Results for “function unit testing” — Page 18

DOE OSTI2022

Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives

Abstract Discovering renewable fuels and fuel additives is paramount in reducing carbon emissions from internal combustion engines. Terpenes, a group of compounds that can be synthesized from plant matter and microorganisms, have gained significant interest in recent years as promising candidates for fuels/additives. Terpenes are a diverse class of compounds that contain rings and methyl branches, resulting in high energy densities and optimal cold weather behavior. Their variation in bond order, carbon chains, and functional groups lead to varying degrees of soot formation and performance in existing engines. The present work leverages predictive models, namely artificial neural networks, to predict the cetane number (CN), sooting tendency (quantified with yield sooting index, YSI), and energy density (quantified with lower heating value, LHV) of terpenes and hydrogenated terpenes whose sooting propensities were previously determined through experimental means. Predicted sooting propensities of these terpenes are compared with experimental values, and predicted cetane numbers and energy densities are used to comment on the compounds’ ability to act as fuels/additives. Expected prediction errors for CN, YSI, and LHV, defined by blind test set median absolute error, are within 5.56 cetane units, 3.63 yield sooting index units, and 0.77 MJ/kg respectively. Additionally, the present work investigates a variety of correlation/dependence metrics for property-property relationships, furthering our understanding of how combustion-relevant properties are related.

09 BIOMASS FUELS↗

DOE OSTI2025

Assessment of Blocking Contacts in Suppressing Polarization Effects in CsPbBr 3 Perovskite Detectors

The CsPbBr 3 perovskite has garnered significant attention as a room-temperature semiconductor for hard radiation detection due to straightforward synthesis, scalable crystal growth, low cost, and excellent energy resolution. However, despite these advantages, at ambient temperature, CsPbBr 3 devices may experience performance deterioration and irreversible failure due to “polarization” induced by electromigration of ions to electrical connections on the device. In this study, we tested several contact materials and their optimization deposition techniques to assess the stability of high-performance CsPbBr 3 γ-ray detectors. Metals, with low work functions (Ti, In, Sn, Sb, Pb, Bi, Al, Au, and TiC) and high-work-function (Au or Pt) contacts, were used to form different Schottky junctions using vacuum thermal evaporation, electron-beam evaporation, and sputtering methods. These detectors were tested in intermittent and continuous modes to assess their stability. Among the tested detectors, the Bi/CLB/Pt electrode configuration demonstrated superior stability, operating effectively for 11 months under periodic testing and 16 days under continuous testing. In contrast, other configurations functioned only for a few months under intermittent conditions. Upon incorporating a ~40-nm-thick TiC passivation layer on the anode side (Bi/TiC/CLB/Pt), the CLB device operated continuously for 36 days without degradation. In many cases, the failure mode of the devices was due to the degradation of the anode. Here, the chemical changes in the fresh and deteriorated anodes were characterized using scanning electron microscopy and energydispersive X-ray spectroscopy

CsPbBr3 perovskite↗

DOE OSTI2020

High-Temperature Heat Transfer Fluid Circulator for Concentrating Solar Power Systems

