arXiv subjects

Vinayak P. Dravid

Publications and source records attributed to Vinayak P. Dravid.

At least 19 recordsLinked to original sources

arXiv2026

Physics-Constrained Learning of Dose-Dependent Spectral Degradation in Metal--Organic Frameworks from In Situ Low-Loss EELS

Electron-beam irradiation limits atomic-resolution characterization of beam-sensitive hybrid materials, yet quantitative models that connect \textit{in situ} spectroscopy to dose-dependent degradation remain scarce. Here we use a physics-informed neural network (PINN) to model beam-induced spectral evolution in MIL-101(Fe) from an in situ low-loss electron energy-loss spectroscopy (EELS) dose series. Each spectrum is reduced to fixed-window low-loss descriptors, $\tilde n_{\mathrm{eff},j}(Φ)=\int_{\mathcal{W}_j}S(E,Φ)\,dE$, evaluated over nominal $π$--$π^{*}$, C--C, C--O, and M--O windows. These descriptors are relative window-integrated low-loss spectral areas, not absolute f-sum-rule effective electron numbers. For each spectral channel, a latent integrity variable $C_i(Φ)$ obeys the same uncoupled power-law degradation equation in normalized dose space, $dC_i/dϕ=-k_i C_i^{p_i}$, regularized by monotonicity, boundedness, and a single hierarchy prior $k_{\mathrm{C\text{-}O}}\geq k_{\mathrm{C\text{-}C}}$. Applied to nine dose frames spanning 152--1368~e$^-$/Å$^2$, the ensemble PINN identifies C--O and C--C as the most strongly dose-sensitive linker-associated channels, with half-integrity thresholds of approximately $1.0\times10^3$~e$^-$/Å$^2$. The 1--3~eV $π$--$π^{*}$-labelled window increases with dose and is therefore interpreted as a mixed low-energy response, likely involving oscillator-strength redistribution rather than direct monotonic loss of a single bond population. The framework provides a dose-dependent, spectroscopy constrained description of MOF degradation while also defining the limits of what fixed-window low-loss EELS can assign without independent chemical-state validation.

cond-mat.mtrl-sci↗

arXiv2026

Oxide-Nitride Heteroepitaxy for Low-Loss Dielectrics in Superconducting Quantum Circuits

Superconducting qubits show great promise for the realization of fault-tolerant quantum computing, but lossy, amorphous dielectrics limit current technology. Identifying highly crystalline and stoichiometric dielectrics with intrinsically low microwave loss is therefore a central materials challenge, yet experimentally validated platforms remain scarce. This work integrates a crystalline dielectric into a heteroepitaxial TiN/$γ$-Al$_2$O$_3$/TiN trilayer grown via pulsed laser deposition. Correlative high-resolution imaging, diffraction, and spectroscopy measurements confirm the single-crystal quality and chemical integrity of all layers, with minimal defects and limited anion interdiffusion across the oxide-nitride interfaces. Using microwave lumped-element resonators with parallel-plate capacitors, this work establishes an experimentally-measured upper bound for the dielectric loss of $γ$-Al$_2$O$_3$, which has a low intrinsic two-level system loss of $δ_{\text{TLS}}^0 = (2.8 \pm 0.1) \times 10^{-5}$. These results establish heteroepitaxial oxides on transition metal nitrides as an attractive materials platform for superconducting quantum circuits, particularly for integration into compact device architectures such as merged-element transmons and microwave kinetic inductance detectors.

quant-ph↗

arXiv2026

Octupole-driven spin torque switching of antiferromagnetic tunnel junctions

Magnetic tunnel junctions (MTJs) based on ferromagnets are canonical devices in spintronics, with wide-ranging applications in data storage, computing, and sensing. They simultaneously exhibit mechanisms for electrical detection and control of magnetic order through the tunneling magnetoresistance (TMR) and spin-transfer torque (STT) effects, respectively. It was long assumed that neither of these effects could be sizeable in all-antiferromagnetic tunnel junctions (AATJs), since they exhibit no net magnetization. Recently, however, it was shown that AATJs based on chiral antiferromagnets do exhibit TMR due to their non-relativistic momentum-dependent spin polarization and cluster magnetic octupole moment (CMO), which are manifestations of their spin-split band structure. However, the reciprocal effect, i.e., the antiferromagnetic counterpart of STT, has been assumed non-existent due to the total electric current being spin-neutral. Here, we report nanoscale AATJs exhibiting this reciprocal effect, which we term octupole-driven spin-transfer torque (OTT). We demonstrate current-induced OTT switching of PtMn3|MgO|PtMn3 AATJs, exhibiting a TMR value of 363% at room temperature and switching current densities of the order of 10 MA/cm2. Our theoretical modeling explains the origin of OTT in terms of the imbalance between intra- and inter-sublattice spin currents across the AATJ, and equivalently, in terms of the non-zero net cluster octupole polarization of each PtMn3 layer. This work establishes a new materials platform for antiferromagnetic spintronics and provides a pathway towards deeply scaled magnetic memory and room-temperature terahertz technologies.

