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DOE OSTI2026

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗

DOE OSTI2021

Polyolefin plastic waste hydroconversion to fuels, lubricants, and waxes: a comparative study

Hydroconversion technologies have surged to the forefront of deconstructing plastic waste. Recent studies have been performed over several catalysts with varying conditions and plastics that make comparisons difficult. We compile and compare data from the literature by introducing various metrics and perform a simple energy analysis. We draw mechanistic similarities to and differences from the past literature on small alkane hydroconversion and leverage the former to propose standard approaches to tune product selectivity. We exemplify the plastics materials gap and the challenges it creates. Lastly, we discuss the current limitations and suggest future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Interplay of structural fluctuations and charge carrier dynamics is key for high performance of hybrid lead halide perovskites

The ability of methylammonium lead triiodide (MAPbI 3 ) to achieve photoelectric conversion efficiency that is on par with crystalline silicon has led to a surge of interest in perovskite photovoltaics. However, an in-depth understanding of how the ubiquitous coupling between the fast rovibrational movements of the organic cations and the phonon vibrations of the inorganic framework affects the relaxation and recombination of hot carriers remains largely elusive. Access to such knowledge is critical to guide design and increase efficiency of new classes of perovskite solar cells. In this report, we report a time-domain ab initio investigation of temperature dependent excited state dynamics in MAPbI 3 , with particular emphasis on nuclear anharmonic effects. The observed strong anharmonicity is attributed to softness of the material and unusual dynamical coupling between the organic and inorganic components. At an elevated temperature, the hydrogen bonding between MA and iodines is weakened, enhancing rotation of MA cations, which become more dynamically disordered. As a result, thermal vibrations of the inorganic Pb–I sublattice are suppressed, and the lattice anharmonicity is decreased. Thermal fluctuations of the electronic energy levels are found to follow the trend of anharmonic motions of Pb and I atoms, with holes relaxing faster to the band edges than electrons, due to higher density of the hole states. While elevated temperature accelerates intraband carrier cooling, it slows nonradiative carrier recombination. The latter result is important for performance, since solar cells and other devices heat up during operation. The reported signatures of coupled structural dynamics of the organic cations and inorganic framework unravel the interplay between anomalous structural fluctuations and charge carrier dynamics, which is of particular importance for fundamental understanding of the structure–property relationships in hybrid metal halide perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

An AI-accelerated pathway for reproducible and stable halide perovskites

Halide perovskites (HPs) have remarkable optoelectronic properties, and in the last decade their photovoltaic power conversion efficiency and light-emitting diode efficiency have skyrocketed. Despite the surge in research on these burgeoning materials, two key challenges in the field remain: material irreproducibility and instability. Their behavior is especially dynamic in response to environmental stressors, due to complex interactions with the perovskite crystal lattice. Here, in this review, we survey the latest achievements in HP materials research accomplished with the assistance of artificial intelligence (AI), through the implementation of automated experimentation and machine learning (ML) data analysis. Automated synthesis and characterization tackle problems with material irreproducibility by systematically controlling parameters with very high precision, creating massive datasets, and allowing methodical comparisons from which unbiased conclusions can be drawn. AI can reveal otherwise unnoticed trends, inform future experiments with the highest potential information gain, and forecast future performance. The review concludes with a forward viewpoint of how human-assisted closed-loop laboratories and shared databases allow halide perovskite materials’ processing, properties, and performance to be potentially optimized with AI, accelerating the development of highly reproducible and stable optoelectronic devices.

