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DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes.

16S rRNA↗

DOE OSTI2020

Search for Slow Magnetic Monopoles with the NOνA Far Detector

The magnetic monopole is a hypothetical particle with a magnetic charge. It is an important field configuration in many Grand Unified Theories. Dirac in 1931 derived a charge quantization condition, which suggests that the existence of one magnetic monopole in the universe will explain electric charge quantization. Since then, a search of the elusive particle has begun, and yet all came with negative results. The NO$\nu$A Far Detector is able to probe some of the parameter space for the search for monopoles. To achieve this, two dedicated triggers, one for fast monopoles and the other for slow monopoles, have been developed to record signals. Results for the first 8 months of high-gain slow monopole data were obtained, and a 90\% CL limit was established with no monopole observed. The analysis in this thesis is focused on new data with a higher gain, and we have explored potential improvement in efficiency and improvements in the reconstruction algorithm. We have done this an alysis on Monte-Carlo generated simulated data to establish efficiencies and examined a control set of the new data to understand its differences from the old.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Multitaper Magnitude‐Squared Coherence for Time Series With Missing Data: Understanding Oscillatory Processes Traced by Multiple Observables

To explore the hypothesis of a common source of variability in two time series, observers may estimate the magnitude-squared coherence (MSC), which is a frequency-domain view of the cross correlation. For time series that do not have uniform observing cadence, MSC can be estimated using Welch's overlapping segment averaging. However, multitaper has superior statistical properties to Welch's method in terms of the tradeoff between bias, variance, and bandwidth. The classical multitaper technique has recently been extended to accommodate time series with underlying uniform observing cadence from which some observations are missing. This situation is common for solar and geomagnetic data sets, which may have gaps due to breaks in satellite coverage, instrument downtime, or poor observing conditions. We demonstrate the scientific use of missing-data multitaper magnitude-squared coherence by detecting known solar mid-term oscillations in simultaneous, missing-data time series of solar Lyman α flux and geomagnetic Disturbance Storm Time index. Due to their superior statistical properties, we recommend that multitaper methods be used for all heliospheric time series with underlying uniform observing cadence.

Astro-statistics techniques (1886)↗

DOE OSTI2023

Elastic Moduli: a Tool for Understanding Chemical Bonding and Thermal Transport in Thermoelectric Materials

Abstract The elastic behavior of a material can be a powerful tool to decipher thermal transport. In thermoelectrics, measuring the elastic moduli—directly tied to sound velocity—is critical to understand trends in lattice thermal conductivity, as well as study bond anharmonicity and phase transitions, given the sensitivity of elastic moduli to the chemical bonding. In this review, we introduce the basics of elasticity and explain the origin of high‐temperature lattice softening from a bonding perspective. We then review elasticity data throughout classes of thermoelectrics, and explore trends in sound velocity, anharmonicity, and thermal conductivity. We reveal how experimental sound velocities can improve the accuracy of common thermal conductivity models and present a critical discussion of Grüneisen parameter estimates from elastic moduli. Readers will be equipped with tools to leverage elasticity measurements or calculations to accurately interpret thermal transport trends.

Isotta, Eleonora↗

DOE OSTI2023

Elastic Moduli: a Tool for Understanding Chemical Bonding and Thermal Transport in Thermoelectric Materials

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Rational design of a uranyl metal-organic framework for the capture and colorimetric detection of organic dyes

A new uranyl containing metal-organic framework, RPL-1: [(UO2)2(C28H18O8)] · H2O (RPL for Radiochemical Processing Laboratory), was prepared, structurally characterized, and the solid-state photoluminescence properties explored. The single crystal X-ray diffraction data reveal the structure of RPL-1 consists of two crystallographically unique three dimensional, interpenetrating nets with a 4,3-connected tbo topology. Each net contains large pores with an average width of 22.8 Å and is formed from monomeric, hexagonal bipyramidal uranyl nodes that are linked via 1,2,4,5-tetrakis(4-carboxyphenyl)benzene (TCPB) linkers. The thermal and photophysical properties of RPL-1 were investigated using thermogravimetric analysis and absorbance, fluorescence, and lifetime spectroscopies. The material displays excellent thermal stability and temperature dependent uranyl and TCBP luminescence. The framework is stable in aqueous media and due to the large void space (constituting 76% of the unit cell by volume) can sequester organic dyes, the uptake of which induces a visible change to the color of the material.

