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DOE OSTI2025

Harnessing land-atmosphere interactions to enhance subseasonal-to-seasonal predictability

2025 Advancing Understanding of Land-Atmosphere Interactions and Processes on S2S Predictability Workshop What: 227 registered workshop participants gathered in person (43%) and online (57%) to discuss state-of-the-art scientific understanding and modeling of land-atmosphere interactions and related processes in the context of subseasonal-to-seasonal (S2S) predictability. Topics covered sources of S2S predictability, land model initialization methods, model diagnosis and evaluation metrics, AI/ML analysis and applications, and coordination of future community multi-model S2S forecast focused experiments. To advance the science, this community workshop, organized by NSF NCAR, NOAA, NASA, and DOE, aimed to 1) identify process- and application-oriented metrics for assessing S2S prediction skill and 2) develop experimental protocols for coordinated experiments to isolate, quantify, and understand the role of land-atmosphere interactions in S2S predictability. When: June 16-18, 2025 Where: Boulder, CO, USA, and online.

Land-Atmosphere Interaction↗

DOE OSTI2024

LANSCE Science Overview [Slides]

LANSCE is primarily focused on three science questions for NNSA and contributes to several other programs. We will primarily consider the NNSA questions: (1) How can we advance our understanding of dynamic material behavior using focused experiments? (2) What tools are needed to address Advanced Manufacturing and Aging? (3) How do we constrain the nuclear reaction networks involved in weapons?

36 MATERIALS SCIENCE↗

DOE OSTI2024

The Radical Atom: Mechanosynthetic 3D Printing of an Atomically Precise SPM Tip

This research effort sought to overcome current limitations in scanning probe-based atomic manipulation to enable atomically precise manufacturing (APM). Previous theoretical and experimental works on atom by atom and molecule by molecule fabrication of precise structures are limited to essentially to two-dimensions. APM will enable a paradigm shift in 21st century manufacturing practices in which every single atom in a electronic chip, device or machine can be placed in an exact and predefined position in three-dimensions. By providing a general method for generating reproducible SPM tip structure, this project will drive forward the entire field of atomically precise scanning probe microscopy, opening the door to positional control of nearly arbitrary covalent chemistry. Such control could, for example, be used in applications such as novel 2.5 or 3D microchip fabrication. The creation of a unique manufacturing method through APM has the potential to impact technologies at the theoretical limits of performance, weight, and utility including: solid-state quantum and spintronic computing systems, high efficiency optical antenna, solar power systems, defect engineered materials and extremely efficient catalysts. Although this experiment focused on pick-and-place non-scalable APM, the better understanding of the chemistry is crucial to the eventual goal of scalable APM. To place individual atoms into a specified location is a seminal aspiration of researchers and engineers in the many fields and may have early premium applications in medical devices and microelectronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Vibrational Signatures of Electronic Properties in Renewable-Energy Catalysis

The objective of this research program is to discover and develop new approaches for ab initio computational simulations of molecular motion. Specifically, this program aims to decipher the connection between the underlying electronic structure and the accordant molecular vibrations in reactive ions and radicals for renewable-energy purposes. Recent experimental progress in ion sources and optical spectroscopies has unearthed considerable new inner-sphere detail for these complexes, but the connection between these spectral signatures and mechanistic information often remains elusive, to the continued frustration of experimentalists. For this purpose, new anharmonic vibrational frequency methods, along with a publicly deployed software package, will be developed. Working closely with committed experimental collaborators, this conceptual and computational framework will be used to explain the results of new spectroscopy experiments, focusing specifically on the inner-shell mechanisms of renewable-energy catalysis. The oxidation half of catalytic water-splitting chemistry will be a central focus, along with fundamental studies of the manner in which strong ions and radicals activate solvent as a chemical species. The resulting products of the research program will include openly available software and algorithms for the ab initio simulation of challenging vibrational spectra, as well as critical mechanistic insight into energy-focused catalytic processes that are opaque to other existing analytical techniques.

