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Contour interpolated radial basis functions with spline boundary correction for fast 3D reconstruction of the human articular cartilage from MR images

Purpose: The aim of this work is to demonstrate a new image processing technique that can provide a “near real-time” 3D reconstruction of the articular cartilage of the human knee from MR images which is user friendly. This would serve as a point-of-care 3D visualization tool which would benefit a consultant radiologist in the visualization of the human articular cartilage. Methods: The authors introduce a novel fusion of an adaptation of the contour method known as “contour interpolation (CI)” with radial basis functions (RBFs) which they describe as “CI-RBFs.” The authors also present a spline boundary correction which further enhances volume estimation of the method. A subject cohort consisting of 17 right nonpathological knees (ten female and seven male) is assessed to validate the quality of the proposed method. The authors demonstrate how the CI-RBF method dramatically reduces the number of data points required for fitting an implicit surface to the entire cartilage, thus, significantly improving the speed of reconstruction over the comparable RBF reconstruction method of Carr. The authors compare the CI-RBF method volume estimation to a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Results: The authors demonstrate how the CI-RBF method significantly reduces the number of data points (p-value < 0.0001) required for fitting an implicit surface to the cartilage, by 48%, 31%, and 44% for the patellar, tibial, and femoral cartilages, respectively. Thus, significantly improving the speed of reconstruction (p-value < 0.0001) by 39%, 40%, and 44% for the patellar, tibial, and femoral cartilages over the comparable RBF model of Carr providing a near real-time reconstruction of 6.49, 8.88, and 9.43 min for the patellar, tibial, and femoral cartilages, respectively. In addition, it is demonstrated how the CI-RBF method matches the volume estimation of a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Furthermore, the performance of the segmentation method used for the extraction of the femoral, tibial, and patellar cartilages is assessed with a Dice similarity coefficient, sensitivity, and specificity measure providing high agreement to manual segmentation. Conclusions: The CI-RBF method provides a fast, accurate, and robust 3D model reconstruction that matches Carr’s RBF method, 3D DOCTOR, and a manual benchmark method in accuracy and significantly improves upon Carr’s RBF method in data requirement and computational speed. In addition, the visualization tool has been designed to quickly segment MR images requiring only four mouse clicks per MR image slice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Adsorption of terbium (III) on DGA and LN resins: Thermodynamics, isotherms, and kinetics

Two commercially available extraction chromatography (EXC) resins containing N,N,N’,N’-tetra-n-octyldiglycolamide (DGA Resin, Normal, 50 – 100 μm) and Bis(2-ethylhexyl) phosphate (LN Resin, 100 – 150 μm) were used as adsorbents to study fundamental adsorption properties such as thermodynamic values, equilibrium isotherms, and kinetic uptake models for terbium(III) adsorption. Weight distribution ratios (D w ) for terbium on DGA and LN resins were measured using a [ 160 Tb]Tb 3+ radiometric tracer in nitric acid as a function of acidity, temperature, initial analyte concentration, and equilibrium time. The D w values showed increasing binding affinity for DGA resin at high nitric acid concentrations and decreasing binding affinity for LN resins. Thermodynamic studies for DGA and LN resins revealed that the Gibbs free energy (ΔG) increased consistently with temperature. To model equilibrium data, increasingly higher parameter equilibrium isotherm models (Henry (1) < Langmuir, Freundlich (2) < Redlich-Peterson (3) < Fritz-Schluender (4)) were compared on their root mean squared errors (RMSE) and adjusted determination coefficients to determine the most applicable model. In all cases, the empirical four-parameter Fritz-Schluender isotherm demonstrated a superior fit. Similar comparisons for reaction-based kinetic models (Pseudo-first-order < Pseudo-second-order < Pseudo-n-order) revealed that the higher-order PNO model yielded a superior fit of kinetic data for both resins. Furthermore, in some cases, adsorption isotherms and kinetic models could also be modeled by a lower-order model with minimal change in error parameters. Weber-Morris plots revealed that two linear sections are observed for each resin, where the first linear segment is attributed to fast (film diffusion) adsorption of terbium, followed by slower intraparticle diffusion of terbium through the pores as the rate-limiting step. Based on the Weber-Morris plot, both film and intraparticle diffusion are involved in controlling the kinetic rate of adsorption for DGA and LN resins.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Invariant-mass and fractional-energy dependence of inclusive production of dihadrons in e + e - annihilation at s = 10.58 GeV

