arXiv subjects

Amy J. Clarke

Publications and source records attributed to Amy J. Clarke.

5 recordsLinked to original sources

arXiv2026

PiMiX 2.02: Toward AI-Driven Data Fusion in Radiographic Imaging and Tomography

PiMiX (Physics-informed Meta-instrument for eXperiments) was introduced for multi-instrument, multi-experiment, and simulation-experiment data fusion in radiographic imaging and tomography (RadIT). Here we present PiMiX 2.02 as an evolving AI-enhanced cyber-physical meta-instrument integrating imaging sensors, near-sensor computing, data fusion, physics-informed inference, and human-supervised AI workflows across X-ray, neutron, and other modalities. Demonstrated capabilities include multimodal CMOS radiation imaging, simulation-assisted sub-pixel neutron localization, and edge-deployed optical-neural-network (ONN) inference; GPU and ONN implementations achieved greater than 96% precision for neutron-event detection with sub-micron localization. A further advance is human-in-the-loop agentic-AI co-analysis of X-ray and neutron images from inertial-confinement-fusion experiments. Beyond conventional preprocessing, the workflow generates competing feature hypotheses, ranks contours using physics-informed evidence, estimates confidence, and presents alternatives for human review. The same architecture adapts to different physics: X-ray analysis emphasizes dark, nonuniform ring structures using deformable closed paths and multi-scale evidence, whereas neutron analysis targets bright emission envelopes using fractional-emission levels, intensity gradients, and cross-filter persistence. We also highlight automated comparison of an as-designed stereolithography model with an X-ray CT reconstruction of an additively manufactured metal lattice. Together, these examples show progression from AI assistance in specific processing tasks to multi-task, multi-domain scientific co-analysis. PiMiX 2.0 further provides a pathway toward PRISM, a RadIT scientific foundation model, and tighter integration of diagnostics, digital representations, inference, and experimental control.

eess.IV↗

arXiv2026

PiMiX 2.0: AI-enhanced Data Fusion for Radiographic Imaging and Tomography

Extending earlier work in Physics-informed Meta-instrument for eXperiments (PiMiX) [1], PiMiX~2.0 is an artificial-intelligence (AI)-enhanced data-fusion and analysis framework that integrates multi-experiment multi-modal radiographic imaging and tomography (RadIT) with physics-informed reasoning and agentic AI workflows. The framework supports automated data ingestion, multimodal image processing from one or more experiments, three-dimensional (3D) and time-resolved three-dimensional (4D) reconstruction, and physics-aware interpretation of experimental observations. The PiMiX agents are designed for deployment on desktop and laptop systems commonly used in experimental workflows, while remaining scalable to high-performance computing environments for computationally intensive tasks. By coupling RadIT instrumentation and measurements with geometry, physics, computation, and statistical inference, PiMiX 2.0 aims to accelerate RadIT data processing, knowledge extraction, improve reproducibility, and enable more integrated analysis and workflows in high-temperature plasmas, nuclear fusion, advanced manufacturing, other static and dynamic experiments.

physics.ins-det↗

arXiv2026

Microstructure evolution during rapid solidification of hypoeutectic Al-Ag alloys near absolute stability

Microsegregation-free microstructures can form by solidifying at velocities beyond the absolute stability limit ($V_{\text{abs}}$), where solute partitioning is suppressed by a stable, planar solid-liquid interface. Producing such microstructures is of considerable practical interest; however, $V_{\text{abs}}$ typically exceeds the ${\sim}1$ m/s growth rates encountered in additive manufacturing (AM). Here we demonstrate the absolute stability limit can be reached in sufficiently concentrated hypoeutectic Al-Ag alloys at growth rates well below the 1~m/s typically encountered in additive manufacturing. Dynamic Transmission Electron Microscopy (DTEM) of rapid solidification front evolution -- following laser spot melting of Al-Ag thin films -- combined with postmortem microstructural characterization, enables detailed quantitative comparison with both phase-field (PF) simulations and a sharp-interface linear stability analysis that uses a non-equilibrium, velocity-dependent phase diagram extracted from the PF model. The analysis predicts that $V_{\text{abs}}$ follows a trend similar to that of the miscibility gap, first increasing and then decreasing with Ag concentration. Predicted values of $V_{\text{abs}}$ are in good quantitative agreement with PF simulations over the entire hypoeutectic concentration range and with experiments for three concentrated alloys. These results inform the prediction and control of microstructural development in concentrated alloys near the absolute stability limit under AM conditions.

cond-mat.mtrl-sci↗

arXiv2025

Calibrating a Finite-strain Phase-field Model of Fracture for Bonded Granular Materials with Uncertainty Quantification

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, GPU-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives, though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.

physics.comp-ph↗

arXiv2023

Microstructural Pattern Formation during Far-from-Equilibrium Alloy Solidification

We introduce a new phase-field formulation of rapid alloy solidification that quantitatively incorporates nonequilibrium effects at the solid-liquid interface over a very wide range of interface velocities. Simulations identify a new dynamical instability of dendrite tip growth driven by solute trapping at velocities approaching the absolute stability limit. They also reproduce the formation of the widely observed banded microstructures, revealing how this instability triggers transitions between dendritic and microsegregation-free solidification. Predicted band spacings agree quantitatively with observations in rapidly solidified Al-Cu thin films.

cond-mat.mtrl-sci↗