42 ENGINEERING↗

DOE OSTI2025

GEANT3 simulations for a beryllium Moderator for the Neutron Target Demonstrator (NTD)

Measurements of neutron-induced reactions, particularly on short-lived nuclei, are crucial for nuclear astrophysics and applications. The Neutron Target Demonstrator (NTD) aims to address this by using a strong mod erated spallation neutron source coupled with an ion storage ring. This work investigates the potential of improving the neutron moderator, a key component of the NTD. Using GEANT3 simulations, we compare the performance of the existing 80 cm carbon moderator with a new moder ator design, which utilizes beryllium pieces available at LANL to form a core surrounded by carbon. Simulations were performed 800 MeV pro tons incident on a tungsten target. The results demonstrate that the beryllium-core moderator increases the density of moderated neutrons within the central beam pipe by roughly a factor 4 compared to the pure carbon moderator. This enhancement makes the beryllium-core design a very promising option for future experiments focused on neutron-induced measurements in inverse kinematics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

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↗

DOE OSTI2025

Measuring the Muon Neutrino Magnetic Moment in the NOvA Near Detector

Measuring an enhanced neutrino magnetic moment would be a clear indication of physics beyond the Standard Model, shedding light on the correct beyond Standard Model theory or the potential Majorana nature of neutrinos. It would manifest in the NOvA near detector as an excess of neutrino-on-electron elastic scattering interactions at low electron recoil energies. Leveraging an intense and highly pure muon neutrino beam, along with a finely segmented liquid scintillator detector technology specifically designed for electromagnetic shower separation, enables NOvA to achieve a potentially world-leading sensitivity in probing the effective muon neutrino magnetic moment. This analysis, based on neutrino data collected between 2014 and 2021, corresponding to an exposure of $13.8\times10^{20}$ protons-on-target, yields a result consistent with the Standard Model-only hypothesis with a p-value of 0.31. An upper limit on the effective muon neutrino magnetic moment is set at $\mu_{\nu_\mu}<19.1\times 10^{-10}\mu_B$ at $90\%$ confidence level. Despite facing statistical limitations stemming from low cross section of the signal process, systematic uncertainties have a significant impact on this result. To address these challenges, the NOvA Test Beam experiment focuses on mitigating some of the largest systematic uncertainties within NOvA by investigating particle interactions and energy deposition in a small-scale replica NOvA detector. This thesis describes the calibration of the NOvA Test Beam detector, which is a crucial step in analysing the Test Beam data before they can be utilised to reduce NOvA systematic uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Quality Assurance of the Irradiated EBR-II Metallic Fuels Data

The U.S. DOE-NE’s Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) and the NE-4 Advanced Fuels Campaign (AFC) have jointly undertaken efforts to qualify post-irradiation examination (PIE) data for Experimental Breeder Reactor II (EBR-II) and Fast Flux Test Facility (FFTF) metallic fuels. Among the thousands of PIE datasets in the Metallic Fuels Irradiation & Physics Database (FIPD), data from selected EBR-II experiments have been prioritized as the most valuable to the U.S. nuclear industry for licensing activities related to metallic fuel-based advanced fast reactors. This report summarizes the general data qualification progress of the EBR-II and FFTF experiments, with focus on the selected EBR-II experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment

The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO 2 -emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.

Environmental sciences↗

DOE OSTI2025

Mechanical cosmology: Simulating scalar fluctuations in expanding universes using synthetic mechanical lattices

Inspired by recent advances in observational astrophysics and continued explorations in the field of analog gravity, we discuss the prospect of simulating models of cosmology within the context of synthetic mechanical lattice experiments. We focus on the physics of expanding universe scenarios described by the Friedmann-Lemaître-Robertson-Walker (FLRW) metric. Specifically, quantizing scalar fluctuations in a background FLRW spacetime leads to a quadratic bosonic Hamiltonian with temporally varying pair production terms. Here we present a mapping that provides a one-to-one correspondence between these classes of cosmology models and feedback-coupled mechanical oscillators. As proof of principle, we then perform experiments on a synthetic mechanical lattice composed of such oscillators. We simulate two different FLRW expansion scenarios with universes dominated by vacuum energy and matter and discuss our experimental results. Published by the American Physical Society 2025

Rhyno, Brendan (ORCID:0000000235266998)↗

DOE OSTI2026

Intrinsic nonlocality of spin- and polarization-resolved probabilities in strong-field quantum electrodynamics