The inclusive cross sections for dihadrons of charged pions and kaons ( e + e - → h h X ) in electron-positron annihilation are observed and reported on. They are obtained as a function of the total fractional energy and invariant mass for any di-hadron combination in the same hemisphere as defined by the thrust event-shape variable and its axis. Since same-hemisphere dihadrons can be assumed to originate predominantly from the same initial parton, di-hadron fragmentation functions are probed. Moreove, these di-hadron fragmentation functions are needed as an unpolarized baseline in order to quantitatively understand related spin-dependent measurements in other processes and to apply them to the extraction of quark transversity distribution functions in the nucleon. The di-hadron cross sections are obtained from a 655 fb - 1 data sample collected at or near the Υ ( 4 S ) resonance with the Belle detector at the KEKB asymmetric-energy e + e - collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring electron-beam induced modifications of materials with machine-learning assisted high temporal resolution electron microscopy

Directed atomic fabrication using an aberration-corrected scanning transmission electron microscope (STEM) opens new pathways for atomic engineering of functional materials. In this approach, the electron beam is used to actively alter the atomic structure through electron beam induced irradiation processes. One of the impediments that has limited widespread use thus far has been the ability to understand the fundamental mechanisms of atomic transformation pathways at high spatiotemporal resolution. Here, we develop a workflow for obtaining and analyzing high-speed spiral scan STEM data, up to 100 fps, to track the atomic fabrication process during nanopore milling in monolayer MoS 2 . An automated feedback-controlled electron beam positioning system combined with deep convolution neural network (DCNN) was used to decipher fast but low signal-to-noise datasets and classify time-resolved atom positions and nature of their evolving atomic defect configurations. Through this automated decoding, the initial atomic disordering and reordering processes leading to nanopore formation was able to be studied across various timescales. Using these experimental workflows a greater degree of speed and information can be extracted from small datasets without compromising spatial resolution. This approach can be adapted to other 2D materials systems to gain further insights into the defect formation necessary to inform future automated fabrication techniques utilizing the STEM electron beam.

36 MATERIALS SCIENCE↗

Collective Summary of sCO2 Materials Development (Supercritical Transformational Electric Power Generation (STEP) Level 2 Milestone Report) (Parts I - II)

Polymers such as PTFE (polytetrafluorethylene or Teflon), EPDM (ethylene propylene diene monomer) rubber, FKM fluoroelastomer (Viton), Nylon 11, Nitrile butadiene (NBR) rubber, hydrogenated nitrile rubber (HNBR) and perfluoroelastomers (FF_202) are commonly employed in super critical CO 2 (sCO2) energy conversion systems. O-rings and gaskets made from these polymers face stringent performance conditions such as elevated temperatures, high pressures, pollutants, and corrosive humid environments. In FY 2019, we conducted experiments at high temperatures (100°C and 120°C) under isobaric conditions (20 MPa). Findings showed that elevated temperatures accelerated degradation of polymers in sCO2, and that certain polymer microstructures are more susceptible to degradation over others. In FY 2020, the focus was to understand the effect of sCO2 on polymers at low (10 MPa) and high pressures (40 MPa) under isothermal conditions (100°C). It was clear that the same selectivity was observed in these experiments wherein certain polymeric functionalities showed more propensity to failure over others. Fast diffusion, supported by higher pressures and long exposure times (1000 hours) at the test temperature, caused increased damage in sCO2 environments to even the most robust polymers. We also looked at polymers under compression in sCO2 at 100°C and 20 MPa pressure to imitate actual sealing performance required of these materials in sCO2 systems. Compression worsened the physical damage that resulted from chemical attack of the polymers under these test conditions. In FY 2021, the effect of cycling temperature (from 50°C to 150°C to 50°C) for polymers under a steady sCO2 pressure of 20 MPa was studied. The aim was to understand the influence of cycling temperatures of sCO2 for typical polymers under isobaric (20 MPa) conditions. Thermoplastic polymers (Nylon, and PTFE) and elastomers (EPDM, Viton, Buna N, Neoprene, FF202, and HNBR) were subjected to 20 MPa sCO2 pressure for 50 cycles and 100 cycles in separate experiments. Samples were extracted for ex-situ characterization at 50 cycles and upon the completion of 100 cycles. Each cycle constituted of 175 minutes of cycling from 50°C to 150°C. The polymer samples were examined for physical and chemical changes by Dynamic Mechanical and Thermal Analysis (DMTA), Fourier Transform Infrared (FTIR) spectroscopy, and compression set. Density and mass changes immediately after removal from test were measured for degree of swell comparisons. Optical microscopy techniques and micro computer tomography (micro CT) images were collected on select specimens. Evaluations conducted showed that exposures to super-critical CO2 environments resulted in combinations of physical and/or chemical changes. For each polymer, the dominance of cycling temperatures under sCO2 pressures, were evaluated. Attempts were made to qualitatively link the permanent sCO2 effects to polymer micro- structure, free volume, backbone substitutions, presence of polar groups, and degree of crystallinity differences. This study has established that soft polymeric materials are conducive to failure in sCO2 through mechanisms of failure that are dependent on polymer microstructure and chemistry. Polar pendant groups, large atom substitutions on the backbone are some of the factors that are influential structural factors.