Surbella, Robert G.↗

DOE OSTI2020

On the decaying-sterile-neutrino solution to the electron (anti)neutrino appearance anomalies

We explore the hypothesis that the unexplained data from LSND and MiniBooNE are evidence for a new, heavy neutrino mass-eigenstate that mixes with the muon-type neutrino and decays into an electron-type neutrino and a new, very light scalar particle. We consider two different decay scenarios, one with Majorana neutrinos, one with Dirac neutrinos; both fit the data equally well. We find a reasonable, albeit not excellent, fit to the data of MiniBooNE and LSND. The decaying-sterile-neutrino hypothesis, however, cleanly evades constraints from disappearance searches and precision measurements of leptonic meson decays, as long as $1~{\rm MeV}\gtrsim m_4\gtrsim 10$~keV. The SBN program at Fermilab should be able to definitively test the decaying-sterile-neutrino hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Synchrotron-based diffraction-enhanced imaging and diffraction-enhanced imaging combined with CT X-ray imaging systems to image seeds at 30 keV

Utilized the upgraded Synchrotron-based non-destructive Diffraction-enhanced imaging and Diffraction-enhanced imaging coupled with CT X-ray imaging systems to image the chickpea seeds, to enhance the contrast in plant root architecture, visibility of fine structures of root architecture growth and some aspects of physiology at acceptable level. DEI-CT images were acquired with 30 keV synchrotron X-rays. A series of DEI-CT slices were assembled together, to form a 3D data set. DEI-CT images explored more structural information and morphology. Noticed detailed anatomical, physiological observations, and contrast mechanisms. Furthermore, with these systems, some of the complex plant traits, root morphology, growth of laterals and subsequent laterals can be visualized directly.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Genome-wide fetalization of enhancer architecture in heart disease

Heart disease is associated with re-expression of key transcription factors normally active only during prenatal development of the heart. However, the impact of this reactivation on the regulatory landscape in heart disease is unclear. Here, we use RNA-seq and ChIP-seq targeting a histone modification associated with active transcriptional enhancers to generate genome-wide enhancer maps from left ventricle tissue from up to 26 healthy controls, 18 individuals with idiopathic dilated cardiomyopathy (DCM), and five fetal hearts. Healthy individuals have a highly reproducible epigenomic landscape, consisting of more than 33,000 predicted heart enhancers. In contrast, we observe reproducible disease-associated changes in activity at 6,850 predicted heart enhancers. Combined analysis of adult and fetal samples reveals that the heart disease epigenome and transcriptome both acquire fetal-like characteristics, with 3,400 individual enhancers sharing fetal regulatory properties. We also provide a comprehensive data resource (http://heart.lbl.gov) for the mechanistic exploration of DCM etiology.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Kernel methods for evolution of generalized parton distributions

Generalized parton distributions (GPDs) characterize the 3-dimensional structure of hadrons, combining information about their internal quark and gluon longitudinal momentum distributions and transverse position within the hadron. The dependence of GPDs on the factorization scale Q 2 allows one to connect hard exclusive processes involving GPDs at disparate energy and momentum scales, which is needed in global analyses of experimental data. Here, in this work, we explore how finite element methods can be used to construct fast and differentiable Q 2 evolution codes for GPDs in momentum space, which can be used in a machine learning framework. We show numerical benchmarks of the methods' accuracy, including a comparison to an existing evolution code from PARTONS/APFEL++, and provide a repository where the code can be accessed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗

DOE OSTI2020

Gamma-ray spectrum variations for surface measurements of uranium hexafluoride cylinders

Here, this work aims to characterize features that contribute to the spectral variations that appear in gamma-23 ray spectra of filled uranium hexafluoride (UF 6 ) cylinders. While the enrichment of the UF 6 in a 24 cylinder can greatly affect gamma-ray spectra at peaks such as the 185.7 keV peak and be used to 25 verify enrichment, many other characteristics of a filled UF 6 cylinder can affect the spectra. These 26 characteristics vary on a per-cylinder basis and can include: the time between when a cylinder was 27 filled and when it was measured; the previous fill history of a cylinder; how the cylinder was most 28 recently filled; the UF 6 geometric distribution within the cylinder; and the measurement location 29 along the cylinder. This work explores spectral variations seen in measurement data and uses 30 validated simulation models to find trends in these uncertainties. These trends are analyzed to observe 31 how each parameter can contribute to the overall uncertainty of UF 6 spectral measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Investigating the Role of Copper in Arsenic Doped Cd(Se,Te) Photovoltaics