Concentrating Solar Power (CSP) plants with Thermal Energy Storage (TES), require compressors capable of circulating supercritical carbon dioxide (sCO2) heat transfer fluids (HTFs) at temperatures from 500 to 700+°C and pressures from 8 to 25 MPa (80 to 250 Bar or 1160 to 3626 psia) in order to achieve thermal-to-electric efficiencies >50%. A review of papers relating to SCO2 compressors reveals that in almost every case the conditions being considered either allow for cooling of the SCO2 working fluid or are considering operating conditions close to the critical point at a temperature and pressure of approximately 31°C and 1070 psi). While the technology reported in these papers is relevant to most turbomachinery, the current CSP gas pathway circulator operating pressures are well above the CO2 critical point and do not allow for cooling of the main HTF flow. The purpose of this paper was to describe the key system issues affecting the design of a HTF circulator that could be scaled from a small size research and proof of concept circulator compressor to sizes supporting power plants producint upwards of 100 to 300 Mega Watts of electrical power. Due to the high temperatures and pressures the research scale HTF circulator was designed to be hermetically sealed to prevent leakage of the super critical carbon dioxide to the environment. In order to achieve hermetic sealing the drive motor and centrifugal impeller were fully integrated in a single shaft system configuration. From a preliminary assessment of compression power as a function of operating speed and impeller diameter it was determined that a smaller, higher speed impeller would result in a more efficient circulator. However, due to the high pressure and corresponding density of the sCO2 coupled with high operating speeds, large windage losses (i.e., viscous drag on the high speed rotating shaft) would occur which could result in a substantial reduction in efficiency of the system. Therefore tradoff studies were complerted to identify the operating speeds and system component sizes to achieve high efficiency. Based on the trade studies, the final design was a 55 mm diamter compressor impeller operating at speeds to 85,000 rpm. The unit will be built and tested in the future. Key Words: Super Critical Carbon Dioxide, Heat Transfer Fluid, Turbomachinery, Compressor, Circulator, Critical Point, Concentrating Solar Power, Solar Energy

Super Critical Carbon Dioxide, Heat Transfer Fluid↗

DOE OSTI2024

A novel electro-hydraulic unit design based on a shaftless integration of an internal gear machine and a permanent magnet electric machine

In recent years, increasingly stringent emission regulations have spurred an electrification trend in off-highway vehicle technology. To address challenges such as the high cost of power electronics components, limited battery capacity, and the substantial modifications required for the vehicles, there is a pressing need to develop high-speed, cost-effective, compact, and efficient electro-hydraulic units capable of powering vehicle functions. In response to these demands, this paper introduces an innovative morphology for an electro-hydraulic unit and outlines the integration method for a crescent-type internal gear machine with a permanent magnet synchronous electric machine. The proposed morphology aims to minimize component count through a shaftless solution while incorporating a cooling system that utilizes the same working fluid as the hydraulic machine. The design approach utilizes a genetic algorithm optimization process to maximize overall energy efficiency and compactness. Insights gained from the optimization results shed light on the relationship between key design parameters and unit performance, enhancing the understanding of this electro-hydraulic unit. A prototype of the unit was manufactured and tested, demonstrating a volumetric efficiency ranging from 81 % to 97 % at a maximum rotational velocity of the pinion of 6000 rpm. Finally, these results validate both the morphology and the design approach, indicating the feasibility of designing compact electro-hydraulic units that leverage hydraulic machines with higher maximum rotational velocities than commercially available counterparts as a mean to enhance efficiency and compactness.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Pyomo: Accidentally outrunning the bear

Pyomo is an open-source optimization modeling software that has undergone significant evolution since its inception in 2008. Pyomo has evolved to enhance flexibility, solver integration, and community engagement. Modern collaborative tools for open-source software have facilitated the development of new Pyomo functionality and improved our development process through automated testing and performance-tracking pipelines. However, Pyomo faces challenges typical of research software, including resource limitations and knowledge retention. The Pyomo team’s commitment to better development practices and community engagement reflects a proactive approach to these issues. We describe Pyomo’s development journey, highlighting both successes and failures, in the hopes that other open-source research software packages may benefit from our experiences.