Hering, Abigail R. [Univ. of California, Davis, CA↗

DOE OSTI2025

Life cycle greenhouse gas emissions and carbon intensity of U.S. fuel use and projection for the next 10 years-based on built capacity and expansion plans

The U.S. Inflation Reduction Act of 2022 supports biofuel production expansion through the 45Z clean fuel production tax credit, replacing previous 40A and 40B credits. This follows on the Renewable Fuel Standard from the Energy Policy Act of 2005 and its expansion in 2007. States like California, Oregon, and Washington also offer clean fuel credits. Meanwhile, federal agencies, including the U.S. Department of Energy, have advanced alternative fuel technologies through research and development funding. The surging interest in the biofuel industry has spurred the demand for biofuel supplies in the markets, although achieving profitability for advanced biofuels and low-carbon e-fuels remains challenging. This study aims to track U.S. alternative fuel production capacity expansion plans over the next 10 years and estimate impacts on greenhouse gas (GHG) emissions. By tracking built capacity and industry announcements of planned expansion, this study complements other studies which use models to predict changes in energy technologies and the associated GHG implications. Modeled projections of future technologies are often criticized for over or underestimating the cost and potential role of new technologies. The study focuses on sustainable aviation fuel, renewable diesel, ethanol, biodiesel, and renewable natural gas. Using facility-level data, we conducted a bottom-up analysis linking biofuel production pathways with corresponding pathways and parameterizations in the Argonne R&D GREET model. Results indicate that biofuel capacity could reach 3.8 exajoules in 2035, potentially reducing U.S. GHG emissions by 179 million tonnes, including the full life cycle. This corresponds to a 20% reduction in transportation and 5% in industry sector emissions by 2035, or a 3.6% reduction in economy-wide emissions. Overall, this study shows that while biofuel production capacity in the U.S. is expanding, the capacities remain limited compared to fuel demand. Uncertainty regarding the durability and extension of incentives may be dampening the pace of growth. Meanwhile, demonstrating the commercial potential for alternative fuels and climbing the learning curve for new technologies could lead to an increased pace of expansion in later years. This study offers insights for bioenergy stakeholders, highlighting biofuel technologies' contribution to U.S. energy system and emissions reduction over time based on producers' plans.

Biofuel Producers↗

DOE OSTI2025

Determining the Minimum Phase‐to‐Phase Gap Distance for Unconventional Transmission Lines Using Numerical Method

With the increasing demand for power transmission, compact, high surge impedance loading (HSIL) high-voltage transmission lines have emerged as a viable solution due to their reduced land acquisition costs and higher power delivery capability. The compactness of a transmission line depends on effective insulation coordination, particularly in determining the phase-to-phase clearance, which is governed by the critical flashover voltage under switching and lightning overvoltage conditions. Traditional methods for phase-to-phase clearance rely on empirical formulas derived from experimental data, which are convenient for conventional high-voltage lines. However, unconventional HSIL lines require a faster and more adaptable evaluation method, as they involve optimized conductor positioning to reduce right-of-way requirements while enhancing natural power loadability. This study presents a simplified numerical approach to determine the minimum phase-to-phase gap, utilizing arc propagation viability curves, and offers an efficient alternative to conventional empirical methods. The proposed method was successfully applied to a 500 kV conventional line as well as 500 and 735 kV unconventional line designs, demonstrating its capability in accurately assessing insulation requirements. Results reveal that the method can support reduced gap clearances while still maintaining reliability, thereby validating its usefulness in optimizing compact transmission line configurations.

Arafat, Easir [The University of Texas at Dallas, ↗

DOE OSTI2024

Streaming Readout and Data-Stream Processing With ERSAP

With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.

Vardan, Gyurjyan↗

DOE OSTI2024

Towards High-Performance AI4NP Applications on Modern GPU Platforms

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.

Mei, Xinxin↗

DOE OSTI2025

Investigating the Impact of Temporal and Directional Traffic Distribution on Crash Frequencies