36 MATERIALS SCIENCE↗

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Investigation of boosted proton energies through proton radiography of target normal sheath acceleration fields in the multi-ps regime

Multi-kilojoule, multi-picosecond short-pulse lasers, such as the National Ignition Facility-Advanced Radiographic Capability laser and the OMEGA-Extended Performance laser, which have been constructed over the last two decades, enable exciting opportunities to produce high-brightness, high-energy laser-driven proton sources for applications in high-energy-density science like proton fast ignition for inertial fusion energy, particle radiography, and materials science studies. Results on these platforms have demonstrated enhanced accelerated proton energies and electron temperatures when compared to established scaling laws. Recent work has developed a new scaling for proton TNSA in the multi-ps regime. However, this new physics in the multi-ps regime motivates the need to understand the origin of the enhancement in proton energies. Toward this goal, here this work presents the first measurements of the TNSA accelerating sheath field in the multi-ps regime for pulse durations of 0.6, 5, and 10 ps. This measurement was achieved by using a separate TNSA proton source to radiograph the spatiotemporal profile of the accelerating sheath that is responsible for proton acceleration. The use of stacked radiochromic film detectors allows for a discrete time profile of the radiographs, thus enabling the measurement of the temporal and spatial evolution of the accelerating field. In performing this measurement, we extract quantities such as the sheath strength as a function of time and pulse duration, which shows that longer pulse durations sustain a stronger electric field for a longer duration when compared to sub-ps laser pulses, which may enable the observed boosted proton energies and proton conversion efficiencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optically multiplexed neutron time-of-flight technique for inertial confinement fusion

Neutron time-of-flight (nTOF) detectors are crucial in diagnosing the performance of inertial confinement fusion (ICF) experiments, which implode targets of deuterium–tritium fuel to achieve thermonuclear conditions. These detectors utilize the fusion neutron energy spectrum to extract key measurements, including the hotspot ion temperature and fuel areal density. Previous work [Danly et al., Rev. Sci. Instrum. 94, 043502 (2023)] has demonstrated adding 1D spatial resolution to an nTOF-like detector using a neutron aperture and streak camera to measure the ion temperature profile of an ICF implosion. By contrast, the study presented herein explores modifying the 1D detector to use a fast photomultiplier tube (PMT) to validate the design of a 2D spatially resolved instrument based on reconstruction from 1D profiles. The modification would collect time-of-flight traces from separate scintillators in an imaging array with one PMT using optical fibers of varying lengths to time-multiplex the signals. This technique has been demonstrated in ride-along experiments on the OMEGA laser with 20 fiber-coupled scintillator channels connected to a Photek PMT210. Results provide constraints on the fiber lengths and PMT gating requirements to promote pulse fidelity throughout all channels. Calibration of the detector to fixed nTOFs can provide a preliminary estimate of the instrument response function (IRF), although measurement of the IRF is currently under way. These results suggest that nTOF signals can potentially be time-multiplexed with fibers so long as the design is strategic to mitigate signal-to-noise reduction, modal dispersion, and charge build-up in the PMT, which has implications beyond ion temperature imaging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Onset of Scrambling as a Dynamical Transition in Tunable-Range Quantum Circuits