automation↗

DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗

DOE OSTI2025

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

DOE OSTI2021

Organic Iodide Sorption from Dilute Gas Streams

Reprocessing used nuclear fuel releases volatile radionuclides, including 129 iodine (I), into the off-gas of a processing plant. Volatile radioiodine could be present in several forms, depending on the chemistry of the process used and the off-gas stream. Inorganic I 2 is expected to be the predominant I species in the dissolver off-gas (DOG), with minor organic iodides present. The bulk of the I is expected to volatilize into the DOG in parts-per-million-level (ppm) concentrations. In contrast, in the vessel off-gas (VOG), most of the volatile I is expected to be found as organic iodides, such as CH 3 I, C 4 H 9 I, and C 12 H 25 I. These species are expected to be present in parts-per-billion-level (ppb) concentrations but require abatement, even at low expected concentrations, to meet regulatory emissions limits in the United States. Historically, studies of I abatement by Ag-functionalized sorbents have focused on inorganic I in the DOG, but in the last few years, more research attention has been given to organic iodides, especially longer chain species, such as C 4 H 9 I, and C 12 H 25 I. This report has three main goals: (1) to present new data generated at Oak Ridge National Laboratory (ORNL) in FY21 on the sorption behavior of organic iodides on AgZ, (2) to summarize and synthesize organic iodide data produced by ORNL and Idaho National Laboratory (INL) over the last 4 years to answer questions on organic iodides behavior outlined in the 2018 joint test plan (Jubin et al. 2018), and (3) to propose a VOG abatement system design that can provide the capture efficiencies required to meet I emission limits. The 2021 ORNL experimental campaign tested the effects of organic iodide speciation and concentration in the off-gas, superficial velocity of the off-gas, and effects of aging on AgZ sorbent capacity. These studies found that the sorption rate of organic iodides by AgZ depends on the hydrocarbon chain length and the concentration in the off-gas. Higher molecular weight organic iodides adsorb to AgZ more slowly than I. At a concentration of 50 ppm concentration in the off-gas, CH 3 I loads 8% slower, C 4 H 9 I loads 20% slower, and C 12 H 25 I loads 40% slower than I. The lowest concentration loading rates calculated were in 5 ppm organic iodide gas streams in which AgZ gained on average 0.14 mg I/g sorbent/hour in the bench scale test system. Thus, longer sorbent beds might be needed to accommodate slower loading rates onto AgZ in lower concentration gas streams. Although sorption rate varies as a function of hydrocarbon chain length, the saturation concentration of the sorbent for these I-bearing species does not vary. Aging AgZ in a humid air stream for 9 months drops the overall sorbent capacity by ~35% for CH 3 I, ~50% for C 4 H 9 I, and ~40% for C 12 H 25 I. This results in a saturation capacity between 35 and 70 mg I/g sorbent for the aged AgZ. In conjunction with recent data produced by INL, these data are used to estimate the mass transfer zone (MTZ) and decontamination factor (DF) for sorbent beds of AgZ. Sorption tests performed with iodide gas concentrations of about 1 ppm and higher at a superficial gas velocity of 10 m/min, indicate that MTZ depths for these conditions tend to range between about 8-20 cm. Tests performed at lower concentrations between 50-90 ppb and at gas superficial velocities of 1, 10, and 20 m/min indicate that the MTZ depth increases with increasing superficial gas velocity. The 20 m/min test indicates that the MTZ for those conditions was at least 22 cm, and doubling the superficial gas velocity from 10 to 20 m/min could roughly double or triple the MTZ depth. Doubling and tripling the bounding MTZ depth of 20 cm for the body of MTZ estimates made at with 10 m/min superficial velocity would extend the MTZ for a superficial velocity of 20 m/min to 40-60 cm. This bounding limit applies to all of the organic iodides that have been tested. These results also indicate that the sorption rate-limiting step is not sensitive to the superficial gas velocity; otherwise the MTZ depth would not have increased approximately in proportion to the increase in the gas superficial velocity. This further suggests that the rate limiting step is not associated with mass transfer of the sorbate to the sorbent surface, or mass transfer of the reaction byproducts from the sorbent surface, but is associated with sorption or chemical reactions on the sorbent surface or in sorbent pores. Deep bed testing at INL has established DFs of >2,000 for I, CH 3 I, and C 4 H 9 I under a range of conditions (Soelberg et al. 2021, Bruffey et al. 2019). DF does not seem to be affected by the concentration of the organic iodide in the gas stream over the range of 1 to 50 ppm. Thus, if the MTZ is accommodated in sorbent bed design for the DOG and VOG, then regulatory DFs will be met. To meet the third objective outlined in this report, these experimental data were used to update an engineering evaluation of the VOG first completed in 2016. The updated VOG design can be found in an accompanying document (Welty et al., 2021; INL- LTD-21-64587). This report finds that the VOG will decrease in both size and complexity, relative to previous designs, and will still meet regulatory requirements for all iodine forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Cryogenic optical beam steering for superconducting device calibration

