arXiv subjects

Thomas A. Caswell

Publications and source records attributed to Thomas A. Caswell.

6 recordsLinked to original sources

arXiv2026

PowderLine: a programmatic powder diffraction analysis application

Whole-pattern fitting methods, such as Rietveld refinement, excel at extracting detailed structural, chemical, and microstructural information from powder diffraction data. Obtaining reliable results requires both considerable expertise and software-specific knowledge, and applying these methods at scale typically relies on custom scripts written for each application. High-throughput experiments and autonomous self-driving laboratories increasingly utilize powder diffraction analysis to proceed programmatically and to return structured, machine-readable results. Here, we introduce PowderLine, a Python application that encapsulates a complete refinement into a single declarative recipe, validates that recipe against a versioned schema, and executes it through refinement software to return structured results. The refinement recipe is an all-inclusive, machine-readable and -writable description of either Rietveld or single peak analysis that users, scripts, and automated agents can specify and run in the same way. As a result of PowderLine's composability, it naturally fits into interactive, scripted, and autonomous workflows alike.

cond-mat.mtrl-sci↗

arXiv2025

A modular framework for collaborative human-AI, multi-modal and multi-beamline synchrotron experiments

High-throughput materials discovery and studies of complex functional materials increasingly rely on multi-modal characterization performed at synchrotron light sources. However, measurements are typically done with no use of data until after an experiment, neglecting opportunities for data-driven insights to guide measurements. We developed a modular, open-source framework that incorporates artificial intelligence within the Bluesky control and data streaming infrastructure at NSLS-II, enabling real-time orchestration of multi-beamline, multi-modal experiments. AI agents perform on-the-fly reduction, clustering, Gaussian process modelling, and Bayesian optimization driven data acquisition, while users monitor agent behavior and visualize results live. Combinatorial libraries of the ternary Al-Ni-Pt system were spatially mapped by X-ray diffraction and X-ray absorption fine structure measurements at the PDF and BMM beamlines, respectively. Dynamic switching between AI-driven and conventional grid mapping strategies was achieved, demonstrating the flexible workflows possible through this framework. A digital twin constructed from a simulated Al-Li-Fe oxide dataset shows that AI-driven mapping strategies outperform conventional mapping as well as random sampling by prioritizing measurements that better resolve both phase boundaries and localized minority phases. This framework supports plug-and-play capabilities, and establishes a foundation for routine multi-modal, AI-assisted large-scale user-facility operations.

physics.app-ph↗

arXiv2024

Quantum Imaging with X-rays

Quantum imaging encompasses a broad range of methods that exploit the quantum properties of light to capture information about an object. One such approach involves using a two-photon quantum state, where only one photon interacts with the object being imaged while its entangled partner carries spatial or temporal information. To implement this technique, it is necessary to generate specific quantum states of light and detect photons at the single-photon level. While this method has been successfully demonstrated in the visible electromagnetic spectrum, extending it to X-rays has faced significant challenges due to the difficulties in producing a sufficient rate of X-ray photon pairs and detecting them with adequate resolution. Here, we demonstrate record high rates of correlated X-ray photon pairs produced via a spontaneous parametric down-conversion process and we employ these photons to perform quantum correlation imaging of several objects, including a biological sample (E. cardamomum seedpod). Notably, we report an unprecedented detection rate of about 6,300 pairs per hour and the observation of energy anti-correlation for the X-ray photon pairs. We also present a detailed analysis of the properties of the down-converted X-ray photons, as well as a comprehensive study of the correlation imaging formation, including a study of distortions and corrections. These results mark a substantial advancement in X-ray quantum imaging, expanding the possibilities of X-ray quantum optical technologies, and illustrating the pathway towards enhancing biological imaging with reduced radiation doses.

quant-ph↗

arXiv2023

Self-driving Multimodal Studies at User Facilities

Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a single sample library at distant instruments, driven by a concert of distributed agents that use analysis from each modality to inform the direction of the other in real time. Powered by the Bluesky project at the National Synchrotron Light Source II, this experiment is a world's first for beamline science, and provides a blueprint for future approaches to multimodal and multifidelity experiments at user facilities.

cond-mat.mtrl-sci↗

arXiv2014

Dynamics of Vapor Layer Under a Leidenfrost Drop

In the Leidenfrost effect a small drop of fluid is levitated above a sufficiently hot surface, on a persistent vapor layer generated by evaporation from the drop. The vapor layer thermally insulates the drop from the surface leading to extraordinarily long drop lifetimes. The top-view shape of the levitated drops can exhibit persistent star-like vibrations. I extend recent work [Burton et al. PRL 2012] to study the bottom surface of the drop using interference-imaging. In this work I use a high-speed camera and automated image analysis to image, locate and classify the interference fringes. From the interference fringes I reconstruct the shape and height profile of the rim where the drop is closest to the surface. I measure the drop-size dependence of the planar vibrational mode frequencies, which agree well with previous work. I observe a distinct breathing mode in the average radius of the drop, the frequency of which scales differently with drop size than the other modes. This breathing mode can be tightly coupled to a vertical motion of the drop. I further observe a qualitative difference in the structure and dynamics of the vertical profile of the rim between large and small drops.

physics.flu-dyn↗

arXiv2012

Observation and Characterization of the Vestige of the Jamming Transition in a Thermal 3D System

We study the dependence of the pair-correlation function, $g(r)$, and particle mobility on packing fraction in a dense three-dimensional packing of soft colloids made of poly N-isopropyl acrylamide (pNIPAM), a thermo-sensitive gel. We find that $g(r)$ for our samples is qualitatively like that of a liquid at all packing fractions. There is a peak in $g_{1}$, the height of the first peak of $g(r)$, as a function of packing fraction. This peak is identified as the thermal remnant of the T=0 divergence found at the jamming transition in simulations of soft frictionless spheres at zero-temperature. Near where there is a peak in $g_{1}$ the particles become arrested on the time scale of the experiment.

cond-mat.soft↗