cond-mat.mtrl-sci↗

arXiv2026

Reconfigurable field-free spin Hall nano-oscillators enabled by crystallographic anisotropy in epitaxial Co/Pt

Spin Hall nano-oscillators (SHNOs) are nanoscale microwave sources for wireless communication, neuromorphic computing and oscillator-based Ising machines, but conventional devices require a global magnetic bias. Here we replace this bias through crystallographic anisotropy in epitaxial Co/Pt. Growth of hcp Co with its c-axis in the film plane produces an anisotropy field of about 0.36 T and enables field-free auto-oscillations above 10 GHz in nanoconstriction SHNOs. The active current polarity is selected by the remanent magnetization, providing nonvolatile reconfiguration of the oscillation state. Micro-focused Brillouin light scattering confirms that the nonlinear response is confined to the nanoconstriction region. Lithographic control of the angle between the current and anisotropy axes tunes the excitation threshold and drives two spectral branches from separated modes to a dominant single branch, consistent with mutual synchronization. These results establish epitaxial crystallographic anisotropy as a route to reconfigurable field-free spintronic oscillators and oscillator networks.

cond-mat.mes-hall↗

arXiv2026

Physics-Informed Neural Networks for Sparse Strain-Field Reconstruction in 4D-STEM

Quantitative strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) typically requires densely sampled scans that can damage beam-sensitive specimens. We develop a physics-informed neural network (PINN) for sparse 4D-STEM strain reconstruction that embeds elastic equilibrium and Saint-Venant compatibility in the training loss through automatic differentiation. The architecture combines a coordinate-based implicit representation, sine activations with stable second derivatives, frozen residual-scale normalization, an exponential physics-weight ramp, and residual-based adaptive collocation. We apply a sine-activated residual network to an experimental $180\times400$-pixel strain map of domain-structured PbGeSnSe$_{1.5}$Te$_{1.5}$. Across $1$-$75%$ sampling ($720$-$54{,}000$ probe positions), $R^2$ for $\varepsilon_{xx}$ reaches $0.80$ at $10%$ sampling and saturates near $0.86$ by $25%$; the chevron strain-band morphology is recovered from $10%$ of probe positions. At $10%$ sampling, the PINN reduces mean absolute error by approximately $26%$ relative to compressed sensing and $22%$ relative to Gaussian-process regression. An ablation against an equal-capacity data-only SIREN shows that the PDE prior improves accuracy at extreme sparsity and consistently improves physical self-consistency, but biases the reconstruction when data are abundant. Monte Carlo dropout and mean-field variational inference provide per-pixel epistemic uncertainty maps correlated with reconstruction error. With an appropriate constitutive model, the framework is adaptable to strain mapping across diverse material systems.

cond-mat.mtrl-sci↗

arXiv2026

Schema-Bound LLM Control of Scientific Instrumentation through Model Context Protocol Skills

Large language models (LLMs) can plan tool-mediated scientific work, but scientific instruments remain difficult to connect to such agents: vendor APIs may load only inside acquisition host processes, facilities may prohibit cloud-hosted agents, and natural-language interfaces can emit physically unreasonable arguments. We present a method for connecting local LLMs to scientific instruments through the Model Context Protocol (MCP). It combines: (1) a schema-bound tool surface that validates requests against physical bounds before adapter dispatch; (2) a vendor-neutral, host-process adapter pattern separating language-side reasoning from instrument-side execution; (3) a persistent lifecycle for long-running live-processing jobs; and (4) MCP-prompt-registered skills that compose typed tools into reusable multi-step protocols. Our open-source reference server exposes 30 typed tools, 5 live-job types, and 6 skills through a physics-plausible simulator implementing the same protocol surface. Validation is software-only: all 120 hardware-independent tests pass deterministically, while 15 local-LLM integration tests pass 12-15 of 15 across runs because of model nondeterminism. A preliminary single-run probe across five open tool-calling LLMs indicates that the schema-bound interface can be driven locally by small open-weight models without cloud dependency; it is not a benchmark and has no confidence intervals. The method provides a bounded, testable, and reproducible foundation for closed-loop agentic instrumentation research.

