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DOE OSTI2023

Reaction nanoscopy of ion emission from sub-wavelength propanediol droplets

Abstract Droplets provide unique opportunities for the investigation of laser-induced surface chemistry. Chemical reactions on the surface of charged droplets are ubiquitous in nature and can provide critical insight into more efficient processes for industrial chemical production. Here, we demonstrate the application of the reaction nanoscopy technique to strong-field ionized nanodroplets of propanediol (PDO). The technique’s sensitivity to the near-field around the droplet allows for the in-situ characterization of the average droplet size and charge. The use of ultrashort laser pulses enables control of the amount of surface charge by the laser intensity. Moreover, we demonstrate the surface chemical sensitivity of reaction nanoscopy by comparing droplets of the isomers 1,2-PDO and 1,3-PDO in their ion emission and fragmentation channels. Referencing the ion yields to gas-phase data, we find an enhanced production of methyl cations from droplets of the 1,2-PDO isomer. Density functional theory simulations support that this enhancement is due to the alignment of 1,2-PDO molecules on the surface. The results pave the way towards spatio-temporal observations of charge dynamics and surface reactions on droplets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

RiverPIXELS: paired Landsat images and expert-labeled sediment and water pixels for a selection of rivers v1.0

RiverPIXELS contains GeoTIFFs of hand-labeled water and sediment pixels from Landsat images containing rivers. Each of the 104 labeled patches contains 256 x 256 Landsat pixels (30 meter resolution). Our aim in releasing RiverPIXELS is to provide an "off-the-shelf" training and testing dataset for building machine-learned models to automatically identify rivers from multispectral imagery. While a number of trained models and/or surface water products already exist, RiverPIXELS aims for pixel-level accuracy in order to precisely identify river boundaries in particular. Our selection of rivers is heavily Arctic, but we include tropical and temperate rivers as well. Patches are provided for the Colville (7), Indigirka (6), Kolyma (4), Ucayali (54), Waitaki (21), and Yana (12) Rivers. For each patch, all surface water pixels are labeled (1) and all in-channel sediment pixels are labeled (2). Sediments not in-channel are considered part of the land (0) class. RiverPIXELS also includes paired surface water data from the Global Surface Water dataset that may be useful as additional features in machine learning models. Each patch therefore contains four aligned GeoTIFFs: labeled, landsat, gswmo, and gswocc.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Tunneling current modulation in atomically precise graphene nanoribbon heterojunctions

Lateral heterojunctions of atomically precise graphene nanoribbons (GNRs) hold promise for applications in nanotechnology, yet their charge transport and most of the spectroscopic properties have not been investigated. Here, we synthesize a monolayer of multiple aligned heterojunctions consisting of quasi-metallic and wide-bandgap GNRs, and report characterization by scanning tunneling microscopy, angle-resolved photoemission, Raman spectroscopy, and charge transport. Comprehensive transport measurements as a function of bias and gate voltages, channel length, and temperature reveal that charge transport is dictated by tunneling through the potential barriers formed by wide-bandgap GNR segments. The current-voltage characteristics are in agreement with calculations of tunneling conductance through asymmetric barriers. We fabricate a GNR heterojunctions based sensor and demonstrate greatly improved sensitivity to adsorbates compared to graphene based sensors. This is achieved via modulation of the GNR heterojunction tunneling barriers by adsorbates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Reactions of atomic thorium and uranium cations with CF 4 studied by guided ion beam tandem mass spectrometry

The fundamental chemistry of the actinides continues to be an area of interest because of their use in nuclear fuel cycles. Here, the kinetic energy dependences of the reactions of thorium and uranium cations with CF 4 were studied using guided ion beam tandem mass spectrometry. The products observed include AnF x + (An = Th or U, x = 1-3) and CF y + (y = 1-3). Although most reactions are exothermic according to literature thermochemistry, all cross sections display strong endothermic features indicating a restriction in the reactivity at low energies. For both actinides, only the AnF + + CF 3 product channel is observed at low energies; however, its formation proceeds very inefficiently. Furthermore, these results indicate that the reactions of Th + and U + with CF 4 are not thermodynamically driven and suggest that the low-energy reactivity results from precise alignment of the reactants.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Improving deep learning-based protein distance prediction in CASP14