Safety Performance Functions (SPFs) are mathematical models that establish relationships between the frequency of various crash types and site-specific characteristics, serving as essential tools for traffic safety analysis and roadway design. Traditional SPFs, however, often overlook the temporal fluctuations in traffic flow (such as peak-hour surges) and directional imbalances between opposing traffic streams. These traffic patterns can exacerbate congestion, disrupt driver behavior, and create unexpected conflict points, potentially leading to increased crash frequencies and more severe accidents. In light of this gap, this study aims to explore the potential of incorporating K-factors (representing peak-hour traffic proportions) and D-factors (reflecting the imbalance of directional traffic) into the development of SPFs to assess whether these factors can effectively represent the impact of temporal and spatial traffic distribution on roadway safety. Using crash data from Pennsylvania urban-suburban collector roadways, it is found that the D-factor plays a significant role in predicting the frequency of total crashes, fatal + injury crashes, and angle crashes, with positive coefficient signs indicating that higher directional imbalances correspond to increased crash risks. Similarly, the K-factor emerges as a critical predictor for fatal + injury crashes and rear-end crashes, with negative coefficients suggesting that a more pronounced traffic peak is associated with a reduction in expected crash frequencies. These results highlight the importance of accounting for uneven traffic distribution in both time and direction when developing SPFs, offering deeper insights into crash patterns and supporting more effective safety interventions and roadway designs.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗

DOE OSTI2021

Surfactants and cloud droplet activation: A systematic extension of Köhler theory based on analysis of droplet stability

The activation of aerosol particles to form cloud droplets, a necessary first step in cloud formation, controls much of the impact that aerosols have on clouds and climate. Recently, there has been a surge of interest in extending the Köhler theory of cloud droplet activation to include surface active (typically organic) as well as water-soluble (typically inorganic) aerosol components, but a systematic framework for doing this has yet to be developed. Here, we apply a droplet stability analysis to this end. Ideal and Szyszkowski–Langmuir surfactant models are analyzed to demonstrate the new approach, but the underlying theoretical framework is fundamental and model free. A key finding is that superficial densities at the cloud activation threshold (Köhler maximum) are significantly sub-monolayer, with fractional coverage ranging from 69% to 85% for the organic compounds and mixtures studied. The result, significant for model inventories of cloud condensation nuclei, is a weakening of the surfactant effect relative to expectations based on bulk sample measurements. Analytical results are obtained for the loci of Köhler maxima and applied to aerosol mixtures containing an arbitrary number of water-soluble and surfactant components.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Widespread deep seismicity in the Delaware Basin, Texas, is mainly driven by shallow wastewater injection

Significance The Delaware Basin, western Texas, has experienced a surge in the number of earthquakes. We investigate basin-wide earthquake, hydrogeologic, industrial, and geodetic data spanning 1993–2020 to identify the reasons for the increase. We use these data and models to quantify the stress changes from wastewater injection and hydrocarbon extraction. We demonstrate that the basin-wide seismicity is dominated by the stresses caused by shallow injection that are transmitted vertically by deforming the underlying crust. We analyze both injection and production data to understand how subsurface properties control earthquake locations and timings. We suggest that injecting wastewater into porous formations will minimize seismic hazard. We establish a framework explaining why earthquakes sometimes occur and sometimes do not occur within human activity-impacted areas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Extreme elevational migration spurred cryptic speciation in giant hummingbirds

The ecoevolutionary drivers of species niche expansion or contraction are critical for biodiversity but challenging to infer. Niche expansion may be promoted by local adaptation or constrained by physiological performance trade-offs. For birds, evolutionary shifts in migratory behavior permit the broadening of the climatic niche by expansion into varied, seasonal environments. Broader niches can be short-lived if diversifying selection and geography promote speciation and niche subdivision across climatic gradients. To illuminate niche breadth dynamics, we can ask how “outlier” species defy constraints. Of the 363 hummingbird species, the giant hummingbird (Patagona gigas) has the broadest climatic niche by a large margin. To test the roles of migratory behavior, performance trade-offs, and genetic structure in maintaining its exceptional niche breadth, we studied its movements, respiratory traits, and population genomics. Satellite and light-level geolocator tracks revealed an >8,300-km loop migration over the Central Andean Plateau. This migration included a 3-wk, ~4,100-m ascent punctuated by upward bursts and pauses, resembling the acclimatization routines of human mountain climbers, and accompanied by surging blood-hemoglobin concentrations. Extreme migration was accompanied by deep genomic divergence from high-elevation resident populations, with decisive postzygotic barriers to gene flow. The two forms occur side-by-side but differ almost imperceptibly in size, plumage, and respiratory traits. The high-elevation resident taxon is the world’s largest hummingbird, a previously undiscovered species that we describe and name here. The giant hummingbirds demonstrate evolutionary limits on niche breadth: when the ancestral niche expanded due to evolution (or loss) of an extreme migratory behavior, speciation followed.