cs.SE↗

arXiv2026

Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials

Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This "valley of death" stems from optimization that prioritizes laboratory metrics over industrial viability. We propose a new strategy: "born-qualified" autonomous development, which embeds manufacturability, cost, and durability constraints from the outset. This approach is enabled by four pillars, including the development of multi-objective metrics, causal models, a modular infrastructure, and embedding manufacturing in the discovery loop. Realizing this vision will require sustained, community-wide commitment, but the potential return on that investment is commensurate with the scale of the challenge.

cond-mat.mtrl-sci↗

arXiv2026

Microstructural Topology as a Prescriptor for Quantum Coherence: Towards A Unified Framework for Decoherence in Superconducting Qubits

In superconducting quantum circuits, decoherence improvements are frequently obtained through process interventions that simultaneously modify surface chemistry, microstructural topology, and device geometry, leaving mechanistic attribution structurally underdetermined. Predictive materials engineering requires measurable structural statistics to be separated from geometry-dependent coupling coefficients into independently testable factors. We introduce the concept of classical and quantum microstructure. In that context, we formulate a channel-wise separable framework for decoherence in superconducting transmon qubits in which each loss channel is described by a reduced prescriptor. Here, a channel-specific microstructural state variable is determined independently of device geometry, and a geometry-dependent coupling functional is computable from field solutions without reference to surface chemistry. We derive this product form from a spatially resolved kernel representation and establish a perturbative separability criterion that defines the regime where independent variation of the variables is valid. The framework specifies five prescriptor classes for dominant loss pathways in transmon-class devices. Falsifiability is operationalized through a pre-committed 2x2 experimental protocol in which the variables must satisfy independent ratio checks within propagated uncertainty. A Minimum-Dataset Specification standardizes reporting for cross-laboratory inference. Part I establishes the conceptual and mathematical architecture; coordinated experimental validation is reserved for Part II.

quant-ph↗

arXiv2025

RN-SDEs: Limited-Angle CT Reconstruction with Residual Null-Space Diffusion Stochastic Differential Equations

Computed tomography is a widely used imaging modality with applications ranging from medical imaging to material analysis. One major challenge arises from the lack of scanning information at certain angles, resulting in distortion or artifacts in the reconstructed images. This is referred to as the Limited Angle Computed Tomography (LACT) reconstruction problem. To address this problem, we propose the use of Residual Null-Space Diffusion Stochastic Differential Equations (RN-SDEs), which are a variant of diffusion models that characterize the diffusion process with mean-reverting (MR) stochastic differential equations. To demonstrate the generalizability of RN-SDEs, we conducted experiments with two different LACT datasets, ChromSTEM and C4KC-KiTS. Through extensive experiments, we demonstrate that by leveraging learned MR-SDEs as a prior and emphasizing data consistency using Range-Null Space Decomposition (RNSD) based rectification, we can recover high-quality images from severely degraded ones and achieve state-of-the-art performance in most LACT tasks. Additionally, we present a quantitative comparison of RN-SDE with other networks, in terms of computational complexity and runtime efficiency, highlighting the superior effectiveness of our proposed approach.

eess.IV↗

arXiv2025

Identifying Materials-Level Sources of Performance Variation in Superconducting Transmon Qubits

The Superconducting Materials and Systems (SQMS) Center, a DOE National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various nondestructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T$_1$ lifetime across different devices. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices, but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values.

quant-ph↗

arXiv2024

Electron-Induced Radiation Chemistry in Environmental Transmission Electron Microscopy

Environmental transmission electron microscopy (E-TEM) enables direct observation of nanoscale chemical processes crucial for catalysis and materials design. However, the high-energy electron probe can dramatically alter reaction pathways through radiolysis - the dissociation of molecules under electron beam irradiation. While extensively studied in liquid-cell TEM, the impact of radiolysis in gas-phase reactions remains unexplored. Here, we present a numerical model elucidating radiation chemistry in both gas and liquid E-TEM environments. Our findings reveal that while gas-phase E-TEM generates radiolytic species with lower reactivity than liquid-phase systems, these species can accumulate to reaction-altering concentrations, particularly at elevated pressures. We validate our model through two case studies: the radiation-promoted oxidation of aluminum nanocubes and disproportionation of carbon monoxide. In both cases, increasing the electron beam dose rate directly accelerates their reaction kinetics, as demonstrated by enhanced AlOx growth and carbon deposition. Based on these insights, we establish practical guidelines for controlling radiolysis in closed-cell nanoreactors. This work not only resolves a fundamental challenge in electron microscopy but also advances our ability to rationally design materials with sub-Angstrom resolution.