Abstract Motivation Accurate prediction of residue–residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. The input features for the deep learning method include co-evolutionary features as well as other sequence-based features derived from multiple sequence alignments (MSAs). Three alignment methods are used with multiple protein sequence/profile databases to generate MSAs for input feature generation. Based on different configurations and training strategies of the deep learning method, five MULTICOM distance predictors were created to participate in the CASP14 experiment. Results Benchmarked on 37 hard CASP14 domains, the best performing MULTICOM predictor is ranked 5th out of 30 automated CASP14 distance prediction servers in terms of precision of top L/5 long-range contact predictions [i.e. classifying distances between two residues into two categories: in contact (<8 Angstrom) and not in contact otherwise] and performs better than the best CASP13 distance prediction method. The best performing MULTICOM predictor is also ranked 6th among automated server predictors in classifying inter-residue distances into 10 distance intervals defined by CASP14 according to the precision of distance classification. The results show that the quality and depth of MSAs depend on alignment methods and sequence databases and have a significant impact on the accuracy of distance prediction. Using larger training datasets and multiple complementary features improves prediction accuracy. However, the number of effective sequences in MSAs is only a weak indicator of the quality of MSAs and the accuracy of predicted distance maps. In contrast, there is a strong correlation between the accuracy of contact/distance predictions and the average probability of the predicted contacts, which can therefore be more effectively used to estimate the confidence of distance predictions and select predicted distance maps. Availability and implementation The software package, source code and data of DeepDist2 are freely available at https://github.com/multicom-toolbox/deepdist and https://zenodo.org/record/4712084#.YIIM13VKhQM. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Magnetic interactions and excitations in SrMnSb 2

The magnetic interactions in the antiferromagnetic (AFM) Dirac semimetal candidate SrMnSb 2 are investigated using ab initio linear response theory and inelastic neutron scattering (INS). Our calculations reveal that the first two nearest in-plane couplings (J 1 and J 2 ) are both AFM in nature, indicating a significant degree of spin frustration, which aligns with experimental observations. The orbital resolution of exchange interactions shows that J 1 and J 2 are dominated by direct and superexchange, respectively. In a broader context, a rigid-band model suggests that electron doping fills the minority spin channel and results in a decrease in the AFM coupling strength for both J 1 and J 2 . To better compare with INS measurements, we calculate the spin-wave spectra within a linear spin-wave theory, utilizing the computed exchange parameters. Although the calculated spin-wave spectra somewhat overestimate the magnon bandwidth, they exhibit overall good agreement with measurements from INS experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

RFSoC based digital low level RF control firmware and software suite (mimo_llrf) v1.0

It features a framework of a firmware and software architecture in support of building a digital low-level RF control system for accelerators, where precised digital RF generation and measurement are needed across many RF channels. It primarily supports the Xilinx RFSoC chips (xczu48dr, xczu47dr, xczu29dr) and their evaluation boards (zcu208, zcu216), for a highly integrated solution enabling the need for synchronous low-level RF systems, including: multi-tile synchronization, external reference for sampling clocks, deterministic delay, aligned NCO phase for digital mixers, and built-in EPICS IOC.

Du, Qiang [Lawrence Berkeley National Laboratory (↗

DOE OSTI2021

Observation of new excited ${B} ^0_{s}$ states

A structure is observed in the ${B} ^{\pm }{K} ^{\mp }$ mass spectrum in a sample of proton–proton collisions at centre-of-mass energies of 7, 8, and 13 TeV, collected with the LHCb detector and corresponding to a total integrated luminosity of 9$\,\text {fb} ^{-1}$. The structure is interpreted as the result of overlapping excited ${B} ^0_{s}$ states. With high significance, a two-peak hypothesis provides a better description of the data than a single resonance. Under this hypothesis the masses and widths of the two states, assuming they decay directly to ${B} ^{\pm }{K} ^{\mp }$, are determined to be $\begin{aligned} m_1&= 6063.5 \pm 1.2 \text { (stat)} \pm 0.8\text { (syst)}\,\text {Me}\text {V}, \\ \Gamma _1&= 26 \pm 4 \text { (stat)} \pm 4\text { (syst)}\,\text {Me}\text {V}, \\ m_2&= 6114 \pm 3 \text { (stat)} \pm 5\text { (syst)}\,\text {Me}\text {V}, \\ \Gamma _2&= 66 \pm 18 \text { (stat)} \pm 21\text { (syst)}\,\text {Me}\text {V}. \end{aligned}$ Alternative values assuming a decay through ${B} ^{*\pm }{K} ^{\mp }$, with a missing photon from the $B^{*\pm } \rightarrow B^{\pm }\gamma $ decay, which are shifted by approximately 45 $\,\text {Me}$V, are also determined. The possibility of a single state decaying in both channels is also considered. The ratio of the total production cross-section times branching fraction of the new states relative to the previously observed $B_{s2}^{*0}$ state is determined to be $0.87 \pm 0.15 \text { (stat)} \pm 0.19 \text { (syst)}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BeyondPlanck project in terms of motivation, methodology and main products, and provide a guide to a set of companion papers that describe each result in fuller detail. Building directly on experience from ESA's Planck mission, we implement a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a joint posterior distribution P(omega|d), where omega represents the set of all free instrumental (gain, correlated noise, bandpass etc.), astrophysical (synchrotron, free-free, thermal dust emission etc.), and cosmological (CMB map, power spectrum etc.) parameters. Some notable advantages of this approach are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-l CMB polarization reconstruction, paying special attention to the LFI 44 GHz channel. We find evidence of significant residual systematic effects that are still not accounted for in the current processing, but must be addressed in future work. These include a break-down of the 1/f correlated noise model at 30 and 44 GHz, and scan-aligned stripes in the Southern Galactic hemisphere at 44 GHz. On the Northern hemisphere, however, we find that all results are consistent with the LCDM model, and we constrain the reionization optical depth to tau = 0.067 +/- 0.016, with a low-resolution chi-squared probability-to-exceed of 16%. The marginal CMB dipole amplitude is 3359.5 +/- 1.9 uK. (Abridged.)

