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DOE OSTI2025

Long Island Steatite Sourcing from Rhode Island Quarries During the Late Holocene Era

This study aimed to investigate the possible sourcing of Long Island steatite artifacts from quarries in Rhode Island. Seven steatite samples from archeological sites on Long Island including Nassau County, Suffolk County (North Fork and South Fork) and Shelter Island were compared to two Rhode Island quarry sample putative sources using X-ray fluorescence (XRF) microscopy at the Submicron Resolution X-ray spectroscopy (SRX) beamline of the National Synchrotron Light Source II at Brookhaven National Laboratory. The site-derived steatite samples displayed numerous similarities in elemental composition compared to the two Rhode Island quarries, Oaklawn and Ochee Springs. This study provides new evidence to support the possible sourcing of Long Island steatite from Rhode Island during the late Holocene era.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Characterization of Gas Bremsstrahlung sources at the Electron-Ion Collider

This report estimates the potential impact of Gas Bremsstrahlung, generated as the electron beam traverses the straight sections of the storage ring and impinges onto selected locations of the Electron-Ion Collider. The source terms were calculated for routine operation scenarios at three different energies: 5, 10 and 18 GeV, using the FLUKA Monte Carlo particle transport and interaction code. The source term’s power distributions were validated and compared with the Gas Bremsstrahlung produced in the long straight sections of the National Synchrotron Light Source II storage ring.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Macromolecular crystallography and biology at the Linac Coherent Light Source

The Linac Coherent Light Source (LCLS) has significantly impacted the field of biology by providing advanced capabilities for probing the structure and dynamics of biological molecules with high precision. The ultrashort coherent X-ray pulses from the LCLS have enabled ultrafast, time-resolved, serial femtosecond crystallography that is inaccessible at conventional synchrotron light sources. Since the facility's founding, scientists have captured detailed insights into biological processes at atomic resolution and fundamental timescales. The ability to observe these processes in real time and under conditions closely resembling their natural state is transforming our approach to studying biochemical mechanisms and developing new medical and energy applications. This work recounts some of the history of the LCLS, advances in biological research enabled by the LCLS, key biological areas that have been impacted and how the LCLS has helped to unravel complex biological phenomena in these fields.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

3D small-gain formula allowing strong focusing and harmonic lasing for a ring-based x-ray free electron laser oscillator

We present a detailed derivation of a formula for the small-gain calculation for an x-ray free electron laser oscillator (XFELO) based on a medium-energy (3–4 GeV) storage ring. We found harmonic lasing and strong focusing are essential for this beam energy range. Taking the small-signal low-gain formula developed by Kim and his colleagues, we modified it in such a way that the gain can be calculated without the “no focusing approximation,” and a strong focusing can be applied, as well as harmonic lasing. In this formula, the gain is represented as a product of two factors with one of them depending only on the harmonic number, undulator period, and gap. Using this factor, we show that it is favorable to use harmonic lasing to achieve hard x-ray FEL working in the small-signal low-gain regime with the medium-energy electron beam. Our formula also allows FEL optimization by varying the vertical gradient of the undulator, the vertical dispersion, and the horizontal and vertical focusing, independently. As an example, we applied this formula to study the feasibility of an XFELO option for the National Synchrotron Light Source II (NSLS-II) upgrade. Since a quite high peak current is required for the FEL, collective effects of beam dynamics in medium-energy synchrotrons significantly affect the electron beam parameters. We carried out a multiparameter optimization taking collective effects into account. Note, even though our example is for a ring-based XFELO at 3 to 4 GeV, the formula and, in particular, the approach developed here may be applied to other types of FELs. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

DOE OSTI2024

A general Bayesian algorithm for the autonomous alignment of beamlines

Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Advanced Characterization in Advanced Manufacturing Workshop

The Advanced Manufacturing (AM) Work shop successfully convened experts from government, academia, and industry to address pressing scientific challenges and strengthen the AM user community. The workshop was held at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory during the National Synchrotron Light Source II (NSLS-II) and Center for Functional Nanomaterials (CFN) Users’ Meeting. Participation included researchers from Stony Brook University, Massachusetts Institute of Technology, Yale University, Harvard University, Columbia University, and several other institutions across the United States and the world. In conclusion, the program featured three complementary components—oral presentations, a facility tour, and a brainstorming session— that together fostered collaboration and high lighted the transformative role of synchrotron based characterization in AM.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Application and performance of the novel Elcomat 5000 autocollimator in slope-measuring profilometry of beamline optics

