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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measurement of the LCLS-II dark current using the LDMX Trigger Scintillator Prototype

The Light Dark Matter eXperiment (LDMX) is a proposed fixed-target missing momentum search for sub-GeV thermal relic dark matter. LDMX aims to probe thermal dark matter targets with 1016 electrons on target. Such an approach requires a high-repetition rate, low-current beam, with an average of one electron on target per event. These requirements are well-suited to the DArk Sector Experiments at LCLS-II (DASEL) facility, which will take advantage of the unused RF buckets between LCLS-II bunches to produce a well-defined low-current beam with a 26.9 ns bunch spacing. This document describes the results of a measurement of dark current in the Sector 30 transfer line (S30XL) of the LCLS-II beam, using a prototype of the LDMX trigger scintillator (TS) subsystem.

Berzin, Elizabeth [SLAC]↗
DOE OSTI2024

Operational Experience of a Cryomodule Test Stand for LCLS-II Cryomodules

CMTS1 (cryomodule test stand 1) at Fermilab was built to test cryomodules built for the LCLS-II beamline at SLAC and is currently testing cryomodules for LCLS-II-HE, the high energy upgrade to LCLS-II. The first cryomodule test was in 2016 and to date over 30 cryomodules have been tested here. This talk will highlight operational experience of the vacuum systems including insulating, coupler, and a low particulate beamline vacuum system. It will focus on the problems that have come up over the years, their solutions, and mitigations put in place to prevent further issues.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

HOM Spectra Measurements in 1.3 GHz Cavities for LCLS-II

Fermilab recently completed production and testing of 1.3 GHz cryomodules for the LCLS-II project. Each cryomodule consists of eight TESLA-shaped super-conducting elliptical cavities equipped with two High Order Mode (HOM) coupler ports. Measurement of the HOM spectrum is part of the incoming quality control of cavities at room temperature and the final qualification cold test of cryomodules at the Cryomodule Test Facility (CMTF). In this paper we describe the procedure for measuring the HOM spectrum along with further data processing. Finally, we present accumulated statistics of individual HOM frequencies and quality factors related to various cavity vendors and dis-cuss the possible contribution of HOMs to heat loads and beam dynamics.

Lunin, A.↗
DOE OSTI2024

Results of High Order Modes Spectra Measurements in 1.3 GHz Cavities for LCLS-II

Fermilab recently completed production and testing of 1.3 GHz cryomodules for the LCLS-II project. Each cryomodule consists of eight TESLA-shaped superconducting elliptical cavities equipped with two High Order Mode (HOM) coupler ports. Measurement of the HOM spectrum is part of the incoming quality control of cavities at room temperature and the final qualification cold test of cryomodules at the Cryomodule Test Facility (CMTF). In this paper we describe the procedure for measuring the HOM spectrum along with further data processing. Finally, we present accumulated statistics of individual HOM frequencies and quality factors related to various cavity vendors and discuss the possible contribution of HOMs to heat loads and beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Accelerating data acquisition with FPGA-based edge machine learning: a case study with LCLS-II

New scientific experiments and instruments generate vast amounts of data that need to be transferred for storage or further processing, often overwhelming traditional systems. Edge machine learning (EdgeML) addresses this challenge by integrating machine learning (ML) algorithms with edge computing, enabling real-time data processing directly at the point of data generation. EdgeML is particularly beneficial for environments where immediate decisions are required, or where bandwidth and storage are limited. In this paper, we demonstrate a high-speed configurable ML model in a fully customizable EdgeML system using a field programmable gate array (FPGA). Our demonstration focuses on an angular array of electron spectrometers, referred to as the ‘CookieBox,’ developed for the Linac Coherent Light Source II project. The EdgeML system captures 51.2 Gbps from a 6.4 GS s −1 analog to digital converter and is designed to integrate data pre-processing and ML inside an FPGA. Our implementation achieves an inference latency of 0.2 µs for the ML model, and a total latency of 0.4 µs for the complete EdgeML system, which includes pre-processing, data transmission, digitization, and ML inference. The modular design of the system allows it to be adapted for other instrumentation applications requiring low-latency data processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗
DOE OSTI2025

Numerical Analysis of High-Order Modes in SRF Resonators for Particle Accelerators

