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At least 163 records · Page 9

The BigBite Calorimeter for the Super Bigbite Spectrometer Program at Jefferson Lab

Here, we report features of the design, construction, installation, and performance of the BigBite Calorimeter (BBCal), a lead-glass electromagnetic calorimeter constructed as part of the BigBite Spectrometer (BBS), which served as the electron arm for the Super Bigbite Spectrometer (SBS) program of high-precision neutron electromagnetic form factor measurements in Hall A at Jefferson Lab. As a total-absorption calorimeter, BBCal provided the primary electron trigger for BBS, detecting quasi-elastically scattered electrons in the 1–4 GeV energy range with an energy resolution of approximately 6.2%, position resolution of 1.2 cm, and timing resolution of 0.5 ns.

BBCal↗

A Study of the Ultraviolet Radiation of Hybrid X-Pinches

The results of an experimental study of hybrid X-pinches (HXPs) as sources of vacuum ultraviolet (VUV) radiation within the wavelength range of λ < 2000 Å are presented here. A KING compact low-voltage generator (45 kV, 200 kA, 190 ns) was used to feed the X-pinches. The dynamics of forming the radiating plasma of HXPs of different materials were studied using pinhole cameras with radiation receivers based on microchannel plates with a time resolution of 5 ns and a spatial resolution of 150 µm. The time structure and energy characteristics of the radiation were studied using diamond photoconducting detectors (PCDs). The spectral composition of UV radiation was investigated using a spectrograph based on the transmission grating. It has been shown that the efficiency of conversion of the capacitor-stored energy to the VUV radiation may reach 5%, whereas the fraction of soft X-rays (SXR) with quanta energies above 800 eV is no more than 3%. In this case, the source brightness reaches 2 × 10 9 W/(sr cm 2 ).

plasma UV-spectroscopy↗

Interesting Solar Energy System Simulations in 1990 and 2025

This presentation uses a simulation by the author in 1991 and newer developements in 2025 to illustrate strategies to address problems that arise when steady state assumption is applied in time series simulation: 1) high resolution time series data; 2) distirbution functiion; 3) machine learning. The presentation does not report new findings (previously published material is cited).

14 SOLAR ENERGY↗

28nm front end ASIC and 12” LGADs for 3D integration

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (≈10 μm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present the design and results from a 28 nm CMOS ASIC prototype, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. We also report on the co-design and characterization of reticle-scale LGAD sensors with 50 μm and 100 μm pixels and introduce the next 10k-pixel ASIC designed for full 3D integration. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

The HTAP_v3.2 emission mosaic: merging regional and global monthly emissions (2000–2020) to support air quality modelling and policies

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3.2, an ad-hoc global mosaic of anthropogenic inventories, is an update to the HTAP_v3 global mosaic inventory and has been developed by integrating official inventories over specific areas (North America, Europe, Asia including China, Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO 2 , NO x , CO, NMVOC, NH 3 , PM 10 , PM 2.5 , Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 × 0.1° and time intervals of months and years covering the period 2000–2020 (https://doi.org/10.5281/zenodo.17086684, Crippa, 2025, https://edgar.jrc.ec.europa.eu/dataset_htap_v32, last access: 27 October 2025). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3.2 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Guizzardi, Diego [European Commission, Ispra (Ital↗

A New Measurement of the Neutron Electric Form Factor with the Super Bigbite Spectrometer Apparatus