Andersen, KJ↗

DOE OSTI2025

Comparative experimental study of heat transfer processes in accumulation energy recovery exchangers

In this study, an experimental comparison between three different energy accumulating ceramic heat exchangers for energy recovery in ventilation systems was presented. The units were selected to represent three different approaches on the energy recovery process: honeycomb structure with more accumulation mass (more energy can be stored in one unit)- Unit 1.1, honeycomb structure with lower accumulation mass- Unit 1.2, and a rectangular structure with expanded heat transfer surface- Unit 1.3. The achieved results are useful for the future application of such units in ventilation systems. It was established that all evaluated units demonstrated an acceptable effectiveness of thermal energy recovery from the exhaust air. Their average energy recovery efficiency ranged between 70 % and 80 %, aligning with expected performance benchmarks for regenerative heat exchangers employed in contemporary mechanical ventilation systems. It was also established that the factor which has the highest impact on thermal effectiveness is the heat transfer surface available in the tested heat exchangers. Units with the highest number of channels (i.e., with the highest amount of single channel walls, which can be used for heat transfer) achieve the highest thermal effectiveness. However, higher thermal effectiveness can negatively affect the ventilation potential of the units. Unit 1.3, which was characterized by the highest thermal efficiency, was also characterized by the lowest achievable flow rate. It was also found that the important technical aspect that should be taken into account when analyzing accumulation energy recovery units is also the fluctuation of the supply air temperature. The ability to ensure minimal temperature fluctuations is a significant operational advantage, as it ensures a higher level of safety at lower outside temperatures.

Energy recovery↗

DOE OSTI2025

Single-nuclei transcriptome analysis of IgM+ cells isolated from channel catfish (Ictalurus punctatus) spleen

Catfish production is the primary aquaculture sector in the United States, and the key cultured species is channel catfish (Ictalurus punctatus). The major causes of production losses are pathogenic diseases, and the spleen, an important site of adaptive immunity, is implicated in these diseases. To examine the channel catfish immune system, single-nuclei transcriptomes of sorted and captured IgM + cells were produced from adult channel catfish. Three channel catfish (~1 kg) were euthanized, the spleen dissected, and the tissue dissociated. The lymphocytes were isolated using a Ficoll gradient and IgM + cells were then sorted with flow cytometry. The IgM + cells were lysed and single-nuclei libraries generated using a Chromium Next GEM Single Cell 3’ GEM Kit and the Chromium X Instrument (10x Genomics) and sequenced with the Illumina NovaSeq X Plus sequencer. The reads were aligned to theI. punctatusreference assembly (Coco_2.0) using Cell Ranger, and normalization, cluster analysis, and differential gene expression analysis were carried out with Seurat. Across the three samples, approximately 753.5 million reads were generated for 18,686 cells. After filtering, 10,637 cells remained for the cluster analysis. The cluster analysis identified 16 clusters which were classified as B cells (10,276), natural killer-like (NK-like) cells (178), T cells or natural killer cells (45), hematopoietic stem and progenitor cells (HSPC)/megakaryocytes (MK) (66), myeloid/epithelial cells (40), and plasma cells (32). The B cell clusters were further defined as different populations of mature B cells, cycling B cells, and plasma cells. The plasma cells highly expressedighmand we demonstrated that the secreted form of the transcript was largely being expressed by these cells. This atlas provides insight into the gene expression of IgM + immune cells in channel catfish. The atlas is publicly available and could be used garner more important information regarding the gene expression of splenic immune cells.

