb, Mo) y B z , where x is in the range 18-28, y is in the range 35-45, and z is in the range 32-42. In another example, the material may be the alloy Fe 23 (Nb, Mo) 40 B 37 . The alloy may be doped with Zr and/or W, where the Zr and/or W comprises at most 10% of the alloy.

Mehta, Apurva↗
DOE OSTI2023

Tuning In-Plane Magnetic Anisotropy and Interfacial Exchange Coupling in Epitaxial La 2/3 Sr 1/3 CoO 3 /La 2/3 Sr 1/3 MnO 3 Heterostructures

Controlling the in-plane magnetocrystalline anisotropy and interfacial exchange coupling between ferromagnetic (FM) layers plays a key role in next-generation spintronic and magnetic memory devices. In this work, we explored the effect of tuning the magnetocrystalline anisotropy of La 2/3 Sr 1/3 CoO 3 (LSCO) and La 2/3 Sr 1/3 MnO 3 (LSMO) layers and the corresponding effect on interfacial exchange coupling by adjusting the thickness of the LSCO layer (t LSCO ). The epitaxial LSCO/LSMO bilayers were grown on (110) o -oriented NdGaO 3 (NGO) substrates with a fixed LSMO (top layer) thickness of 6 nm and LSCO (bottom layer) thicknesses varying from 1 to 10 nm. Despite the small difference (~0.2%) in lattice mismatch between the two in-plane directions, [001] o and [11̅0] o , a pronounced in-plane magnetic anisotropy was observed. Soft X-ray magnetic circular dichroism hysteresis loops revealed that for t LSCO ≤ 4 nm, the easy axes for both LSCO and LSMO layers were along the [001] o direction, and the LSCO layer was characterized by magnetically active Co 2+ ions that strongly coupled to the LSMO layer. No exchange bias effect was observed in the hysteresis loops. In contrast, along the [11̅0] o direction, the LSCO and LSMO layers displayed a small difference in their coercivity values, and a small exchange bias shift was observed. As t LSCO increased above 4 nm, the easy axis for the LSCO layer remained along the [100] o direction, but it gradually rotated to the [11̅0] o direction for the LSMO layer, resulting in a large negative exchange bias shift. Therefore, we provide a way to control the magnetocrystalline anisotropy and exchange bias by tuning the interfacial exchange coupling between the two FM layers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Local ordering in Ge/Ge–Sn semiconductor alloy core/shell nanowires revealed by extended x-ray absorption fine structure (EXAFS)

Short-range atomic order in semiconductor alloys is a relatively unexplored topic that may promote design of new materials with unexpected properties. Here, local atomic ordering is investigated in Ge–Sn alloys, a group-IV system that is attractive for its enhanced optoelectronic properties achievable via a direct gap for Sn concentrations exceeding ≈10 at. %. The substantial misfit strain imposed on Ge–Sn thin films during growth on bulk Si or Ge substrates can induce defect formation; however, misfit strain can be accommodated by growing Ge–Sn alloy films on Ge nanowires, which effectively act as elastically compliant substrates. In this work, Ge core/Ge 1–x Sn x (x ≈ 0.1) shell nanowires were characterized with extended x-ray absorption fine structure (EXAFS) to elucidate their local atomic environment. Simultaneous fitting of high-quality EXAFS data collected at both the Ge K-edge and the Sn K-edge reveals a large (≈ 40%) deficiency of Sn in the first coordination shell around a Sn atom relative to a random alloy, thereby providing the first direct experimental evidence of significant short-range order in this semiconductor alloy system. Furthermore, comparison of path length data from the EXAFS measurements with density functional theory simulations provides alloy atomic structures consistent with this conclusion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Magnetic phase diagram mapping in Fe 1- x Rh x composition-spread thin films

We have fabricated high-quality polycrystalline Fe 1- x Rh x composition-spread thin films by cosputtering Fe and Rh, and investigated their structural and magnetic transformations as a systematic function of composition. With increasing Rh concentration, Fe 1-x Rh x thin film undergoes from an α' phase to a disordered γ phase and also shows a magnetic transition from a ferromagnetic phase to a paramagnetic phase. Vibrating-sample magnetometry and x-ray magnetic circular dichroism measurements show an antiferromagnetic-ferromagnetic transition in the range of 0.52 < x < 0.58 in the Fe 1- x Rh x composition gradient at room temperature. Based on our structural and magnetic property mapping, we construct a thin-film phase diagram of Fe 1- x Rh x . Compared to reported results in bulk alloys, the antiferromagnetic-ferromagnetic transition in the Fe 1- x Rh x thin films was found to occur at slightly higher Rh concentrations, while the boundary between the pure γ phase and the α'/ γ mixed phase region is shifted to the lower concentration Rh.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Discovery of LaAlO 3 as an efficient catalyst for two-electron water electrolysis towards hydrogen peroxide

Electrochemical two-electron water oxidation reaction (2e-WOR) has drawn significant attention as a promising process to achieve the continuous on-site production of hydrogen peroxide (H 2 O 2 ). However, compared to the cathodic H 2 O 2 generation, the anodic 2e-WOR is more challenging to establish catalysts due to the severe oxidizing environment. In this study, we combine density functional theory (DFT) calculations with experiments to discover a stable and efficient perovskite catalyst for the anodic 2e-WOR. Our theoretical screening efforts identify LaAlO 3 perovskite as a stable, active, and selective candidate for catalyzing 2e-WOR. Our experimental results verify that LaAlO 3 achieves an overpotential of 510 mV at 10 mA cm -2 in 4 M K 2 CO 3 /KHCO 3 , lower than those of many reported metal oxide catalysts. In addition, LaAlO 3 maintains a stable H 2 O 2 Faradaic efficiency with only a 3% decrease after 3 h at 2.7 V vs. RHE. This computation-experiment synergistic approach introduces another effective direction to discover promising catalysts for the harsh anodic 2e-WOR towards H 2 O 2 .