Protons and neutrons, collectively known as nucleons, make up the nuclei at the core of atoms which form our world. The nucleon has been under intensive study for over 100 years, and yet we still do not fully understand the internal dynamics which govern properties like its spin or its mass-which contributes to almost all of the visible mass in the universe. These dynamics are governed by quantum chromodynamics(QCD), the predictions of which are experimentally tested at high energy accelerator facilities such as Jefferson Lab. TheGEN-II experiment (E12-09-016) is one such experiment. GEN-II is part of the Super Bigbite Spectrometer (SBS) experimental form factor pro gramme taking place in Hall A at Jefferson Lab, which aims to make precision measurements of the nucleon electromagnetic form factors(EMFFs)at record high values of squared four momentum transfer ¿2. EMFFs describe the electric and magnetic moment distributions within the nucleon. They can be measured through elastic electron scattering off the nucleon, and describe the recoil response of the target nucleon at a given energy scale. GEN-II is a double polarized semi-exclusive beam target asymmetry (BTA) experiment, seeking to measure the electric form factor of the neutron,¿¿ ¿,at three new values of squared four-momentum transfer¿2 =2.92,6.74and9.82GeV². The latter two points being at record high ¿2. The form factor is determined through measuring the BTA of quasielliptical scattering of a neutron from a polarized nuclear target. The experiment utilized the CEBAF accelerator to produce longitudinally polarized electrons up to ~85% polarization, which were scattered off neutrons within a novel polarized helium-3 (³He) target. This new polarized ³He target was employed by building on the technology of its precursors which existed in similar preceding experiments. This target was designed to operate at the high luminosities typical of Hall A, and reached a record breaking combination of polarization and beam intensity known as figure of merit, three times larger than those predecessors. The SBS collaboration designed and constructed two brand new high acceptance spectrometers for these experiments, an electron arm named Bigbite (BB) and a hadron arm named Super Bigbite. Both spectrometers featured a large acceptance EM dipole magnet, and complementary detector systems. The electron arm contained gaseous electronmultipliers(GEMs) which were used for high precision tracking of the scattered electrons, a heavy gas cherenkov (GRINCH) which was used for PID between electrons and pions, a plastic i ii scintillator timing hodoscope to provide high resolution timing of the start of events, and a pair of EM calorimeters (BBCal) which provided energy measurements of detected particles, and provided the experimental trigger. The hadron arm also contained a system of GEMs which will be utilized for future SBS experiments, and a hadron calorimeter designed to provide position, timing and energy measurements of the recoiling nucleon. The calibration of all detector subsystems, beam and target data is discussed, with a focus on novel timing calibrations to the hodoscope and hadron calorimeter. An analysis of selecting quasielliptical events and suppressing background contributions from a number of sources which contaminate the final event sample is given. The largest irreducible backgrounds are found to be from misidentified protons, timing accidentals and inelastic events. The physical asymmetry is measured and used to extract a value for the form factor ratio ¿¿ ¿/¿¿ ¿. High precision ¿2 data for ¿¿ ¿ is used to then extract ¿¿ ¿. This work finds at ¿2 = 2.92 GeV2 that ¿¿ ¿ = 0.0129+0.0019 -0.0020. This result is in statistical agreement with existing fits to world data, and predictions from the constituent quark model and Dyson–Schwinger equations, in this region of ¿2.

Penman, Gary [Univ. of Glasgow, Scotland (United K↗

Real-time inference and extrapolation with Time-Conditioned UNet: Applications in hypersonic flows, incompressible flows, and global temperature forecasting

Neural Operators are fast and accurate surrogates for nonlinear mappings between functional spaces within training domains. Extrapolation beyond the training domain remains a grand challenge across all application areas. We present Time-Conditioned UNet (TC-UNet) as an operator learning method to solve time-dependent PDEs continuously in time without any temporal discretization, including in extrapolation scenarios. TC-UNet incorporates the temporal evolution of the PDE into its architecture by combining a parameter conditioning approach with the attention mechanism from the Transformer architecture. After training, TC-UNet makes real-time inferences on an arbitrary temporal grid. We demonstrate its extrapolation capability on a climate problem by estimating the global temperature for several years and also for inviscid hypersonic flow around a double cone. We propose different training strategies involving temporal bundling and sub-sampling. We demonstrate performance improvements for several benchmarks, performing extrapolation for long time intervals and zero-shot super-resolution time.

