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At least 667 records · Page 37

Noise in Intense Electron Bunches (Final Technical Report)

The goal of this project is to investigate density fluctuations in electron bunches. Noise and density fluctuations in relativistic electron bunches, accelerated in a linac, are of critical importance to various Coherent Electron Cooling (CEC) concepts as well as to free-electron lasers (FELs). For CEC, the beam noise results in additional diffusion that counteracts cooling; and if this noise is not controlled at sufficiently low level, the noise heating effects can overcome cooling. There have been several proposals in the past to suppress the noise in the beam in the frequency range of interest in order to optimize the cooling effects. In SASE FELs a microwave instability starts from the initial noise in the beam and eventually leads to the beam microbunching yielding coherent radiation, and the initial noise in the FEL bandwidth plays a useful role. In seeded FELs, in contrast, such noise interferes with the seed signal, so that reducing noise at the initial seed wavelength would lower the seed laser power requirement. Our major goals were (1) to measure the electron beam density noise level in a 0.5 – 10 um wavelength range, (2) to predict the beam noise level in order to compare with the measurements, and (3) as a stretch goal, to find mechanisms that affect the beam noise to control its level in a predictable manner.

43 PARTICLE ACCELERATORS↗

Realizing Steady-State Microbunching with Optical Stochastic Crystallization

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗

Steady-State Microbunching using Optical Stochastic Cooling

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations demonstrating the beam dynamics will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗

High Intensity Gamma-Ray Source(HIγS) Radiographic Experiments

High Intensity Gamma-ray Source (HIGS) is a Free-Electron Laser (FEL) based Compton back-scattering γ-ray source. The HIGS facility is located on the campus of Duke University and operated by Triangle Universities Nuclear Laboratory (TUNL).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Probing molecular wavepacket evolution using multidimensional coherent spectroscopy (Final Report)

The goal of this project was to develop and demonstrate multidimensional coherent spectroscopy (MDCS) techniques to fully map wave-packet dynamics in simple molecules. MDCS correlates excitation and emis sion frequencies, enabling continuous tracking of wave-packet evolution even when multiple wave-packets evolve simultaneously. The initial experiments were to be performed using the MDCS apparatus in the PI’s laboratory to record the evolution of the wave-packet’s energy in molecular iodine. A longer-term goal was to develop a version compatible with using an X-ray Free Electron Laser (XFEL) as a probe, which would allow the evolution of the internuclear distance of the wave-packet—not just its energy—to be determined.

74 ATOMIC AND MOLECULAR PHYSICS↗

Characterizing sample degradation from synchrotron based X-ray measurements of ultra-thin exfoliated flakes

It is undeniable that novel 2D devices and heterostructures will have a lasting impact on the advancement of future technologies. However, the inherent instability of many exfoliated van der Waals (vdW) materials is a well-known hurdle yet to be overcome. Thus, the sustained interest in exfoliated vdW materials underscores the importance of understanding the mechanisms of sample degradation to establish proactive protective measures. Here, the impact of prolonged synchrotron-based X-ray beam exposure on exfoliated flakes of two contemporary vdW materials, NiPS 3 and α-RuCl 3 , is explored using resonant inelastic X-ray scattering (RIXS) and total fluorescence yield X-ray absorption spectroscopy (XAS). In NiPS 3 , the resulting RIXS and XAS spectra show a suppression, then vanishing, of NiS 6 multiplet excitations coupled with an upward shift of the peak energy of the XAS as a function of X-ray dose. In α-RuCl 3 , the signs of beam damage from the RIXS spectra are less evident. However, the post-experiment characterization of both materials using Raman spectroscopy exhibits signals of an amorphous and disordered system compared to pristine flakes; in addition, energy-dispersive X-ray spectroscopy of NiPS 3 shows evidence of ligand vacancies. As synchrotron radiation is fast becoming a required probe to study 2D vdW materials, these findings lay the groundwork for the development of future protective measures for synchrotron-based prolonged X-ray beam exposure, as well as for X-ray free electron laser.