The open circuit voltage (VOC) deficit in Cd(Se,Te)-based photovoltaics remains a critical obstacle for pushing the technology closer to theoretical performance limits. Arsenic doping has become a dominant and promising route to achieve the higher p-type carrier concentrations necessary for higher VOC, but challenges associated with this alternate defect chemistry and higher doping density have hindered progress. Here we show that while arsenic doping enables high carrier concentrations (>1016 cm-3), co-doping with copper can provide a boost to VOC without a significant change to carrier concentration. A large data set is initially used to explore current-voltage and capacitance-voltage trends associated with arsenic doped devices with and without copper. A smaller subset is then used to probe these trends using a wide variety of characterization techniques. Copper is found to facilitate reduced interface recombination and potentially improved bulk absorber characteristics, though the mechanisms for these improvements are not yet clear. Despite the improved performance of co-doped devices, VOC is still far below its potential especially for highly doped devices. Low emitter doping in conjunction with high absorber doping seems to be a plausible cause for this significant deficit, though other device properties may exacerbate this problem.

CdSeTe↗

DOE OSTI2025

Reconciling the Different Apparent Decay Pathways for Iron(III) Tetraphenylporphyrin Chloride: Evidence for Excited State Branching

Detailed understanding of the photophysical properties of metalloporphyrins is key to rationally exploiting them in a variety of applications ranging from photocatalysis to opto-magnetics. Previous studies of the ferric-tetraphenylporphyrin chloride have provided contradictory descriptions of the excited state evolution. Optical transient-absorption suggested initial formation of a ππ* excited state, followed by ligand-to-metal charge-transfer (LMCT) from the porphyrin ring and then decay on the ∼2 ps time scale to a metal-centered excited state that had a lifetime of ∼15 ps. In contrast, femtosecond extreme ultraviolet transient-absorption at the Fe M 2,3 -edge, while agreeing on the initial formation of an LMCT state, found evidence that this decayed in ∼2 ps to the ground state. Here, we have used K-edge transient X-ray absorption and X-ray emission, together with time-resolved X-ray solution scattering to explore this system. Based on these data, we propose a new model, consistent with both the earlier and the current data, in which photoexcited FeTPPCl evolves through three different states on the LMCT manifold, with the ∼2 ps decay now seen to involve a branching between return to the ground state (∼70%) and formation of a long-lived LMCT state (∼30%).

Excited states↗

DOE OSTI2022

The Atlantic Jet Response to Stratospheric Events: A Regime Perspective

The tropospheric response to Sudden Stratospheric Warmings (SSWs) is associated with an equatorward shift in the midlatitude jet and associated storm tracks, while Strong Polar Vortex (SPV) events elicit a contrasting response. Recent analyses of the North Atlantic jet using probability density functions of a jet latitude index have identified three preferred jet latitudes, raising the question of whether the tropospheric response to SSWs and SPVs results from a change in relative frequencies of these preferred jet regimes rather than a systematic jet shift. We explore this question using atmospheric reanalysis data from 1979 to 2018 (26 SSWs and 33 SPVs), and a 202-years integration of the Whole Atmosphere Community Climate Model (92 SSWs and 68 SPVs). Following SSWs, the northern jet regime becomes less common and the central and southern regimes become more common. These changes occur almost immediately following “split” vortex events, but are more delayed following “displacement” events. In contrast, the northern regime becomes more frequent and the southern regime less frequent following SPV events. Following SSWs, composites of 500-hPa geopotential heights, surface air temperatures, and precipitation most closely resemble composites of the southern jet regime, and are generally opposite in sign to the composites of the northern jet regime. These comparisons are reversed following SPVs. Thus, one possible interpretation is that the two southernmost regimes appear to be favored following SSWs, while the southernmost regime becomes less common following SPVs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Habit–Dependent Vapor Growth Modulates Arctic Supercooled Water Occurrence

We present an analysis of long-term data collected at Utqiagvik, Alaska, to explore the impacts of cloud processes on the probability of finding supercooled water given cloud temperature, P(L|T), in the topmost unseeded liquid-bearing layers. P(L|T) has local minima at temperatures around –6°C and –15°C. Simulations using habit-evolving ice microphysics models suggest that these minima are the result of efficient vapor growth by non-isometric habits found at these temperatures. Here, we conclude that habit-dependent vapor growth of ice crystals modulates the macrophysical occurrence of supercooled water in polar clouds, the effect of which should be included in model parametrizations to avoid biases and/or error compensation. Our methodology is adaptable for spherical ice treatments implemented in models (example parametrizations provided), amenable for use with satellite measurements to give global impartial observational targets for model evaluations, and may allow empirical characterization of bulk responses to seeding and possibly secondary ice effects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