Deep learning↗

Gallium oxide semiconductor-based large volume ultrafast radiation hard spectroscopic scintillators

We report on the development of the first-ever inorganic radiation-hard moisture-insensitive large volume spectroscopic semiconductor-based scintillator with less than 2 ns decay time and light yields as high as 8000 ph/MeV. Despite extensive research into scintillator materials, the quest for an ideal scintillator combining ultrafast decay times (akin to BaF 2 and Yb-doped scintillators such as Lu 2 O 3 :Yb), high light yields (exceeding 2000 photons per MeV), spectroscopic capabilities, and exceptional radiation hardness remain unfulfilled. In this study, we demonstrate and report for the first time the viability of large-volume (up to 20 mm thickness) gallium oxide (β-Ga 2 O 3 ) semiconductor-based scintillators for applications requiring these properties. These β-Ga 2 O 3 scintillators were grown using the fast turnaround (~2 days) crucible-free optical float zone (FZ) technique. The high light yield and ultrafast decay time of these high-purity n-type semiconductors with free carrier concentration of 6 × 10 17 cm –3 are attributed to native defects, specifically oxygen vacancies (V O ) and gallium–oxygen vacancy pairs (V Ga –V O ), generated during optimized FZ growth. The ultrafast decay, along with high light yield, enables excellent timing resolution and high count rate detection for applications like time-of-flight positron emission tomography, physics experiments, and nuclear safety. The radiation hardness of these devices has been documented in a separate publication.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Calorimeter calibration and performance for the Mu2e experiment

The Mu2e experiment at Fermilab will search for the charged lepton flavour-violating conversion of a muon into an electron, aiming to reach a sensitivity of $R_{\mu e} \sim 10^{-17}$, an improvement of four orders of magnitude over previous limits. To reach this goal, Mu2e will use an intense pulsed muon beam and a detector system composed of a high-precision straw tube tracker and a pure CsI crystal calorimeter. The calorimeter plays a crucial role in the experiment, as it provides particle identification capabilities that are necessary for background suppression. To perform its tasks, the detector must achieve an energy resolution better than 10% and a timing resolution below 500 ps for 100 MeV electrons. Cosmic-ray data and laser pulses are used to equalize the response of each channel, to calibrate the energy scale and to monitor the system's stability over time. This poster reports on the calibration and analysis techniques developed to ensure that the calorimeter requirements for precise energy and time measurements are met. Results for the calorimeter performance obtained during the commissioning phase will be discussed, and an overview of the current status in the Mu2e experimental hall will be presented.

Salamino, Sabrina [Frascati]↗

Black carbon emissions from modern automated cordwood stoves for space heating

Wood burning stove design is improving as regulation become stricter for particulate matter emissions. Here, this study describes results of black carbon (BC) emissions from three modern automated wood stoves when tested in common failure modes using a test protocol that included cold-starts, high and low fuel loading densities, and use of overly large pieces of fuel. Emission sampling was performed using a dilution sampling system in tandem with an aethalometer to measure BC with high time resolution. Results show that the time-weighted average BC emission rates were 0.91, 4.30, and 1.74 g/h for the three stoves tested (A, B, and C respectively), the values, both higher and lower than the United States 2020 certification test emission limit of 2.5 g/h. The results demonstrate good performance overall, given the rigorous nature of the testing protocol used. The aethalometer data showed that the performance was relatively poor during cold-start, when the fuel was ignited and combusted without a coalbed, and when stoves failed to optimize air delivery due to specific loading and output conditions. During the cold-start test section, the average BC emission rate was seven times higher than the overall average for Stove A, 10 times above the average for Stove B, and two times above the average emission rate for Stove C. Calculations of the Average Angstrom Absorption Exponent (AAE) of the exhaust aerosol showed little correlation with BC concentration. The results show that automation results in a quantifiable reduction in particular BC emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-bandwidth frequency domain multiplexed readout of transition-edge sensors for neutrinoless double beta decay searches