Science & Technology - Other Topics↗

DOE OSTI2021

LAMP Diagnostics at the Point-of-Care: Emerging Trends and Perspectives for the Developer Community

Over the past decade, loop-mediated isothermal amplification (LAMP) technology has played an important role in molecular diagnostics. Amongst numerous nucleic acid amplification assays, LAMP stands out in terms of sample-to-answer time, sensitivity, specificity, cost, robustness, and accessibility, making it ideal for field-deployable diagnostics in resource-limited regions. In this review, we outline the front-end LAMP design practices for point-of-care (POC) applications, including sample handling and various signal readout methodologies. Next, we explore existing LAMP technologies that have been validated with clinical samples in the field. We summarize recent work that utilizes reverse transcription (RT) LAMP to rapidly detect SARS-CoV-2 as an alternative to standard PCR protocols. Finally, we describe challenges in translating LAMP from the benchtop to the field and opportunities for future LAMP assay development and performance reporting. Despite the popularity of LAMP in the academic research community and a recent surge in interest in LAMP due to the COVID-19 pandemic, there are numerous areas for improvement in the fundamental understanding of LAMP, which are needed to elevate the field of LAMP assay development and characterization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Electromagnetic turbulence simulation of tokamak edge plasma dynamics and divertor heat load during thermal quench

Abstract The edge plasma turbulence and transport dynamics, as well as the divertor power loads during the thermal-quench phase of tokamak disruptions, are numerically investigated with BOUT++’s flux-driven six-field electromagnetic turbulence model. Here, transient yet intense particle and energy sources are applied at the pedestal top to mimic the plasma power drive at the edge induced by a core thermal collapse, which flattens the core temperature profile. Interesting features, such as surging of divertor heat load (up to 50 times) and broadening of heat-flux width (up to four times) on the outer-divertor target plate, are observed in the simulation, in qualitative agreement with experimental observations. The dramatic changes in divertor heat load and width are due to the enhanced plasma turbulence activities inside the separatrix. Two cross-field transport mechanisms, namely, the E × B turbulent convection and the stochastic parallel advection/conduction, are identified to play important roles in this process. First, an elevated edge pressure gradient drives instabilities and subsequent turbulence in the entire pedestal region. The enhanced turbulence not only transports particles and energy radially across the separatrix via the E × B convection, which causes the initial divertor heat-load burst, but it also induces amplified magnetic fluctuation B ˜ . Once themagnetic fluctuation is large enough to break the magnetic flux surface, magnetic flutter effect provides an additional radial transport channel. In the late stage of our simulation, | B ˜ r / B 0 | reaches to 10 −4 level that completely breaks magnetic flux surfaces such that stochastic field lines are directly connecting pedestal top plasma to the divertor target plates or first wall, further contributing to the divertor heat-flux width broadening.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Characterization of SOL profiles and turbulence in ICRF-heated plasmas in EAST

Scrape-off layer (SOL) profiles and turbulence in ion cyclotron range of frequency (ICRF)-heated plasmas are investigated by the reciprocating probe diagnostic system (FRPs) and gas puff imaging (GPI) diagnostic in EAST. A radio-frequency (RF) sheath potential reaching up to 100 V is identified proximate to the ICRF antennas. Notably, the amplitude of this RF sheath potential escalates in response to rising ICRF power and inversely with plasma density. When a RF sheath is present in the far SOL, a pronounced density ‘shoulder’ forms in front of the ICRF antennas, while the ‘shoulder’ fade away as the antenna and associated RF sheath shift outwards. A strong E r shear is revealed by measurements from both FRPs and GPI. Analysis of the poloidal wave number-frequency spectrum reveals suppression of high-frequency turbulence in the far SOL due to the RF sheath. This effect is manifested in the reduced autocorrelation time τ c and reduced average blob size δ blob of the SOL plasma. Intriguingly, the poloidal propagation direction of the low-frequency turbulence reverses from the electron to the ion diamagnetic drift direction at the RF sheath location. A surge of tungsten impurity is potentially attributed to the heightened interaction between the SOL plasmas and the wall material. Shifting the ICRF antennas outward, to alleviate heat spots, results in the relocation of the RF sheath to the shaded region of the main limiter. This shift amplifies the radial velocity of blobs in the far SOL and concurrently diminishes the SOL density when compared to conditions without ICRF injection. The properties of ion saturation current fluctuations are consistent with the stochastic model predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Radiation-front position control with scenario adjustments during the first tungsten divertor operation on KSTAR