We have developed a calibration system based on a micro-electromechanical systems (MEMS) mirror that is capable of delivering an optical beam over a wavelength range of 180 -- 2000 nm (0.62 -- 6.89 eV) in a sub-Kelvin environment. This portable, integrated system can steer the beam over a $\sim$3 cm $\times$ 3 cm area on the surface of any sensor with a precision of $\sim$100 $μ$m, enabling characterization of device response as a function of position. This fills a critical need in the landscape of calibration tools for sub-Kelvin devices, including those used for dark matter detection and quantum computing. These communities have a shared goal of understanding the impact of ionizing radiation on device performance, which can be pursued with our system. This paper describes the design of the first-generation calibration system and the results from successfully testing its performance at room temperature and 20 mK.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Polyhalohydrins: Investigating Vicinal Functionalities by Ring-Opening of Epoxides on Polyolefins

Halohydrins are functional groups that are underexplored in polymer science. This study synthesized and examined structure–property relationships of halohydrin-functionalized polymers derived from polycyclooctene (PCOE), which was obtained via ring-opening metathesis polymerization (ROMP). The polyhalohydrins, including polychlorohydrin, polybromohydrin, and polyiodohydrin, were produced through a two-step process involving epoxidation of PCOE followed by epoxide ring-opening using hydrochloric, hydrobromic, or hydroiodic acid. These stereoirregular and regioirregular polymers are amorphous as measured by differential scanning calorimetry and X-ray scattering. Lap joint shear testing revealed an enhanced adhesive performance in polychlorohydrin and polybromohydrin, with the former demonstrating nearly three times the ultimate shear stress compared to a model polyethylene, hydrogenated PCOE. Additionally, contact angle measurements and surface free energy analysis showed an increase in hydrophilicity and polarity from iodine- to bromine- to chlorine-functionalized polyhalohydrins, aligning with trends in adhesion strength. Furthermore, these results underscore the potential of halohydrin functionalization as a versatile approach for tuning surface properties, offering new opportunities for polymer-to-polymer transformations.

Functional groups↗

DOE OSTI2020

Characterization and Analysis of the Energy-Reporting Accuracy of Connected Devices