The next-generation of cryogenic neutrinoless double-beta decay experiments require increasingly fast readout in order to improve background discrimination. These experiments, operated as cryogenic calorimeters at ∼ 10 mK, are usually read out by high-impedance neutron transmutation doped (NTD) thermistors, which provide good energy resolution, but are limited by ∼ 1 ms response times. Superconducting detectors, such as transition-edge sensors (TESs) with a time resolution of ∼ 100 μs, offer superior timing performance over NTD semiconductor bolometers. To make this technology viable for an application to a thousand or more channels, multiplexed readout is necessary in order to minimize the thermal load and radioactive contamination induced by the readout. Frequency-domain multiplexing readout (fMUX) for TESs, previously developed at Berkeley Lab and McGill University, is currently in use for mm-wave telescopes with detector sampling rates in the order of 100 Hz. We demonstrate a new readout system, based on the McGill/Berkeley digital fMux readout, to satisfy the higher bandwidth and noise requirements of the next generation of TES-instrumented cryogenic calorimeters. Each multiplexing readout module comprises 10 superconducting resonators in the 1–5 MHz range and a DC superconducting quantum interference device (DC-SQUID), interfaced to high-speed field programmable gate array (FPGA)-based electronics for digital signal processing and low-latency SQUID feedback. The new readout samples detectors at 156 kHz, three orders of magnitude faster than its cosmology-oriented predecessor, and demonstrates a stable feedback bandwidth of 3 kHz in a real TES-based system.

47 OTHER INSTRUMENTATION↗

Timing reconstruction utilising multiple detection subsystems at the Short-Baseline Near Detector experiment

The Short-Baseline Near Detector (SBND) is the near detector of the Short-Baseline Neutrino Program, located only 110 m away from the Booster Neutrino Beam (BNB) target at Fermilab (Illinois, USA). SBND employs key detection technologies: a 112-ton Liquid Argon Time Projection Chamber for ionisation electrons, an advanced Photon Detection System (PDS) made up of photomultiplier tubes and X-ARAPUCAs for scintillation light, and a 4π coverage of Cosmic Ray Taggers (CRTs) for cosmic muons. This setup offers an exceptional energy, spatial and timing reconstruction of neutrino interactions. In this poster, we present ongoing timing reconstruction efforts of the PDS and CRTs, as well as combining complementary information across multiple detection subsystems to improve the timing resolution. This results in nanosecond level timing information that can be leveraged as an analysis tool, including the reconstruction of the BNB substructure to accept or reject signals detected in-between neutrino bunches as well as a timing-based discrimination for cosmic rejection.

Corallo, Annalea [INFN, Ferrara]↗

Development of Multiresolution Capabilities for the Holistic Energy Resource Optimization Network (HERON) tool A progress update

INL researchers work on technoeconomic analyses for integrated energy systems (IES) using the Framework for Optimization of ResourCes and Economics (FORCE). Within FORCE, researchers use the Holistic Energy Resource Optimization Network (HERON) tool to conduct optimization of grid portfolios under uncertain market conditions. These optimizations determine optimal capacities for all IES components and strategies for resource dispatch which maximize some economic metric (e.g., net present value). Resource dispatch occurs on finer timescales (typically hours) and thus are asked to respond to a given time series (e.g. hourly load demand profiles for a grid, or pre-determined electricity prices). Volatile and complex bidding dynamics as well as poorly forecasted weather events within deregulated markets add uncertainty to the time series; FORCE can address this uncertainty by training a reduced order model on historical time series and generate unique synthetic time series which represent individual scenarios or realizations of the market. The IES configuration can be simulated under these different sampled realizations and a stochastic optimization is conducted which optimizes the expected value of the desired economic metric. The training of a synthetic time series generator is limited by the chosen time resolution; dynamics can occur on different time scales. Seasonal demand trends can dominate faster dynamical events (such as power outages from certain sectors or severe weather events) which might not get captured correctly by the trained model. In this report, we investigate different ways of addressing the training and generation of time series on multiple time scales using three main algorithms: wavelet decomposition, dynamic mode decomposition, and generative adversarial networks for time series. We demonstrate a time series analysis that yields information on not just the frequency space but also temporal space: where a fast Fourier transform can provide what frequencies dominate, the new algorithms can provide when the frequencies dominate as well. These analyses can help improve IES optimization by allowing researchers to couple simulations at different timescales when it is most needed - seasonal, day-ahead, and real time optimization - with greater computational efficiency. Future work will include implementation of a subset of the proposed algorithms into the FORCE toolset and application of these analyses into multiple timescale optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Two 28-nm front-end ASICs for ultra-fine spatial resolution and precision timing to be 3D integrated with 12 LGADs

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (about 10 µm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present two 28 nm CMOS ASIC prototypes, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

Two 28-nm front-end ASICs for ultra-fine spatial resolution and precision timing to be 3D integrated with 12 LGADs