Autocollimators are used in profilometers for the precise form measurement of beam-shaping optics for synchrotron light sources and x-ray free-electron lasers. This application requires using an aperture stop, typically 2.5 mm in diameter, which limits the footprint of the autocollimator’s measuring beam on the optics to achieve a sufficiently high lateral resolution. Central to the development of profilometry has been the availability of commercial autocollimators, such as the Elcomat 3000 from Möller–Wedel Optical. Although autocollimators are generally not designed for use with small apertures, this device has proven capable and has become the de facto standard. Now that it has been replaced by the Elcomat 5000, we evaluate the performance of several autocollimators of this type at small apertures, including the characterization of instrument transfer functions with a chirped height profile. We demonstrate that the Elcomat 5000 is capable of repeatable angle measurements with a standard deviation of 0.014 arcsec at an aperture diameter of 1.6 mm, whereas the Elcomat 3000 achieves 0.03 arcsec at 2.5 mm, comparing models with modified reticle designs. Here, we also investigate the influence of optical aberrations of the autocollimator’s objective and their changes with the path length to the surface under test. We characterize the sensitivity of the angle measurement to changes in environmental parameters, in particular, barometric pressure. These efforts are aimed at approaching fundamental limits in the characterization of the shape of optical surfaces with autocollimator-based profilometers so that these are ready for characterizing the next generation of synchrotron and XFEL beamline optics.

angle metrology↗

DOE OSTI2026

Adaptively coupled phase retrieval in multi-peak Bragg coherent diffraction imaging

Recent advances in Bragg coherent diffraction imaging (BCDI) experimental techniques permit routine measurement of multiple Bragg peaks from a single crystalline grain. The resulting images contain the full lattice distortion vector field which can be differentiated to provide lattice strain and rotation. With the advent of fourth-generation synchrotron light sources, such multi-peak datasets are produced at high rates, facilitating the need for rapid phase retrieval of the multiple peaks and subsequent image analysis. Here we describe and demonstrate a new implementation of a coupled phase retrieval technique for multi-peak BCDI which simultaneously treats each Bragg peak of the dataset and produces a three-dimensional image of the crystal's morphology and lattice distortion field. In addition, this method uses the redundant information contained in the various Bragg diffraction patterns to detect and suppress spurious signal appearing on the detector in a subset of the measurements. Compared with manual data editing, adaptive coupling produces a more consistent phase profile in reciprocal space and sharper surfaces in direct space, with no significant difference in computational cost. These improvements reduce the need for manual preprocessing and enable robust high-throughput analysis of multi-peak BCDI data, supporting near-real-time strain microscopy at modern synchrotron facilities.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Adaptive X-ray imaging with reinforcement learning

X-ray imaging is a powerful technique to scan samples in a variety of contexts including biological, environmental and materials science, but commonly requires a synchrotron light source to produce X-rays at sufficient intensity. As these facilities are expensive to operate, the available beam time is limited and always in high demand. Particularly if the illuminated samples are sparse, standard raster scanning methods can be time-consuming, with a majority of that time being spent on areas of the image that carry little information. To increase the efficiency and maximize the information gain for a given time budget, we split the scanning process into a series of steps where previous measurements are used to inform the decision making and adapt the exposure distribution at later stages of the sequence. We formulate this task as a reinforcement learning problem where the goal is to produce a sequence of exposure maps that maximize a predefined scalar metric. We demonstrate the potential of this approach in simulations where the adaptive illumination can accelerate the measurement process by up to an order of magnitude compared with standard raster scanning. Finally, we present the first results from deploying the trained agents on an X-ray fluorescence beamline at the Stanford Synchrotron Radiation Lightsource.

Reinforcement Learning↗

DOE OSTI2026

High-resolution in-beam video rate imaging with the ClearXCam for synchrotron beamlines

The ClearXCam detector is a new video rate imaging in-beam monitor based on a diamond sensor. Imaging with 2304 effective pixels is achieved by sequentially biasing one of 48 metal stripes on one side of a diamond sensor, while reading out the current from 48 stripes on the other side of the sensor. This system was characterized for real-time X-ray beam diagnostics at synchrotron beamline 17-BM at the National Synchrotron Light Source II. Significant results include: detection of in-beam structure via the imaging mode, beam focusing in one minute with real-time imaging feedback during a focusing event, linearity over five orders of magnitude, validation of a fast mode operating at 100 Hz, and sub-micron beam-positioning resolution. The system is now available commercially.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Recent progress in high-temperature superconducting undulators

Considerable effort has been devoted to the development of superconducting undulators (SCUs) intended for particle accelerator-based light sources, including synchrotrons and free electron laser (FEL) facilities. Recently, a high-temperature superconducting (HTS) undulator prototype, consisting of staggered-array Re-Ba-Cu-O bulks, achieved an on-axis sinusoidal magnetic field profile with a peak amplitude B$_0$ of 2.1 T and a period length of 10 mm, resulting in a deflection parameter K = 1.96. Such a short period HTS undulator not only enables the generation of higher-energy photons, but also supports the construction of economically feasible and compact FELs with shorter linear accelerators (LINACs). This article provides a comprehensive review of recent advances in the staggered-array bulk HTS undulator as well as other types of HTS undulators. Furthermore, it offers insights into the development of engineering HTS undulator prototypes designed for deployment in synchrotron and free electron laser (FEL) facilities. We conclude by discussing opportunities for and the challenges facing the use of HTS undulators in practical applications.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗

DOE OSTI2024

Reinforcement induced microcracking during the conversion of polymer-derived ceramics

This study investigates the role of discontinuous reinforcement on the microcracking of a preceramic polymer matrix during polymer to ceramic conversion. The material system comprised a carbosilane-based, preceramic polymer reinforced with mullite particles. The preceramic resin slurry was formulated for photopolymerization on a digital light projection 3D printer. Micro X-ray computed tomography, using a synchrotron light source, monitored a printed composite part during pyrolysis. The conversion of the carbosilane matrix into Si(O)C generated microcracks in the matrix that radially extended from particles. The likelihood of microcrack formation positively correlated with particle size. The largest particles (>10 4 µm 3 volume or >60 µm side length) always abutted microcracks, while the matrix surrounding smaller particles (<5 µm) was free of microcracks. Numerical calculations showed the particles resist the shrinking matrix during its conversion. This created tensile stresses within the matrix. The driving force for microcrack growth was also analyzed with regard to the influence of matrix material parameters, particle form-factor and crack length. These results reveal the need to consider the form factor of discontinuous reinforcements, with regard to the material properties of the polymer-derived ceramic, in order to reduce or eliminate defects in the final part.

36 MATERIALS SCIENCE↗

DOE OSTI2025

JuTrack: A Julia package for auto-differentiable accelerator modeling and particle tracking

Efficient accelerator modeling and particle tracking are key for the design and configuration of modern particle accelerators. In this work, we present JuTrack, a nested accelerator modeling package developed in the Julia programming language and enhanced with compiler-level automatic differentiation (AD). With the aid of AD, JuTrack enables rapid derivative calculations in accelerator modeling, facilitating sensitivity analyses and optimization tasks. Here we demonstrate the effectiveness of AD-derived derivatives through several practical applications, including sensitivity analysis of space-charge-induced emittance growth, nonlinear beam dynamics analysis for a synchrotron light source, and lattice parameter tuning of the future Electron-Ion Collider (EIC). Through the incorporation of automatic differentiation, this package opens up new possibilities for accelerator physicists in beam physics studies and accelerator design optimization.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Dedicated beam position monitor pair for model-independent lattice characterization at NSLS-II

This paper reports recent lattice characterization results obtained at the National Synchrotron Light Source II (NSLS-II) storage ring, conducted without reliance on a lattice model. A pair of beam position monitors (BPMs) with bunch-by-bunch (B$\times$B) resolution, were recently installed in a section of the storage ring free of magnetic fields. The new BPM pair measured the beam, or bunch’s transverse Poincaré map precisely after the beam was excited. Linear one-turn-matrices (OTM) were then derived, and from these, the 4-dimensional coupled Twiss parameters were extracted at the locations of the BPM pair. By normalizing beam oscillation amplitudes with the Twiss parameters, the global action-variables were obtained. Additionally, these action-variables facilitated the measurement of the local Twiss parameters observed by other BPMs independent on lattice model. This method is general, and particularly useful in certain scenarios such as a round beam mode in a diffraction-limited light source ring. We applied it to assess both weakly and strongly coupled lattices at the NSLS-II ring. Through analysis of the strongly coupled lattice, the quadrupole tilt errors were estimated to be less than 400 μrad. Utilizing the BPMs’ B$\times$B resolution, for the first time we observed the variations of the linear lattice along a long bunch-train.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Elucidating the Origins of High Capacity in Iron-Based Conversion Materials: Benefit of Complementary Advanced Characterization toward Mechanistic Understanding

Lithium-ion batteries are recognized as an important electrochemical energy storage technology due to their superior volumetric and gravimetric energy densities. Graphite is widely used as the negative electrode, and its adoption enabled much of the modern portable electronics technology landscape. However, developing markets, such as electric vehicles and grid-scale storage, have increased demands, including higher energy content and a diverse materials supply chain. Alternatives that provide the opportunity to increase capacity and address supply chain concerns are of interest. Understanding the fundamental mechanisms that govern battery function is crucial to driving further improvements in the field. Advanced characterization techniques, such as those enabled by synchrotron light sources and high-resolution electron microscopes, that can uncover these mechanisms have become a necessity for elucidating structural evolution upon electrochemical conversion at the nano- to mesoscales. Performing these experiments with relevant electrochemistry using in situ and operando experiments imparts the ability to identify critical reaction pathways and capture intermediate (dis)charge products not discernible by traditional experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