cond-mat.mtrl-sci↗

arXiv2024

Enhanced Superconducting Qubit Performance Through Ammonium Fluoride Etch

The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride. We show that the ammonium fluoride etch process results in a statistically significant improvement in median $\text{T}_1$ by $\sim22\%$ ($p=0.002$), and a reduction in the number of strongly-coupled TLS in the tunable frequency range. Microwave resonator measurements on samples treated with the ammonium fluoride etch prior to niobium deposition also show $\sim33\%$ lower TLS-induced loss tangent compared to the BOE treated samples. As the chemical treatment primarily modifies the Josephson junction-substrate interface and substrate-air interface, we perform targeted chemical and structural characterizations to examine materials' differences at these interfaces and identify multiple microscopic changes that could contribute to decreased TLS.

cond-mat.mtrl-sci↗

arXiv2024

Iterative Phase Retrieval Algorithms for Scanning Transmission Electron Microscopy

Scanning transmission electron microscopy (STEM) has been extensively used for imaging complex materials down to atomic resolution. The most commonly employed STEM modality, annular dark-field imaging, produces easily-interpretable contrast, but is dose-inefficient and produces little to no discernible contrast for light elements and weakly-scattering samples. An alternative is to use STEM phase retrieval imaging, enabled by high speed detectors able to record full images of a diffracted STEM probe over a grid of scan positions. Phase retrieval imaging in STEM is highly dose-efficient, enabling the measurement of the structure of beam-sensitive materials such as biological samples. Here, we comprehensively describe the theoretical background, algorithmic implementation details, and perform both simulated and experimental tests for three iterative phase retrieval STEM methods: focused-probe differential phase contrast, defocused-probe parallax imaging, and a generalized ptychographic gradient descent method implemented in two and three dimensions. We discuss the strengths and weaknesses of each of these approaches by comparing the transfer of information using analytical expressions and numerical results for a white-noise model. This presentation of STEM phase retrieval methods aims to make these methods more approachable, reproducible, and more readily adoptable for many classes of samples.

cond-mat.mtrl-sci↗

arXiv2024

Operando Analysis of Adsorption-Limited Hydrogen Oxidation Reaction at Palladium Surfaces

Palladium (Pd) catalysts have been extensively studied for the direct synthesis of H2O through the hydrogen oxidation reaction at ambient conditions. This heterogeneous catalytic reaction not only holds considerable practical significance but also serves as a classical model for investigating fundamental mechanisms, including adsorption and reactions between adsorbates. Nonetheless, the governing mechanisms and kinetics of its intermediate reaction stages under varying gas conditions remains elusive. This is attributed to the intricate interplay between adsorption, atomic diffusion, and concurrent phase transformation of catalyst. Herein, the Pd-catalyzed, water-forming hydrogen oxidation is studied, in situ, to investigate intermediate reaction stages via fluid cell transmission electron microscopy. The dynamic behaviors of water generation, associated with reversible palladium hydride formation, are captured in real time with a nanoscale spatial resolution. Our findings suggest that the hydrogen oxidation rate catalyzed by Pd is significantly affected by the sequence in which gases are introduced. Through direct evidence of electron diffraction and density functional theory calculation, we demonstrate that the hydrogen oxidation rate is limited by adsorption processes of gas precursors. These nanoscale insights help identify the optimal reaction conditions for Pd-catalyzed hydrogen oxidation, which has substantial implications for water production technologies. The developed understanding also advocates a broader exploration of analogous mechanisms in other metal-catalyzed reactions.

cond-mat.mtrl-sci↗

arXiv2024

Formation and Microwave Losses of Hydrides in Superconducting Niobium Thin Films Resulting from Fluoride Chemical Processing