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (about 10 µm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present two 28 nm CMOS ASIC prototypes, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

Distribution Function Instead of Steady-State Assumption in Time-Series Simulation

The quasi-steady-state assumption in time-series simulation is inadequate to model phenomena of interest to energy system integration such as inverter clipping, sell-back of excess electricity to a utility and utility hosting capacity, and battery throughput. Researchers are working on stochastic modeling, higher-resolution time series data, and machine learning approaches to address this need. This poster describes a distribution function that allows a maximum value, minimum value, and shape to the curve that can vary within each time-step based only on data inputs at the resolution of that time step (eg. Hourly). The distribution function is not used to synthesize high-resolution data, rather scalar integrals are used to calculate the quantities of interest within each time step. The form of the distribution function shows significant reduction in error when compared to 1 minute data and commercial software employing the distribution function (HOMER Pro version 14.3 and higher) shows a much improved estimate of inverter clipping in an example.

battery↗

Decoding Golden Eagle Movement Behavior from High-Resolution, Variable-Rate Telemetry Data Through Bayesian Filtering

The recent advances in animal tracking technology have enabled the collection of a vast amount of in situ data regarding the movement of wildlife at high spatiotemporal resolution. These data are usually available at variable time resolutions and contains noise (error) originating from GPS fixes. Decoding movement characteristics, particularly of flying animals, from telemetry data while handling these factors is a challenging yet important task for conservation purposes. Typically, this task is broken into two subtasks: resampling, and model calibration. The resampling subtask converts the variable rate positional data into a constant time interval data, while the model calibration subtask uses the resampled data to tune time-invariant parameters of the proposed models. For telemetry data at high temporal resolutions (order of 1 second), it is very challenging to decouple noise from actual movements using interpolation-based resampling techniques. Any errors introduced during resampling can significantly alter the the calibration and prediction attributes of the movement model. We address this problem through a unified Bayesian state-space framework that can handle both the resampling and calibration tasks in a single step. In addition, we use the speed and heading of the bird from telemetry data to regularize the position information of the bird. We use a Kalman filtering approach to include these nonlinearly related motion parameters within the state space framework. We cross-validated to quantify how this inclusion affects the model performance in estimating true bird movements. The relationship between the true state of the bird and environmental and topographical covariates is then represented parametrically. These parameters are then tuned using stochastic sampling strategies like Markov Chain Monte Carlo (MCMC). We use the telemetry data collected from golden eagles in the western USA to demonstrate the applicability of this approach to build a predictive, probabilistic movement model. Our preliminary results show that this approach provides improved predictive performance in terms of capturing higher-order motion parameters such as angular and horizontal accelerations, which may have simpler and more direct relationships with environmental covariates than corresponding speeds. In this talk, we will demonstrate how this state-space approach benefits the prediction capabilities of a movement model in simulating golden eagle paths through a wind power plant in Wyoming given certain atmospheric conditions. The model outcomes are aimed at informing mitigation strategies that can minimize the potential for collisions of golden eagles with wind turbines.

Bayesian methods↗

Time-Resolved Grazing Incidence X-Ray Absorption Spectroscopy for the In Situ Investigation of the Initial Stages of Sputter-Deposited Copper Thin Films

The sputter deposition and the growth of thin copper films on float glass substrates are in situ studied using grazing incidence, reflection mode X-ray absorption fine structure spectroscopy with subsecond time resolution. The experimental data are compared with model calculations, assuming the presence of crystalline, face-centered cubic metallic Cu nanostructures. From a detailed analysis of the measured spectra, the film thickness as well as the surface roughness is determined, leading to a detailed understanding of the films growth as a function of the sputter deposition time. In particular, different stages of film growth can clearly be distinguished from the fits of the experimental data. The results suggest the formation of isolated, approximately nm-sized copper clusters in the initial phase of the film deposition for the first few seconds, a coalescence phase with a nominal thickness of ≈1.5–2.8 nm, constant roughness of about 1.4 nm for the subsequent ≈5 s, and finally 3D growth of the Cu crystallites in the film for later stages of film growth. Further prospects of the methodology are given.

36 MATERIALS SCIENCE↗