Emerging energy-efficient building systems increasingly exhibit greater functionality, often requiring multiple operating modes (e.g. white-tunability for lighting products and data traffic for devices with networked, integrated sensors). This increased functionality makes energy consumption estimates more complex. Given that these functions consume energy, the energy performance of such building systems is dependent on what operating modes they use and how much time they spend in each mode. Devices and systems that can report their own energy consumption mitigate this energy-performance uncertainty. This study explores the energy-reporting accuracy of market-available connected electrical outlets. The study considers two residential-market products (five units each, one outlet per unit) and three commercial-market products (two units each, 18 to 24 outlets per unit) with the ability to report power drawn and/or energy consumed by devices connected to their receptacles. The products were purchased through typical market channels. Pacific Northwest National Laboratory (PNNL) conducted testing in December 2018 at its Connected Lighting Test Bed (CLTB), using a custom-developed test setup and method adapted from industry standards. The setup collected energy-consumption data reported by the outlet devices under test (DUTs) at one-minute intervals and compared that data with measurements taken by a reference meter over a range of test conditions. The residential products reported power draw but not interval or cumulative energy consumption. The commercial products reported both power draw and cumulative energy consumption. Relative reporting error (RRE) was calculated for all measurements, and analysis of the results revealed variations across devices and test conditions. The total number of measurements (50 for each residential product, 60 for each commercial product) offers an appreciable comparison of performance at the make/model level. The average RRE of the residential products derived from reported power draw was -0.02% and -1.20%. The average RRE for two of the three the commercial products derived from reported power draw was worse than those of the residential products (-2.40%, -2.72%, -0.36%). The internal integration of power over time, used to calculate cumulative energy consumption, typically occurs at current and voltage sampling rates much higher than once per minute. This suggests that the average commercial-product RRE derived from reported energy consumption should be very consistent and better than performance based on reported power draw. However, the RRE derived from reported energy consumption varied significantly across the three makes of commercial-market products and was uniformly less accurate than performance based on reported power draw. Subsequent analysis identified a number of root causes for this decrease in performance, most of which were related to reporting resolution. The goals of this study are to generate awareness of building systems capable of reporting their own energy consumption, further interest in the value of energy data for a variety of uses, draw attention to how the accuracy of reported metrics can be characterized, and quantify the performance variation found in marketavailable products. The results of this study and subsequent related work may be relevant to stakeholders in industry-specification and standards-development organizations. The methods this study employs could inform test and measurement procedures and performance classifications for connected outlets, lighting products, and other building systems capable of reporting their own energy consumption. The study concludes with stakeholder recommendations, including the following: • Energy-reporting device and system manufacturers developing products that report energy consumption should characterize the accuracy of reported metrics using a reference meter calibrated by an independent laboratory that was accredited by an ILAC MRA signatory (and whose scope of accreditation explicitly covers energy measurement), and should include this information on product data sheets. • Standards and specification development organizations should develop application-specific performance classifications that end users can understand and relate to their energy-data use needs (e.g., 2% accuracy class for utility streetlight energy billing needs, or 10% accuracy class for ESCO performance verification needs). • Current or potential owners, operators, and specifiers of energy-reporting building systems should rigorously analyze the dependency of current and planned energy-data use cases on accuracy, noting in particular the dependence (or lack thereof) on relative vs. absolute accuracy, and on trueness vs. precision (i.e., repeatability), and should communicate use-case needs to industry standards and specification organizations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Characterization and Analysis of the Energy-Reporting Accuracy of Connected Devices

Emerging energy-efficient building systems increasingly exhibit greater functionality, often requiring multiple operating modes (e.g. white-tunability for lighting products and data traffic for devices with networked, integrated sensors). This increased functionality makes energy consumption estimates more complex. Given that these functions consume energy, the energy performance of such building systems is dependent on what operating modes they use and how much time they spend in each mode. Devices and systems that can report their own energy consumption mitigate this energy-performance uncertainty. This study explores the energy-reporting accuracy of market-available connected electrical outlets. The study considers two residential-market products (five units each, one outlet per unit) and three commercial-market products (two units each, 18 to 24 outlets per unit) with the ability to report power drawn and/or energy consumed by devices connected to their receptacles. The products were purchased through typical market channels. Pacific Northwest National Laboratory (PNNL) conducted testing in December 2018 at its Connected Lighting Test Bed (CLTB), using a custom-developed test setup and method adapted from industry standards. The setup collected energy-consumption data reported by the outlet devices under test (DUTs) at one-minute intervals and compared that data with measurements taken by a reference meter over a range of test conditions. The residential products reported power draw but not interval or cumulative energy consumption. The commercial products reported both power draw and cumulative energy consumption. Relative reporting error (RRE) was calculated for all measurements, and analysis of the results revealed variations across devices and test conditions. The total number of measurements (50 for each residential product, 60 for each commercial product) offers an appreciable comparison of performance at the make/model level. The average RRE of the residential products derived from reported power draw was -0.02% and -1.20%. The average RRE for two of the three the commercial products derived from reported power draw was worse than those of the residential products (-2.40%, -2.72%, -0.36%). The internal integration of power over time, used to calculate cumulative energy consumption, typically occurs at current and voltage sampling rates much higher than once per minute. This suggests that the average commercial-product RRE derived from reported energy consumption should be very consistent and better than performance based on reported power draw. However, the RRE derived from reported energy consumption varied significantly across the three makes of commercial-market products and was uniformly less accurate than performance based on reported power draw. Subsequent analysis identified a number of root causes for this decrease in performance, most of which were related to reporting resolution. The goals of this study are to generate awareness of building systems capable of reporting their own energy consumption, further interest in the value of energy data for a variety of uses, draw attention to how the accuracy of reported metrics can be characterized, and quantify the performance variation found in marketavailable products. The results of this study and subsequent related work may be relevant to stakeholders in industry-specification and standards-development organizations. The methods this study employs could inform test and measurement procedures and performance classifications for connected outlets, lighting products, and other building systems capable of reporting their own energy consumption. The study concludes with stakeholder recommendations, including the following: • Energy-reporting device and system manufacturers developing products that report energy consumption should characterize the accuracy of reported metrics using a reference meter calibrated by an independent laboratory that was accredited by an ILAC MRA signatory (and whose scope of accreditation explicitly covers energy measurement), and should include this information on product data sheets. • Standards and specification development organizations should develop application-specific performance classifications that end users can understand and relate to their energy-data use needs (e.g., 2% accuracy class for utility streetlight energy billing needs, or 10% accuracy class for ESCO performance verification needs). • Current or potential owners, operators, and specifiers of energy-reporting building systems should rigorously analyze the dependency of current and planned energy-data use cases on accuracy, noting in particular the dependence (or lack thereof) on relative vs. absolute accuracy, and on trueness vs. precision (i.e., repeatability), and should communicate use-case needs to industry standards and specification organizations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