Spin and polarization are central to precision tests of fundamental physics and for interpreting radiation from astrophysical sources and ultraintense laser-matter experiments. Here, focusing on the fundamental process of nonlinear Compton scattering, we demonstrate that a key assumption underlying current strong-field quantum electrodynamics models, i.e., that emission can be treated as an instantaneous random event sampled from a local differential rate, is inconsistent once emission angles, electron spin, and/or photon polarization are resolved. Namely, even in strictly constant and uniform fields , the resulting fully differential distribution is sign indefinite, yielding negative inferred probabilities. The physical reason is that the photon emission probability builds up over a finite length of the electron trajectory, the formation region, during which the electron direction changes by roughly the same small angle that defines the radiation cone. Therefore, we put forward a new method where we integrate over this formation region analytically to obtain a physically consistent electron spin and photon polarization model. We show that the implementation of our model is compatible with existing Monte Carlo and particle-in-cell workflows. Simulations of a GeV-class electron-laser collision accessible at current petawatt facilities and of emission in a pulsarlike magnetic field are shown to reveal spin and polarization patterns that differ even qualitatively from state-of-the-art local models. In particular, our new model predicts substantial angle-dependent circular photon polarization where the well-known collinear-emission approach yields none, and a pronounced helicity bias in the recoiling electrons absent from current predictions. These findings have direct implications for upcoming strong-field QED experiments and for interpreting polarized radiation from extreme astrophysical environments.

astrophysical electromagnetic fields↗

DOE OSTI2026

Fundamental chemical physics revealed by scattering reactive open-shell atoms from surfaces

The dynamics of reactive atoms at surfaces are centrally important to areas such as heterogeneous catalysis, corrosion, materials degradation in extreme environments, and plasma etching. Remarkably detailed understanding of dynamical processes at surfaces has been extracted from scattering molecules and inert atoms under well-defined conditions. However, traditional techniques for generating beams of reactive atoms often result in impure mixtures, broad energy distributions, and poorly defined contributions of metastable electronically excited atoms. In this perspective article, we review the state-of-the-art in reactive atom surface scattering with a focus on experiments performed under controlled conditions on well-defined surfaces. We highlight a new technique for controlled state-to-state scattering of polyelectronic atoms from surfaces, based on vacuum ultraviolet photolysis and state-selective ion imaging. The new capabilities provide an avenue for research into the underexplored area of excited state and spin selective chemical dynamics at surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

First light from beam neutrinos on an LAPPD in ANNIE

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is both a physics experiment and a technology testbed for next-generation light-based neutrino detection. In this paper, we report the first demonstration of a fully integrated Large Area Picosecond Photodetector (LAPPD) operating in a running neutrino beam experiment. Particular focus is given to the design, commissioning, and successful deployment of the Packaged ANNIE LAPPD (PAL), a waterproof, self-triggering module incorporating fast waveform digitization and precision timing synchronized to the ANNIE detector subsystems. We identify beam-correlated LAPPD data frames consistent with charged-current neutrino interactions observed in multiple detector subsystems, establishing the first detection of neutrino-induced Cherenkov light with an LAPPD. These results validate the system-level performance of LAPPDs under realistic experimental conditions — including long-term stability, timing synchronization, and event matching with conventional PMT and muon detector systems — marking a critical step toward their deployment in future large-scale neutrino and particle detectors.

Cherenkov detectors↗

DOE OSTI2025

Synthetic tensor gauge fields

Synthetic gauge fields have provided physicists with a unique tool to explore a wide range of fundamentally important phenomena. However, most experiments have focused on synthetic vector gauge fields. The very rich physics brought about by coupling tensor gauge fields to fracton phases of matter remains unexplored in laboratories. Here, we propose schemes to realize synthetic tensor gauge fields that address dipoles instead of single particles. A lattice tilted by a strong linear potential and a weak quadratic potential yields a rank-2 electric field for a dipole formed by a particle-hole pair. Such a rank-2 electric field leads to a new type of Bloch oscillations, which modulates the quadrupole moment and preserves the dipole moment of the system. In higher dimensions, the interplay between interactions and vector gauge potentials imprints a phase to the ring-exchange interaction and thus generates synthetic tensor gauge fields. Such tensor gauge fields make it possible to realize a dipolar Harper-Hofstadter model in laboratories. The resultant dipolar Chern insulators feature chiral edge currents of dipoles in the absence of net charge currents. Published by the American Physical Society 2025