Immunology↗

DOE OSTI2025

Leveraging FPGA Advantages for Quicker Data Processing for LBNF

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, Jacob↗

DOE OSTI2025

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

Rossel, A. Jacob [Fermilab; Unlisted]↗

DOE OSTI2024

Interpretations of the ATLAS measurements of Higgs boson production and decay rates and differential cross-sections in pp collisions at $\sqrt{s}$ = 13 TeV

Measurements of the Higgs boson production times decay rates and differential cross-sections have recently been performed by the ATLAS experiment in several decay channels using up to 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV recorded at the Large Hadron Collider. This paper presents multiple interpretations of these Higgs boson measurements. Measurements of production-mode cross-sections, simplified template cross-sections and fiducial differential cross-sections in different decay channels are reparameterised in terms of the impact of Standard Model effective field theory operators, and constraints are reported on the corresponding Wilson coefficients. Production and decay rate measurements are interpreted in UV-complete extensions of the Standard Model, namely the two-Higgs-doublet model (2HDM) near the alignment limit and the Minimal Supersymmetric Standard Model (MSSM) for various MSSM benchmark scenarios. The constraints on the 2HDM parameters (cos(β - α), tanβ) and the MSSM parameters (m A , tanβ) are complementary to those obtained from direct searches for additional Higgs bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Multichannel Fiber-Optic Silicon Fabry–Pérot Interferometric Bolometer System for Plasma Radiation Measurements

A single-channel fiber-optic bolometer system based on a high-finesse silicon Fabry–Pérot interferometer (FPI) was previously reported, intended to measure plasma radiation from the magnetically confined fusion chamber. Recently, we developed a multichannel fiber-optic bolometer system with five bolometers multiplexed using a coarse wavelength division multiplexer (CWDM) and interrogated with a white-light system involving a superluminescent light-emission diode source and a high-speed spectrometer. One of the bolometers was used as the reference bolometer to compensate for the ambient temperature variations, and the other four bolometers were used for radiation measurement. The bolometers have a simple structure with a silicon pillar at the end of the single-mode fiber and a gold disk on the other side of the silicon pillar. They are also easy to fabricate without stringent requirements on the optical alignment. Analysis of the system optimization was performed to improve the noise performance and to mitigate the vibration effect that may present in the practical application. The system had a significantly enhanced measurement range compared to the previous high-finesse FPI bolometer system for measuring radiation. Test results performed in air using a 405 nm laser as the radiation source showed that the temperature resolution and the noise-equivalent power density of the sensing bolometers connected to each channel of the CWDM were, respectively, ~0.4 mK and ~0.1 W/m2, with a time constant of ~220 ms, which is comparable to the previous more complicated fiber-optic bolometer systems based on high-finesse FPIs that were interrogated using wavelength-scanning lasers.

Uddin, Nezam↗

DOE OSTI2025

Genesis of a novel high-rate composite manufacturing process using large-scale additive manufacturing – compression molding (AM-CM) system: Possibilities and limitations

Oak Ridge National Laboratory (ORNL) has developed a highly automated manufacturing process for thermoplastic composites that combines the benefits of Additive Manufacturing and Compression Molding (AM-CM) to produce high-performance functional composite structures at automotive production rates. Here, the AM-CM process creates highly precise preforms by additively placing extruded fiber-filled polymers (with controlled fiber orientations and multi-material configurations) in the desired mold location before undergoing a secondary compression molding process immediately before the preform cools down. Preforms can be in the form of short, long-chopped, or continuous fiber-filled thermoplastic polymers (e.g., CF/GF-filled ABS, PC, LM-PAEK, etc.). The AM-CM process combines the benefits of controlled fiber alignment, that is only achievable in AM-printed parts with the classical CM process, which eliminates porosity and good surface finish. A preform created using AM-CM can integrate various materials to enable additional architectural functionalities, including over-molding, selective stiffening, and the incorporation of electrically or thermally conductive channels. All these advantages come with a fast part production cycle time. The AM-CM process can manufacture multi-material, multi-functional parts in under 3 min, starting from raw material (pellets) to the final product. The novel AM-CM process offers superior microstructural control and enhanced multi-functionality previously unattainable with any other traditional high-rate thermoplastic composite manufacturing method. This work covers the manufacturing concept, system development, materials and applications of AM-CM process in detail.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗

DOE OSTI2024

Triplet Management at Ligand-Perovskite Interface to Enhanced Photovoltaics Performance

Aromatic organic molecules are widely used as passivators in perovskite solar cells (PSCs). Efforts have been devoted to improving the energy alignments, band edge states, and defect passivation functionalities. However, potential energy loss through triplet states in such conjugated molecules has not been investigated in the past. Here, we report the observation of charge transfer from FAPbI 3 to the triplet state of a pyrene (Pyr)-based cationic ligand. Such a potential loss channel can be suppressed via delicate triplet management in polycyclic aromatic compounds. Interestingly, a subtle structural modification from Pyr to the triphenylene (TP) core gave rise to shallower triplets that prohibit electron transfer from perovskites. This strategy has led to TP-passivated PSCs achieving an enhanced power conversion efficiency (PCE) of 24.69% from 23.10% in Pyr-passivated counterparts. Moreover, the devices retained above 80% initial PCE after 4000 h of light soaking, which likely benefited from the reduced triplet electron trapping at the ligand-perovskite interface.

14 SOLAR ENERGY↗