The Energizer Bunny: Dual-Use Photovoltaic and Pasture-Raised Rabbit Farms (Final Report)

This case study project lays the groundwork for the broader realization of agrivoltaics by considering the techno-economic, environmental, and social aspects of system development and assessing a novel rabbit-based concept. Research on the social and political barriers to agrivoltaic development is sparse, which emphasizes the importance of this project as it provides key insight into the consequential socio-political challenges that may hinder the diffusion of agrivoltaic technology. Additionally, the rabbit agrivoltaic concept is novel and has not been applied in experimental or commercial applications to date. This project advances our understanding of the viability of this co-location scheme through empirical assessment of integrating grazing rabbits with solar. A total of five manuscripts (3 published in peer-reviewed journals, 2 under review) have resulted from this project. The techno-economic component of the project included a) a pilot test study investigating the feasibility of the rabbit agrivoltaic concept and b) an economic analysis of the advantages available to solar operators who leverage grazing animals for lawn maintenance and a dual-revenue stream. Our calculations indicate that the co-location of solar and rabbit farms is a viable form of agrivoltaics, increasing overall site revenue by 2.5%-24.0% above projected electricity revenue. The environmental component of the project entailed an ISO 14040 and 14044 compliant life cycle assessment to quantify the impacts of the rabbit agrivoltaic concept. The results indicate pasture-based agrivoltaic systems provide a dual synergy that produces 69.3% less emissions and demands 82.9% less fossil energy per functional unit of cumulative MWh output of electricity and cumulative kg of meat compared to non-integrated production. The social component of the project included conducting two separate interview studies with agriculture and solar industry professionals and the distribution of a public survey. The interview findings identify the key socio-political opportunities for agrivoltaics include: the retention of agricultural land and rural interests, and increased local level acceptance of solar development. The key barriers to agrivoltaics include: ensuring long term agricultural productivity is not compromised, and subnational zoning strategies. The survey results indicate that support for local solar projects increase by 10% when an agricultural function is incorporated. Survey respondents prefer agrivoltaic projects that are a) designed to provide economic opportunities for farmers and the local community b) located on private property or existing agricultural land, and c) do not threaten local interests. Cumulatively, this project can inform agrivoltaic decision making, solar development practices, rabbit-based applications, land use management, and policy making in a way that supports the furtherance of the renewable energy transition, conserves arable land, and utilizes innovative solar photovoltaic technologies.