Over the past decades, superconducting technology has rapidly evolved towards high accelerating gradients and low surface resistance, making it possible to operate particle accelerators with high average beam currents and large duty factors. However, RF losses due to coherent excitation of the HOM become the limiting factor for these regimes. Unlike the cavity operating mode, which is tuned separately, the HOM parameters can significantly vary from one cavity to another due to finite mechanical tolerances during the manufacturing process. Thus, it is of utmost importance to know the HOM parameter spread in advance in order to predict unexpected cryogenic losses, overheating of beam line components and maintain stable beam dynamics. In this paper, we present a method for generating cavity geometry with an arbitrary spread of mechanical imperfections and numerically evaluating HOM statistics. Knowing the spread of HOM parameters, we calculated the probability of resonant HOM losses in SRF accelerating cavities used in CW beam current machines such as the PIP-II and LCLS-II linacs, as well as for the SRF crab-cavity for the ILC project. Finally, we present experimental results of HOM spectra measurements in hundreds of 1.3 GHz cavities installed in LCLS-II cryomodules. Studying the effects of HOM excitation results in specifications of the SRF cavity and cryomodule and can significantly impact the efficiency and reliability of the machine operation.

Lunin, Andrei [Fermilab] (ORCID:0000000290096792)↗
DOE OSTI2025

LLRF System Analysis for the Fermilab PIP-II Superconducting LINAC

PIP-II is a superconducting linac that is in the initial acceleration chain for the Fermilab accelerator complex. The RF system consists of a warm front-end with an RFQ and buncher cavities along with 25 superconducting cryo-modules comprised of cavities with five different acceleration \(β\). The LLRF system for the linac has to provide field and resonance control for a total of 125 RF cavities. Various components of the LLRF system have been tested with and without beam at the PIP-II test stands. The LLRF system design is derived from the LCLS-II project with its self-excited loop architecture used in the majority of the cryo-modules. The PIP-II beam loading at 2 mA is much higher than the LCLS-II linac. The control system architecture is analyzed and evaluated for the operational limits of feedback gains and their ability to meet the project regulation requirements for cavity field amplitude and phase regulation.

Varghese, P. [Fermilab] (ORCID:0009000925131983)↗
DOE OSTI2026

The chemRIXS Instrument for Solution-Phase Resonant Inelastic X-ray Scattering at the Linac Coherent Light Source

The chemRIXS instrument at the Linac Coherent Light Source (LCLS) offers new opportunities for studying solution-phase systems with time-resolved soft X-ray spectroscopic methods such as resonant inelastic X-ray scattering (RIXS) using the recently commissioned high-repetition-rate LCLS-II X-ray free electron laser. The orders-of-magnitude X-ray flux improvement provided by the superconducting accelerator, combined with corresponding advances in the optical laser system and the liquid jet recirculation system, enables studies on dilute systems with high signal-to-noise compared to what was possible with the LCLS-I copper accelerator. These capabilities open up time-resolved X-ray absorption spectroscopy and RIXS to entirely new classes of samples, as well as enabling the development of new soft X-ray spectroscopic methods on liquid samples. An overview of the beamline components and the first LCLS-II commissioning results are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A hybrid neural architecture: Online attosecond x-ray characterization

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

Accelerator Physics (physics.acc-ph)↗
DOE OSTI2025

Twinac: initiation of a community-driven accelerator digital twin framework

We present the initiation of a community-driven framework for the integration of accelerator digital twins into control systems: Twinac. Few facilities have fully integrated accelerator digital twins like at Cornell’s CHESS. Many facilities have active research to employ surrogate models to aid in operational decisions like at Argonne’s ALS, MSU’s FRIB, SLAC’s LCLS-II, and Fermilab’s FAST/IOTA, PIP-II, and main complex. To lower the barrier to entry for all accelerator facilities to build and benefit from a digital twin of their own accelerators, we propose the following software framework. Twinac will provide the capability to compose one’s own digital twin using reusable components engineered at other facilities. With this model in place, Twinac will also support tools for (1) predictive maintenance systems; (2) discovery of correlated but uncontrolled environmental factors, like seasonal temperature variations causing performance changes on power supplies, magnets, etc.; and (3) prototyping and updating sophisticated optimization and controls algorithms. The Twinac framework will enable sharing and simplified deployment of modeled components and control algorithms at all facilities. With an inter-facility team to build and support the Twinac framework, it will be easy to publish and try out the latest advancements at one’s own facility.