In a fast-scrambling many-body quantum system, information is spread and entanglement is built up on a time scale that grows logarithmically with the system size. This is of fundamental interest in understanding the dynamics of many-body systems, as well as in efficiently producing entangled resource states and error-correcting codes. In this work, we identify a dynamical transition marking the onset of scrambling in quantum circuits with different levels of long-range connectivity. In particular, we show that as a function of the interaction range for circuits of different structures, the tripartite mutual information exhibits a scaling collapse around a critical point between two clearly defined regimes of different dynamical behavior. We study this transition analytically in a related long-range Brownian-circuit model and show how the transition can be mapped onto the statistical mechanics of a long-range Ising model in a particular region of parameter space. This mapping predicts mean-field critical exponents v=–1/(1 + s c ), which are consistent with the critical exponents extracted from Clifford-circuit numerics. In addition to systems with conventional power-law interactions, we identify the same phenomenon in deterministic sparse circuits that can be realized in experiments with neutral-atom arrays.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dual functionality of over-lithiated NMC for high energy silicon-based lithium-ion batteries

Owing to their high specific capacity and suitably low operating potential, silicon-based anodes are an attractive alternative to graphite in next-generation lithium-ion batteries. However, silicon anodes suffer from low initial coulombic efficiency and fast capacity decay, limiting their widespread application. Pre-lithiation strategies are highly appealing to compensate for irreversible active lithium loss and to boost the cell energy density. In this work, we maximize the cell energy density by direct pre-lithiation of the NMC (LiNi 0.5 Mn 0.3 Co 0.2 O 2 ) cathode to Li 1+x NMCO 2 without introducing inactive deadweight to either electrode. First, we demonstrate that Li 1+x NMCO 2 can be synthesized chemically, via reaction between NMC and lithium napthalide, and electrochemically. The NMC cathode is tolerant of a one-time over-lithiation up to 60 mA h g NMC -1 , giving capacity retention on par with untreated NMC in half cell electrochemical cycling. Using synchrotron X-ray absorption spectroscopy (ex situ) and diffraction (in situ), we demonstrate that higher amounts of over-lithiation lead to local structure distortion – driven by transition metal reduction to Jahn–Teller active Mn 3+ and Co 2+ – as well as bulk structural hysteresis during over-lithiation and layer “buckling” that increases the amount of lithium extracted from the structure in the charged state. The Li 1+x NMCO 2 with low-to-moderate over-lithiation capacity (23, 46, and 70 mA h g NMC -1 ) is proven to be a highly effective dual-purpose lithium source and cathode material in full cell tests with a commercially relevant Si–graphite anode. These cells show higher capacity, superior cycle life, and improved coulombic efficiencies when compared to those with stoichiometric NMC cathodes. Finally, this study introduces a new and simple method to pre-lithiate layered transition metal oxide cathodes, opening up new possibilities for the development of high energy density lithium-ion batteries with next-generation anodes.

25 ENERGY STORAGE↗

Optical contrast analysis of α -RuCl 3 nanoflakes on oxidized silicon wafers

α-RuCl 3 , a narrow-band Mott insulator with a large work function, offers intriguing potential as a quantum material or as a charge acceptor for electrical contacts in van der Waals devices. In this work, we perform a systematic study of the optical reflection contrast of α-RuCl 3 nanoflakes on oxidized silicon wafers and estimate the accuracy of this imaging technique to assess the crystal thickness. Via spectroscopic micro-ellipsometry measurements, we characterize the wavelength-dependent complex refractive index of α-RuCl 3 nanoflakes of varying thickness in the visible and near-infrared. Building on these results, we simulate the optical contrast of α-RuCl 3 nanoflakes with thicknesses below 100 nm on SiO 2 /Si substrates under different illumination conditions. We compare the simulated optical contrast with experimental values extracted from optical microscopy images and obtain good agreement. Finally, we show that optical contrast imaging allows us to retrieve the thickness of the RuCl 3 nanoflakes exfoliated on an oxidized silicon substrate with a mean deviation of –0.2 nm for thicknesses below 100 nm with a standard deviation of only 1 nm. Our results demonstrate that optical contrast can be used as a non-invasive, fast, and reliable technique to estimate the α-RuCl 3 thickness.