Zhang, Shaoliang (ORCID:000000016635044X)↗

DOE OSTI2024

Concurrent Measurement of O 2 Production and Isoprene Emission During Photosynthesis: Pros, Cons and Metabolic Implications of Responses to Light, CO 2 and Temperature

Traditional leaf gas exchange experiments have focused on net CO 2 exchange (A net ). Here, using California poplar (Populus trichocarpa), we coupled measurements of net oxygen production (NOP), isoprene emissions and δ 18 O in O 2 to traditional CO 2 /H 2 O gas exchange with chlorophyll fluorescence, and measured light, CO 2 and temperature response curves. This allowed us to obtain a comprehensive picture of the photosynthetic redox budget including electron transport rate (ETR) and estimates of the mean assimilatory quotient (AQ = A net /NOP). We found that A net and NOP were linearly correlated across environmental gradients with similar observed AQ values during light (1.25 ± 0.05) and CO 2 responses (1.23 ± 0.07). In contrast, AQ was suppressed during leaf temperature responses in the light (0.87 ± 0.28), potentially due to the acceleration of alternative ETR sinks like lipid synthesis. A net and NOP had an optimum temperature (Topt) of 31°C, while ETR and δ 18 O in O2 (35°C) and isoprene emissions (39°C) had distinctly higher T opt . The results confirm a tight connection between water oxidation and ETR and support a view of light-dependent lipid synthesis primarily driven by photosynthetic ATP/NADPH not consumed by the Calvin–Benson cycle, as an important thermotolerance mechanism linked with high rates of (photo)respiration and CO 2 /O 2 recycling.

H218O labelling↗

DOE OSTI2025

Cloud-atmosphere impacts on the central Arctic surface energy budget (Final Report)

This project investigated how clouds and atmosphere-sea ice interactions shape the central Arctic surface energy budget using observations from the MOSAiC expedition and coordinated model experiments. Analyses focused on three themes. First, a new method applied to thermistor string data revealed that snow thermal conductivity is systematically higher than assumed in most models, strongly influencing conductive heat flux and sea ice growth, especially under clear skies. Second, a full annual cycle of surface energy budget observations, combined with detailed cloud microphysical retrievals, demonstrated how cloud regimes regulate radiative, turbulent, and conductive fluxes, driving seasonal contrasts in sea ice energy balance: in winter, radiative forcing elicits strong turbulent and conductive responses, while in summer excess energy is primarily partitioned into surface melt. Third, these observations were used to evaluate and improve regional and global forecast models. While some models captured key Arctic cloud-radiation states, most exhibited persistent deficiencies in representing liquid-containing clouds, snow-on-sea-ice processes, and flux responses to radiative forcing. Together, these results provide unprecedented benchmarks for understanding coupled Arctic processes, improve parameterizations of snow, sea ice, and cloud interactions, and highlight critical pathways by which atmospheric variability drives sea ice change in a rapidly evolving Arctic system. Lastly, the project was a resounding success, resulting in 38 peer-reviewed publications and dozens of presentations, while also supporting an early career scientist.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Quantification of carbon phases in detonation soot

Soot is a powdery substance composed of solid residues that results from the incomplete combustion of hydrocarbons. Soot holds valuable information because its chemical makeup can provide answers for condensed carbon kinetics in HE detonations by quantitively identifying what carbon species remain. For carbon-rich explosives, this is particularly important because carbon kinetics is a major pathway for energy release. Current efforts have been able to qualitatively identify the carbons and confirm their presence, but we haven’t been able to successfully quantify them. For example, small angle x-ray diffraction has been fielded to qualitatively identify carbon phases as a function of time during a detonation (work by Trevor Willey and Mike Nielson). Other work (ice experiments) has focused on measuring the “effective” static cold curve equation of state (EOS) of the recovered carbon soots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