Miceli, Tia [Fermilab]↗
DOE OSTI2025

Xopt and Badger: a machine learning ecosystem for real-time accelerator control and optimization

Machine learning (ML)-based black-box optimization algorithms have demonstrated significant improvements in accelerator optimization speed, often by orders of magnitude. However, deploying these algorithms in real-time facility control remains challenging due to the specialized expertise and infrastructure required. To bridge this gap, we introduce the Xopt ecosystem, a versatile suite of tools designed to make advanced ML-based optimization accessible to the broader accelerator community. This ecosystem includes Xopt, a modular Python framework that facilitates the integration of ML-based optimization algorithms with arbitrary control problems, and Badger, a graphical user interface built on top of Xopt, which enables seamless deployment of ML algorithms in real-time control systems. The Xopt ecosystem has been successfully applied towards solving challenging real-time control problems at leading international accelerator facilities, including SLAC, LBNL, Argonne, Fermilab, BNL, DESY, and ESRF, demonstrating its effectiveness in real-world optimization tasks. In this presentation, we provide an overview of Xopt’s capabilities and illustrate its impact through case studies from SLAC accelerator facilities including LCLS, LCLS-II, and FACET-II.

Roussel, Ryan [SLAC]↗
DOE OSTI2024

Results from extended range SRF cavity tuner tests for LCLS-II-HE

The LCLS-II HE superconducting linac can produce multi-energy beams by supporting multiple undulator lines simultaneously. This could be achieved by using the cavity SRF tuner in the off-frequency detune mode. This off-frequency operation method was tested in 8 cryomodules at Fermilab at 2 K. In all the tests the tuners successfully achieved a frequency shift of -565±80 kHz from the 1.3 GHz value. This study discusses the cavity frequency during each stage of assembly from the cryomodule string to when they are finally tested at 2 K. Monitoring the cavity frequency from this initial stage contributed in reaching this large frequency shift. The specific procedures of tuner setting during assembly will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Experience of developing highly reliable Tuner components (piezo actuators and cold stepper motor actuators) for SRF Linac

The resonance control team at FNAL has led the design of the LCLS-II SRF Linac SRF cavity tuner subsystem. The Linac is expected to operate for over 30 years, and the longevity of the tuner is crucial to the overall reliability of the Linac. When the tuner's design was started, there were no active actuators (stepper and piezo) that could meet the longevity requirements of the Linac. The FNAL resonance control team, in collaboration with industrial partners (Phytron and PI), has developed actuators that have been shown to withstand a cryogenic and insulating vacuum environment for over 100 years in accelerated lifetime tests. Details of actuators design and longevity testing will be presented. Now, practically all (small and large) SRF systems that are under construction around the world are using actuators developed at FNAL. A review of possible actuators improvement will be presented.

Pischalnikov, Yuriy [Fermilab]↗
DOE OSTI2026

Cavity Preparation and Assembly: Challenges and Future R&D Directions

This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.

Wu, Genfa [Fermilab]↗
DOE OSTI2026

Cavity Preparation and Assembly: Challenges and Future R&D Directions

This presentation described the state of the art in cavity string assembly for the LCLS-II, HE, and PIP-II projects, as well as cavity performance statistics. The presentation also described the knowledge gap, opportunities for improvement, and future R&D recommendations.

Wu, Genfa [Fermilab]↗
DOE OSTI2025

LDMX -- The Light Dark Matter eXperiment

LDMX, The Light Dark Matter eXperiment, is a missing momentum search for hidden sector dark matter in the MeV to GeV range. It will be located at SLAC in End Station A, and will employ an 8 GeV electron beam parasitically derived from the SLAC LCLS-II accelerator. LDMX promises to expand the experimental sensitivity of these searches by between one and two orders of magnitude depending on the model. It also has sensitivity in visible ALP searches as well as providing unique data on electron-nucleon interactions.

Appert, Stephen [Caltech]↗