2D magnetism↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗

Microfluidic liquid sheets as large-area targets for high repetition XFELs

The high intensity of X-ray free electron lasers (XFELs) can damage solution-phase samples on every scale, ranging from the molecular or electronic structure of a sample to the macroscopic structure of a liquid microjet. By using a large surface area liquid sheet microjet as a sample target instead of a standard cylindrical microjet, the incident X-ray spot size can be increased such that the incident intensity falls below the damage threshold. This capability is becoming particularly important for high repetition rate XFELs, where destroying a target with each pulse would require prohibitively large volumes of sample. We present here a study of microfluidic liquid sheet dimensions as a function of liquid flow rate. Sheet lengths, widths and thickness gradients are shown for three styles of nozzles fabricated from isotropically etched glass. In-vacuum operation and sample recirculation using these nozzles is demonstrated. The effects of intense XFEL pulses on the structure of a liquid sheet are also briefly examined.

47 OTHER INSTRUMENTATION↗

Thin-Entrance Window Process for Soft X-Ray Sensors

New free electron lasers, such as SLAC’s LCLS-II, will provide unique scientific imaging opportunities. In order to fully utilize these facilities, we need to develop detectors with shallow entrance windows that will enable detection of soft x-rays from 250 eV to 1.5 KeV. Achieving adequately shallow entrance windows is challenging because the high temperature anneal needed to activate the dopant also drives the dopant profile deeper, growing the region that is insensitive to soft x-rays. A new microwave annealing technology provides an efficient way to achieve shallow entrance windows in fully depleted high-resistivity silicon sensors. The microwave anneal technique can activate dopants at low substrate temperature, with minimal dopant diffusion, and can be used to fabricate both n-type and p-type entrance windows. SRP and SIMS measurements were used to verify dopant activation with negligible dopant diffusion. We then applied the microwave anneal process to a planar sensor wafer, using the new process to create the backside diode contact. Electrical test of the resulting sensors shows good reverse bias characteristics. The sensors have been bump-bonded to a read-out ASIC and used successfully to measure an Fe-55 x-ray spectrum. Process and device simulations were performed to characterize the quantum efficiency of the entrance window for soft x-rays. This technique is useful for other sensor applications requiring a shallow entrance window, including detectors for UV photons, low energy ions and low energy electrons.

47 OTHER INSTRUMENTATION↗

Superconducting radio frequency photoinjectors for CW-XFEL

A dependable and consistent electron source is a crucial requirement for the achievement of high-power free electron lasers (FELs). Over the past two decades, it has been demonstrated that photoinjectors based on SRF technology (SRF guns) are suitable for continuous wave (CW) beam generation. SRF guns possess both the high accelerating field gradients of normal conducting RF photoinjectors and the low power dissipation thanks to mature SRF cavity technology, and therefore have the potential to provide the high-brightness, high-current beams required for CW-XFELs. After the demonstration of the first SRF gun in Dresden-Rossendorf, several SRF gun programs based on different approaches have achieved promising progress and even succeeded in routine operation. SRF guns are expected to play an important role in XFEL facilities in the near future. In this paper, we give an overview of design concepts, important parameters and development status of the worldwide SRF gun projects.

47 OTHER INSTRUMENTATION↗

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗

A Contrast Calibration Protocol for X-ray Speckle Visibility Spectroscopy

X-ray free electron lasers, with their ultrashort highly coherent pulses, opened up the opportunity of probing ultrafast nano- and atomic-scale dynamics in amorphous and disordered material systems via speckle visibility spectroscopy. However, the anticipated count rate in a typical experiment is usually low. Therefore, visibility needs to be extracted via photon statistics analysis, i.e., by estimating the probabilities of multiple photons per pixel events using pixelated detectors. Considering the realistic X-ray detector responses including charge cloud sharing between pixels, pixel readout noise, and gain non-uniformity, speckle visibility extraction relying on photon assignment algorithms are often computationally demanding and suffer from systematic errors. In this paper, we present a systematic study of the commonly-used algorithms by applying them to an experimental data set containing small-angle coherent scattering with visibility levels ranging from below 1% to ∼60%. We also propose a contrast calibration protocol and show that a computationally lightweight algorithm can be implemented for high-speed correlation evaluation.