This study reports the first experimental demonstration of a radiation front-based detachment control system during the initial tungsten divertor campaign in KSTAR. The system employs real-time infrared video bolometry with tomographic reconstruction to track the inboard radiation-front position, which served as a feedback variable for impurity seeding. In a baseline scenario without pre-D 2 fueling, tungsten accumulation triggered core radiation surges and repetitive H–L back transitions. In contrast, with pre-D 2 fueling, detachment was stabilized by maintaining higher edge-localized mode frequency, suppressing core tungsten buildup, and reducing sputtering, thereby enabling sustained feedback control. The suitability of the inboard front position as a detachment control metric was confirmed by its correlation with the degree of detachment: with D 2 fueling the relation exhibited a broad hysteresis loop characteristic of momentum-loss-dominated detachment, whereas with N 2 fueling, it became narrow and nearly vertical, consistent with radiation-loss-dominated pinning. These results provide a proof-of-principle for radiation-front-based detachment control, demonstrating its viability as a control approach. At the same time, these results clarify that the detachment outcomes were further conditioned by impurity transport characteristics of tungsten divertor operation in KSTAR, providing guidance for future scenario optimization and controller development in tungsten devices.

KSTAR↗

DOE OSTI2020

Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state

For the simulation of the coupled dynamic response of floating offshore wind turbines, it is crucial to calibrate the hydrodynamic damping with experimental data. The aim of this work is to find a set of hydrodynamic drag coefficients for the semisubmersible platform of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project which provides suitable results for an irregular sea state. Due to the complex interaction of several degrees of freedom (DOF), it is common to calibrate drag coefficients with the time series of decay tests. However, applying these drag coefficients for the simulation of an irregular sea state results in misprediction of the motions. By using numerical optimization, it is possible to calibrate multiple drag coefficients simultaneously and effectively, while also considering several DOF. This work considers time series of structural displacements from wave tank tests of the OC6 project and from simulations of the same load cases in OpenFAST. Results are transferred into the frequency domain and the deviation between power spectral densities of surge, pitch and heave from experiment and numerical simulation is used as an objective function to obtain the best fitting drag coefficients. This novel numerical optimization approach enables finding one set of drag coefficients for different load cases, which is a major improvement compared to decay-test-tuned drag coefficients.

42 ENGINEERING↗

DOE OSTI2020

An outlook into the flat land of 2D materials beyond graphene: synthesis, properties and device applications

Abstract The field of two-dimensional (2D) and layered materials continues to excite many researchers around the world who are eager to advance and innovate viable routes for large scale synthesis, doping and integration of monolayers and the development of unique characterization approaches for studying and harnessing exotic properties that will enable novel device applications. There has been a large interest in 2D materials beyond graphene, with particular emphasis on monoelemental materials (phosphorene, silicene, tellurene, etc. ), 2D compounds (MXenes, oxides, nitrides, carbides and chalcogenides), their alloys and layered van der Waals heterostructures. This is not only indicated by the significant increase in the number of peer reviewed publications each year in this area of research, but also by the surging number of conference sessions focusing on 2D materials beyond graphene. This Perspective article highlights some of the recent advances in the field from a diverse international community of theoretical and experimental researchers who participated in the symposium ‘Beyond Graphene 2D Materials—Synthesis, Properties and Device Applications’ at the Materials Research Society (MRS) Fall 2019 meeting.

McCreary, Amber (ORCID:0000000299885800)↗