2D materials↗

Working towards recalcitrance mechanisms: increased xylan and homogalacturonan production by overexpression of GAlactUronosylTransferase12 (GAUT12) causes increased recalcitrance and decreased growth in Populus

The development of fast-growing hardwood trees as a source of lignocellulosic biomass for biofuel and biomaterial production requires a thorough understanding of the plant cell wall structure and function that underlie the inherent recalcitrance properties of woody biomass. Downregulation of GAUT12.1 in Populus deltoides was recently reported to result in improved biomass saccharification, plant growth, and biomass yield. To further understand GAUT12.1 function in biomass recalcitrance and plant growth, here we report the effects of P. trichocarpa GAUT12.1 overexpression in P. deltoides. Increasing GAUT12.1 transcript expression by 7-49% in P. deltoides PtGAUT12.1-overexpression (OE) lines resulted in a nearly complete opposite biomass saccharification and plant growth phenotype to that observed previously in PdGAUT12.1-knockdown (KD) lines. This also included significantly reduced glucose, xylose, and total sugar release (12-13%), plant height (6-54%), stem diameter (8-40%), and overall total aerial biomass yield (48-61%) in 3-month-old, greenhouse-grown PtGAUT12.1-OE lines compared to controls. Total lignin content was unaffected by the gene overexpression. Importantly, selected PtGAUT12.1-OE lines retained the recalcitrance and growth phenotypes upon growth for 9 months in the greenhouse and 2.8 years in the field. PtGAUT12.1-OE plants had significantly smaller leaves with lower relative water content, and significantly reduced stem wood xylem cell numbers and size. At the cell wall level, xylose and galacturonic acid contents increased markedly in total cell walls as well as in soluble and insoluble cell wall extracts, consistent with increased amounts of xylan and homogalacturonan in the PtGAUT12.1-OE lines. This led to increased cell wall recalcitrance, as manifested by the 9-15% reduced amounts of recovered extractable wall materials and 8-15% greater amounts of final insoluble pellet in the PtGAUT12.1-OE lines compared to controls. The combined phenotype and chemotype data from P. deltoides PtGAUT12.1-OE and PdGAUT12.1-KD transgenics clearly establish GAUT12.1 as a recalcitrance- and growth-associated gene in poplar. Overall, the data support the hypothesis that GAUT12.1 synthesizes either an HG-containing primer for xylan synthesis or an HG glycan required for proper xylan deposition, anchoring, and/or architecture in the wall, and the possibility of HG and xylan glycans being connected to each other by a base-sensitive covalent linkage.

09 BIOMASS FUELS↗

Producing ENDF/B-quality Evaluations of 239 Pu(n,f) and 235 U(n,f) Average Prompt Neutron Multiplicities using the CGMF Model

This report documents evaluations of the neutron-induced 239 Pu and 235 U average prompt neutron multiplicities, $\overline{v}_p$, using the CGMF model developed at LANL. These evaluations are not updates of existing ENDF/B-VIII.0 nuclear data, but were both re-done from "scratch". That is, all experimental data were extracted from EXFOR, re-normalized to the newest nuclear data representing monitor observables, and detailed uncertainties were estimated from information in EXFOR as well as from templates of expected measurement uncertainties. We also included experimental data that were not yet available for ENDF/B-VIII.0, for instance, the data of Marini et al. for 239 Pu(n,f) $\overline{v}_p$ or the data of Khoklov et al. for 235 U(n,f) $\overline{v}_p$. Finally, we include the CGMF model; it computes $\overline{v}_p$ based on model parameters that at the same time calculate fission fragments as a function of mass, Y (A), the average total kinetic energy as a function of incident-neutron energy, $\langle TKE \rangle$(E inc ), etc. Such a detailed fission model that ties together many fission quantities has not been used to date for any $\overline{v}_p$ evaluation in ENDF/B. Here, we show that we can get evaluated 235 U(n,f) and 239 Pu $\overline{v}_p$ that not only correspond well to experimental $\overline{v}_p$, but that the associated evaluated model parameters also yield parameterizations of Y (A), $\langle TKE \rangle$(E inc ), etc., that correspond well to their respective experimental data. The new evaluated 239 Pu(n,f) $\overline{v}_p$ was also combined into a 239 Pu test file with the newest nuclear data for the 239 Pu prompt-fission neutron spectrum and fission cross sections. This new 239 Pu file performed reasonably well in predicting PU-MET-FAST assemblies, reaction rates in Jezebel and Flattop and three LLNL pulsed spheres. Due to that, the new 239 Pu(n,f) $\overline{v}_p$ evaluation presented here is being considered for ENDF/B-VIII.1. Hence, we can show here that CGMF is able to produce ENDF/B quality $\overline{v}_p$ nuclear data.