Superconducting Nb thin films have recently attracted significant attention due to their utility for quantum information technologies. In the processing of Nb thin films, fluoride-based chemical etchants are commonly used to remove surface oxides that are known to affect superconducting quantum devices adversely. However, these same etchants can also introduce hydrogen to form Nb hydrides, potentially negatively impacting microwave loss performance. Here, we present comprehensive materials characterization of Nb hydrides formed in Nb thin films as a function of fluoride chemical treatments. In particular, secondary-ion mass spectrometry, X-ray scattering, and transmission electron microscopy reveal the spatial distribution and phase transformation of Nb hydrides. The rate of hydride formation is determined by the fluoride solution acidity and the etch rate of Nb2O5, which acts as a diffusion barrier for hydrogen into Nb. The resulting Nb hydrides are detrimental to Nb superconducting properties and lead to increased power-independent microwave loss in coplanar waveguide resonators. However, Nb hydrides do not correlate with two-level system loss or device aging mechanisms. Overall, this work provides insight into the formation of Nb hydrides and their role in microwave loss, thus guiding ongoing efforts to maximize coherence time in superconducting quantum devices.

cond-mat.mtrl-sci↗

arXiv2024

Systematic Improvements in Transmon Qubit Coherence Enabled by Niobium Surface Encapsulation

We present a novel transmon qubit fabrication technique that yields systematic improvements in T$_1$ relaxation times. We fabricate devices using an encapsulation strategy that involves passivating the surface of niobium and thereby preventing the formation of its lossy surface oxide. By maintaining the same superconducting metal and only varying the surface structure, this comparative investigation examining different capping materials, such as tantalum, aluminum, titanium nitride, and gold, and film substrates across different qubit foundries definitively demonstrates the detrimental impact that niobium oxides have on the coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T$_1$ relaxation times 2 to 5 times longer than baseline niobium qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 300 microseconds, with maximum values up to 600 microseconds, that represent the highest lifetimes to date for superconducting qubits prepared on both sapphire and silicon. Our comparative structural and chemical analysis suggests why amorphous niobium oxides may induce higher losses compared to other amorphous oxides. These results are in line with high-accuracy measurements of the niobium oxide loss tangent obtained with ultra-high Q superconducting radiofrequency (SRF) cavities. This new surface encapsulation strategy enables even further reduction of dielectric losses via passivation with ambient-stable materials, while preserving fabrication and scalable manufacturability thanks to the compatibility with silicon processes.

quant-ph↗

arXiv2023

Unlocking the Structural Mystery of Vaterite CaCO3

Calcium carbonate (CaCO3), the most abundant biogenic mineral on earth, plays a crucial role in various fields. Of the four polymorphs, calcite, aragonite, vaterite, and amorphous CaCO3, vaterite is the most enigmatic one due to an ongoing debate regarding its structure that has persisted for nearly a century. In this work, based on systematic transmission electron microscopy characterizations, elaborate crystallographic analysis and machine learning aided molecular dynamics simulations with ab initio accuracy, we reveal that vaterite can be regarded as a polytypic structure. The basic phase is a monoclinic lattice possessing pseudohexagonal symmetry. Direct imaging and atomic-scale simulations provide evidence that a single grain of vaterite can have three orientation variants. Additionally, we find that vaterite undergoes a second-order phase transition. These atomic scale insights provide a comprehensive understanding of the structure of vaterite and offer new perspectives on the biomineralization process of calcium carbonate.

cond-mat.mtrl-sci↗

arXiv2023

Defect contrast with 4D-STEM: Understanding crystalline order with virtual detectors and beam modification

Material properties strongly depend on the nature and concentration of defects. Characterizing these features may require nano- to atomic-scale resolution to establish structure-property relationships. 4D-STEM, a technique where diffraction patterns are acquired at a grid of points on the sample, provides a versatile method for highlighting defects. Computational analysis of the diffraction patterns with virtual detectors produces images that can map material properties. Here, using multislice simulations, we explore different virtual detectors that can be applied to the diffraction patterns that go beyond the binary response functions that are possible using ordinary STEM detectors. Using graphene and lead titanate as model systems, we investigate the application of virtual detectors to study local order and in particular defects. We find that using a small convergence angle with a rotationally varying detector most efficiently highlights defect signals. With experimental graphene data, we demonstrate the effectiveness of these detectors in characterizing atomic features, including vacancies, as suggested in simulations. Phase and amplitude modification of the electron beam provides another process handle to change image contrast in a 4D-STEM experiment. We demonstrate how tailored electron beams can enhance signals from short-range order and how a vortex beam can be used to characterize local symmetry.

cond-mat.mtrl-sci↗