14 SOLAR ENERGY↗

DOE OSTI2026

Robust Automatic EXAFS First-Shell Fits

Extended X-ray absorption fine structure (EXAFS) is a widely used technique for atomic structure determination. Fourier transformation connects EXAFS in k space and R space. However, determining the appropriate k-range for the transformation can be challenging, but critical for the first-shell fit. In this study, we present an automatic method to determine the k-range using the Larch package and a Python program. The first step is to estimate spectral noise across a series of k-ranges with a fixed minimum value and identify the optimal maximum value in the k-range (k max ). The k max is determined by an empirical noise threshold that marks the point where the noise level in the Fourier transformed spectrum changes dramatically. Using the obtained k max value, the first shell is modeled to determine the minimum k value (k min ) by optimizing the background function through alignment of the spectrum with theory. The optimal k min corresponds to the point of the minimum R-factor, which quantifies the difference between the experimental and fitted spectrum. Our method was tested on various typical datasets and yielded suitable k-ranges for Fourier transformation and accurate first-shell fits. This approach helps avoid unreliable, irreproducible data analysis, especially for noisy data from diluted samples, and enables robust automatic first-shell EXAFS fitting.

EXAFS analysis↗

DOE OSTI2025

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗

DOE OSTI2025

Ultrafast Photoflash Synthesis of High-Entropy Oxide Nanoparticles

High-entropy metal oxides (HEOs) have recently received growing attention for broad energy conversion and storage applications due to their tunable properties. HEOs typically involve the combination of multiple metal cations in a single oxide lattice, thus bringing distinctive structures, controllable elemental composition, and tunable functional properties. Many synthesis methods for HEOs have been reported, such as solid-state reactions and carbon thermal shock methods. These methods frequently are energy-intensive or require relatively expensive heating equipment. In this work, we report an ultrafast photoflash synthesis method for HEO nanoparticles on diverse substrates. The energy input is provided by a commercial Xe photoflash unit, which triggers exothermic reactions to convert metal salt precursors to HEO nanoparticles within tens of milliseconds. The formation of HEO nanoparticles is attributed to the ultrafast heating (∼106 K/s) and cooling (∼105 K/s) rates of the photoflash and overall high temperature (>1000 K) during the ultrafast synthesis process. When the synthesized CoNiFeCrMn oxide (HEO) is tested as an oxygen evolution reaction electrocatalyst, it shows similar activity to similar materials prepared by other methods. We believe this photoflash synthesis provides a simple method for many others to synthesize diverse HEOs and explore their properties and potential applications.

exothermic reaction synthesis↗

DOE OSTI2024

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗

DOE OSTI2024

Constructing Highly Porous Low Iridium Anode Catalysts Via Dealloying for Proton Exchange Membrane Water Electrolyzers

Iridium (Ir) is the most active and durable anode catalyst for the oxygen evolution reaction (OER) for proton exchange membrane water electrolyzers (PEMWEs). However, their large-scale applications are hindered by high costs and scarcity of Ir. Lowering Ir loadings below 1.0 mgcm -2 causes significantly reduced PEMWE performance and durability. Therefore, developing efficient low Ir-based catalysts is critical to widely commercializing PEMWEs. Herein, an approach is presented for designing porous Ir metal aerogel (MA) catalysts via chemically dealloying IrCu alloys. In this study, the unique hierarchical pore structures and multiple channels of the Ir MA catalyst significantly increase electrochemical surface area (ECSA) and enhance OER activity compared to conventional Ir black catalysts, providing an effective solution to design low-Ir catalysts with improved Ir utilization and enhanced stability. An optimized membrane electrode assembly (MEA) with an Ir loading of 0.5 mg Ir cm -2 generated 2.0 A cm -2 at 1.79 V, higher than the Ir black at a loading of 2.0 mg Ir cm -2 (1.63 A cm -2 ). The low-Ir MEA demonstrated an acceptable decay rate of ≈40 µV h -1 during durability tests at 0.5 (>1200 h) and 2.0 A cm -2 (400 h), outperforming the commercial Ir-based MEA (175 µV h -1 at 2.0 mg Ir cm -2 ).

36 MATERIALS SCIENCE↗