239Pu, 235U, Average Prompt-fission Neutron Multip↗

Grid-Connected Modular Soft-Switching Solid State Transformers (M-S4T)

The objective of this project is to develop and verify the concept of a flexible and modular soft-switching solid-state transformer (M-S4T) for direct grid-connected applications. The ability to directly connect power electronics converters to the medium voltage grid (4 kV – 13 kV), and to potentially replace the passive and bulky, but ubiquitous 60 hertz service transformer in the 25 kVA to 100 kVA range, with a more flexible and controllable device, has been regarded as the ‘holy grail’ in grid control. However, this has proven to be extremely difficult. This project has developed the solutions to several key challenges of the direct grid-connected power electronics and realized a 7.2 kV M-S4T prototype. First, a protection method to protect the M-S4T from the high voltages (110 kV for the 13 kV system) that occur on the grid due to transients and lightning strikes have been developed and experimentally verified. Second, the realization and the operation of the M-S4T based on high-voltage SiC devices (>3.3 kV) and a medium-frequency medium-voltage low-leakage transformer in a single-stage solid-state transformer with zero-voltage switching, low dv/dt, and low electromagnetic interference has been successfully demonstrated up to 7.5 kV peak. Third, an oil-cooling system and stable communication and distributed control system for converter module voltage sharing have been developed and experimentally verified. The developed M-S4T has realized a modular universal high-performance power conversion system. This conversion system is scalable to different voltage and power levels and adaptable to four-quadrant bidirectional operation. Moreover, the use of passive cooling techniques meets the equipment life requirements, and the lightning protection scheme fulfills the basic insulation level specifications for direct grid connection. Such power conversion system opens up near-term opportunities, including energy storage, solar PV, or electric vehicle charging with significant cost and footprint savings. In the longer term, the possibility of replacing the utility distribution transformer with an M-S4T will be transformative for future distribution grids with a compact footprint and full controllability to enable high renewable energy and storage penetration. In addition to the main project, this report expands on the Plus-Up projected including as part of the main award. This project developed and demonstrated the technology for autonomous collaborative inverters that can be connected in an ad hoc manner to the grid. The aim of the project was to: (1) evaluate the existing techniques for grid-connected inverters and find their limitations; (2) develop detailed requirements for grid-connected inverters in the modern grid with millions of active nodes; (3) design a unified control strategy that brings more autonomy and intelligence to grid-connected inverters, and addresses parts of the issues with the existing techniques. The proposed technique, called UniCon, enables inverters to 1) connect/disconnect to/from the grid in an ad hoc manner; (2) work based on local sensing. Slow communication could be used for a more optimized behavior; (3) work automatically in both grid-forming/grid-following mode; (4) handle large disturbances, e.g., big load step and fault, in an oscillation-free manner; (5) work collaboratively with other inverters in steady-state and during transients. UniCon can be implemented in the middle-level control; hence it is agnostic to the vendor and to the implementation of the inner voltage/current and protection loops. Furthermore, a new synchronization scheme, based on deep learning, was developed that can extract the grid voltage phase and amplitude in a stable manner. The method is cheap to implement can improve the dynamic performance of the grid-connected inverters during fast transients, e.g., fault. The proposed control scheme was validated by (1) MATLAB/Simulink; (2) hardware-in-the-loop results, and; (3) experimental results using three inverters that form a microgrid in a down-scaled feeder. Lastly, both the M-S4T and UniCon have achieved promising tangible paths to markets. In the case of the M-S4T, the underlying technology — the Soft Switching Solid State Transformer (S4T) developed at the Georgia Tech Center for Distributed Energy (GT-CDE) has been licensed by GridBlock from the Georgia Tech Research Corporation, and GridBlock has been working with manufacturing partner Jabil (one of the largest US-based contract manufacturers) and system integrator Power Secure (largest deployer of microgrids in the US with 4.7 GW under management), to meet the strong initial demand. Similarly, GridBlock has an exclusive license to the UniCon technology, developed under this award by GT-CDE. The UniCon provides an intermediate control layer that enables the implementation of the higher-level ‘transactive’ control commands for the system. The architecture of the system - slow communications with the cloud for system optimization and setpoints, and the use of locally measured quantities for real-time control, provide a very robust and secure way of implementing a real-time must-run grid that is also secure and stable. This is a brand-new functionality that is critical for the future grid and key to GridBlock’s business model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Characterization of a SiPM-based monolithic neutron scatter camera using dark counts