47 OTHER INSTRUMENTATION↗

Complex Attosecond Waveform Synthesis at FEL FERMI

Free-electron lasers (FELs) can produce radiation in the short wavelength range extending from the extreme ultraviolet (XUV) to the X-rays with a few to a few tens of femtoseconds pulse duration. These facilities have enabled significant breakthroughs in the field of atomic, molecular, and optical physics, implementing different schemes based on two-color photoionization mechanisms. In this article, we present the generation of attosecond pulse trains (APTs) at the seeded FEL FERMI using the beating of multiple phase-locked harmonics. We demonstrate the complex attosecond waveform shaping of the generated APTs, exploiting the ability to manipulate independently the amplitudes and the phases of the harmonics. The described generalized attosecond waveform synthesis technique with an arbitrary number of phase-locked harmonics will allow the generation of sub-100 as pulses with programmable electric fields.

47 OTHER INSTRUMENTATION↗

The DREAM Endstation at the Linac Coherent Light Source

Free-electron lasers (FEL), with their ultrashort pulses, ultrahigh intensities, and high repetition rates at short wavelength, have provided new approaches to Atomic and Molecular Optical Science. One such approach is following the birth of a photo electron to observe ion dynamics on an ultrafast timescale. Such an approach presents the opportunity to decipher the photon-initiated structural dynamics of an isolated atomic and molecular species. It is a fundamental step towards understanding single- and non-linear multi-photon processes and coherent electron dynamics in atoms and molecules, ultimately leading to coherent control following FEL research breakthroughs in pulse shaping and polarization control. A key aspect for exploring photoinduced quantum phenomena is visualizing the collective motion of electrons and nuclei in a single reaction process, as dynamics in atoms/ions proceed at femtosecond (10 –15 s) timescales while electronic dynamics take place in the attosecond timescale (10 –18 s). Here, we report on the design of a Dynamic Reaction Microscope (DREAM) endstation located at the second interaction point of the Time-Resolved Molecular and Optical (TMO) instrument at the Linac Coherent Light Source (LCLS) capable of following the photon–matter interactions by detecting ions and electrons in coincidence. The DREAM endstation takes advantage of the pulse properties and high repetition rate of LCLS-II to perform gas-phase soft X-ray experiments in a wide spectrum of scientific domains. With its design ability to detect multi-ions and electrons in coincidence while operating in step with the high repetition rate of LCLS-II, the DREAM endstation takes advantage of the inherent momentum conservation of reaction product ions with participating electrons to reconstruct the original X-ray photon–matter interactions. In this report, we outline in detail the design of the DREAM endstation and its functionality, with scientific opportunities enabled by this state-of-the-art instrument.

47 OTHER INSTRUMENTATION↗

Unusual Breathing Behavior of Optically Excited Barium Titanate Nanocrystals

Coherent X-ray diffraction patterns were recorded by using an X-ray free-electron laser to illuminate barium titanate nanocrystals as a function of time delay after laser excitation. Rather than seeing any significant thermal expansion effects, the diffraction peaks were found to move perpendicular to the momentum transfer direction. This suggests a laser driven rotation of the crystal lattice, which is delayed by the aggregated state of the crystals. Internal deformations associated with crystal contacts were also observed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Crystallization of ApoA1 and ApoE4 Nanolipoprotein Particles and Initial XFEL-Based Structural Studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via high-density lipoprotein (HDL) and low-density lipoprotein (LDL) maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics, and to develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Case Study of High-Throughput Drug Screening and Remote Data Collection for SARS-CoV-2 Main Protease by Using Serial Femtosecond X-ray Crystallography

Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in silico drug screening studies have been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with nine drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.

60 APPLIED LIFE SCIENCES↗