08 HYDROGEN↗
DOE OSTI2022

Strain- and thickness-dependent magnetic properties of epitaxial La 0.67 Sr 0.33 CoO 3 /La 0.67 Sr 0.33 MnO 3 bilayers

Magnetic properties and interfacial phenomena of epitaxial perovskite oxides depend sensitively on parameters such as film thickness and strain state. In this work, epitaxial La0 .67 Sr 0.33 CoO 3 (LSCO)/La 0.67 Sr 0.33 MnO 3 (LSMO) bilayers were grown on NdGaO 3 (NGO) and LaAlO 3 (LAO) substrates with a fixed LSMO thickness of 6 nm, and LSCO thickness (t LSCO ) varying from 2 to 10 nm. Soft x-ray magnetic spectroscopy revealed that magnetically active Co 2+ ions that strongly coupled to the LSMO layer were observed below a critical t LSCO for bilayers grown on both substrates. On LAO substrates, this critical thickness was 2 nm, above which the formation of Co 2+ ions was quickly suppressed leaving only a soft LSCO layer with mixed valence Co 3+ /Co 4+ ions. The magnetic properties of both LSCO and LSMO layers displayed strong t LSCO dependence. This critical t LSCO increased to 4 nm on NGO substrates, and the magnetic properties of only the LSCO layer displayed t LSCO dependence. A non-magnetic layer characterized by Co 3+ ions and with a thickness below 2 nm exists at the LSCO/substrate interface for both substrates. Therefore, the results contribute to the understanding of interfacial exchange spring behavior needed for applications in next generation spintronic and magnetic memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomic-Layer-Deposited Aluminum Oxide Thin Films Probed with X-ray Scattering and Compared to Molecular Dynamics and Density Functional Theory Models

A better understanding of amorphous aluminum oxide’s structure and electronic properties is obtained through combined experimental and computational approaches. Grazing incidence X-ray scattering measurements were carried out on aluminum oxide thin films grown using thermal atomic layer deposition. The corresponding pair distribution functions (PDFs) showed structures similar to previously reported PDFs of solid-state amorphous alumina and molten alumina. Structural models based on crystalline alumina polymorphs (PDFgui) and amorphous alumina (molecular dynamics, MD) were examined for structural comparisons to the experimental PDF data. Smaller MD models were optimized and verified against larger models to allow for quantum chemical electronic structure calculations. The electronic structure of the amorphous alumina models yields additional insight into the band structure and electronic defects present in amorphous alumina that are not present in crystalline samples.

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

Machine learned synthesizability predictions aided by density functional theory

Abstract A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.

Lee, Andrew (ORCID:0000000153014295)↗
DOE OSTI2022

Thin-Film Paradigm to Probe Interfacial Diffusion during Solid-State Metathesis Reactions

We highlight a paradigm for studying complex reaction mechanisms that guide the synthesis of materials. Thin films of FeCl 2 and Na 2 S 2 were deposited to study the metathesis reaction to form FeS 2 and NaCl. In situ X-ray reflectivity was used to monitor the interface between materials, which revealed a slow, impeded reaction at high temperatures as compared to previous studies using powder samples. AC impedance and X-ray photoelectron spectroscopy provided insight into distribution of elements and conductivity of the phases present during the reaction, and phase-field modeling was used to elucidate the diffusion of ions throughout the thin-film bilayers. Here, the use of thin-film bilayers provides a simplified system to study solid-state metathesis reactions and highlights the complexity of diffusion at solid-state interfaces.

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

Giant Orbital Anisotropy with Strong Spin–Orbit Coupling Established at the Pseudomorphic Interface of the Co/Pd Superlattice

Orbital anisotropy at interfaces in magnetic heterostructures has been key to pioneering spin–orbit-related phenomena. However, modulating the interface’s electronic structure to make it abnormally asymmetric has been challenging because of lack of appropriate methods. Here, the authors report that low-energy proton irradiation achieves a strong level of inversion asymmetry and unusual strain at interfaces in [Co/Pd] superlattices through nondestructive, selective removal of oxygen from Co3O4/Pd superlattices during irradiation. Structural investigations corroborate that progressive reduction of Co3O4into Co establishes pseudomorphic growth with sharp interfaces and atypically large tensile stress. The normal component of orbital to spin magnetic moment at the interface is the largest among those observed in layered Co systems, which is associated with giant orbital anisotropy theoretically confirmed, and resulting very large interfacial magnetic anisotropy is observed. All results attribute not only to giant orbital anisotropy but to enhanced interfacial spin–orbit coupling owing to the pseudomorphic nature at the interface. They are strongly supported by the observation of reversal of polarity of temperature-dependent Anomalous Hall signal, a signature of Berry phase. This work suggests that establishing both giant orbital anisotropy and strong spin–orbit coupling at the interface is key to exploring spintronic devices with new functionalities.

42 ENGINEERING↗