The Single Volume Scatter Camera (SVSC) Collaboration aims to develop portable neutron imaging systems for a variety of applications in nuclear non-proliferation. Conventional double-scatter neutron imagers are composed of several separate detector volumes organized in at least two planes. A neutron must scatter in two of these detector volumes for its initial trajectory to be reconstructed. As such, these systems typically have a large footprint and poor geometric efficiency. We report on the design and characterization of a prototype monolithic neutron scatter camera that is intended to significantly improve upon the geometrical shortcomings of conventional neutron cameras. The detector consists of a 50 mm×56 mm× 60 mm monolithic block of EJ-204 plastic scintillator instrumented on two faces with arrays of 64 Hamamatsu S13360-6075PE silicon photomultipliers (SiPMs). The electronic crosstalk is limited to < 5% between adjacent channels and < 0.1% between all other channel pairs. SiPMs introduce a significantly elevated dark count rate over PMTs, as well as correlated noise from after-pulsing and optical crosstalk. In this article, we characterize the dark count rate and optical crosstalk and present a modified event reconstruction likelihood function that accounts for them. We find that the average dark count rate per SiPM is 4.3 MHz with a standard deviation of 1.5 MHz among devices. The analysis method we employ to measure internal optical crosstalk also naturally yields the mean and width of the single-electron pulse height. Here, we calculate separate contributions to the width of the single-electron pulse-height from electronic noise and avalanche fluctuations. We demonstrate a timing resolution for a single-photon pulse to be (128 ± 4) ps. Finally, coincidence analysis is employed to measure external (pixel-to-pixel) optical crosstalk. We present a map of the average external crosstalk probability between 2×4 groups of SiPMs, as well as the in-situ timing characteristics extracted from the coincidence analysis. Further work is needed to characterize the performance of the camera at reconstructing single- and double-site interactions, as well as image reconstruction.

47 OTHER INSTRUMENTATION↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Use of a Mylar filter to eliminate vacuum ultraviolet pulse pileup in low-energy x-ray measurements

We describe a method to reduce vacuum ultraviolet (VUV) pulse pileup (PPU) in x-ray pulse-height Silicon Drift Detector (SDD) signals. An Amptek FAST SDD, with C1 (Si 3 N 4 ) window, measures bremsstrahlung emitted from PFRC-2 plasma to extract the electron temperature (T e ) and density (n e ). The C1 window has low transmissivity for photons with energy below 200 eV though will transmit some VUV and soft x-ray photons, which PFRC-2 plasmas abundantly emit. Multi-VUV-photon PPU contaminates the interpretation of x rays with energy > 100 eV, particularly in a low-energy exponential tail. The predicted low transmissivity of ~1 μm thick Mylar [polyethylene terephthalate (PET)] to photons of energy <100 eV led to the selection of Mylar as the candidate filter to reduce VUV PPU. Experiments were conducted on an x-ray tube with a graphite target and on a quasi-Maxwellian tenuous plasma (n e ~ 10 9 cm –3 ) with effective temperatures reaching 1500 eV. A Mylar filter thickness of 850 nm is consistent with the results. The Mylar-filter-equipped SDD was then used on the PFRC-2 plasma, showing a substantial reduction in the low-energy x-ray signal, supporting our hypothesis of the importance of VUV PPU. Here, we describe the modeling and experiments performed to characterize the effect of the Mylar filter on SDD measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