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DOE OSTI2024

Carboxylating Elastomer via Thiol‐Ene Click Reaction to Improve Miscibility with Conjugated Polymers for Mechanically Robust Organic Solar Cells with Efficiency of 19%

Abstract Incorporating flexible insulating polymers is a straightforward strategy to enhance the mechanical properties of rigid conjugated polymers, enabling their use in flexible electronic devices. However, maintaining electronic characteristics simultaneously is challenging due to the poor miscibility between insulating polymers and conjugated polymers. This study introduces the carboxylation of insulating polymers as an effective strategy to enhance miscibility with conjugated polymers via surface energy modulation and hydrogen bonding. The carboxylated elastomer, synthesized via a thiol‐ene click reaction, closely matches the surface energy of the conjugated polymer. This significantly improves the mechanical properties, achieving a high crack‐onset strain of 21.48%, surpassing that (5.93%) of the unmodified elastomer:conjugated polymer blend. Upon incorporating the carboxylated elastomer into PM6:L8‐BO‐based organic solar cells, an impressive power conversion efficiency of 19.04% is attained, which top‐performs among insulating polymer‐incorporated devices and outperforms devices with unmodified elastomer or neat PM6:L8‐BO. The superior efficiency is attributed to the optimized microstructures and enhanced crystallinity for efficient and balanced charge transport, and suppressed charge recombination. Furthermore, flexible devices with 5% carboxylated elastomer exhibit superior mechanical stability, retaining ≈88.9% of the initial efficiency after 40 000 bending cycles at a 1 mm radius, surpassing ≈83.5% for devices with 5% unmodified elastomer.

Chemistry↗

DOE OSTI2022

Fluxionality of Subnano Clusters Reshapes the Activity Volcano of Electrocatalysis

The Sabatier activity volcano provides intuitive guide for catalyst design, but also imposes fundamental limitations on the composition and maximal activity of catalysts. Here we show that the ORR activity volcano is shifted and reshaped by the potential-dependent fluxionality of subnano cluster catalysts. Fluxionality causes the typically under-binding Ag/Au to gain optimal activity in the cluster form, and surpass Pt/Pd. Furthermore, isomerization of clusters as a function of the potential breaks linear scaling relationships, enabling surpassing the volcano “apex” relative to the bulk. The effect is likely general for fluxional cluster catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Confidence-weighted integration of human and machine judgments for superior decision-making

Large language models (LLMs) can surpass humans in certain forecasting tasks. What role does this leave for humans in the overall decision process? One possibility is that humans, despite performing worse than LLMs, can still add value when teamed with them. A human and machine team can surpass each individual teammate when team members’ confidence is well calibrated and team members diverge in which tasks they find difficult (i.e., calibration and diversity are needed). We simplified and extended a Bayesian approach to combining judgments using a logistic regression framework that integrates confidence-weighted judgments for any number of team members. Using this straightforward method, we demonstrated its effectiveness in both image classification and neuroscience forecasting tasks. Combining human judgments with one or more machines consistently improved overall team performance. Our hope is that this simple and effective strategy for integrating the judgments of humans and machines will lead to productive collaborations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Defect-Regulated Frustrated-Lewis-Pair Behavior of Boron Nitride in Ambient Pressure Hydrogen Activation

We report the construction of heterogeneous frustrated Lewis pairs (FLPs) with performance comparable to or surpassing the homogeneous counterparts in H 2 activation is a long-standing challenge. Herein, sterically hindered Lewis acid (“B” center) and Lewis base (“N” center) sites were anchored within the rigid lattice of highly crystalline hexagonal boron nitride (h-BN) scaffolds. The active sites were created via precision defect regulation during the molten-salt-involved (NaNH 2 and NaBH 4 ) h-BN construction procedure. The as-afforded h-BN scaffolds achieved highly efficient H 2 /D 2 activation and dissociation under ambient pressure via FLP-like behavior, and attractive catalytic efficiency in hydrogenation reactions surpassing the current heterogeneous analogues.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Rational design of high-performance low-loading oxygen reduction catalysts for alkaline fuel cells

The lack of mechanistic understanding and catalyst design principles for alkaline electrolytes, especially for the sluggish oxygen reduction reaction, has impeded the advancement of alkaline fuel cells. Here, in this study, we propose a modified volcano plot and apply this rationale to strategically design Pt nanosheets with PdH x nanosheets substrates. This catalyst exhibited high stability with a specific activity of 1.71 mA cm −2 at 0.95 V versus the reversible hydrogen electrode, surpassing the benchmark of Pt/C by 49-fold. Spectroscopic, electrochemical and electron microscopic characterizations revealed that such performance enhancement originated from tensile-strained Pt{111} facets, improving oxidative stability and suppressing carbon corrosion. In fuel cell testing, the catalyst enabled a peak power density of 1.67 W cm −2 with a loading of 10 µg PGM Cathode cm −2 . Further optimization delivered a peak power density of 21.7 W mg −1 PGM Cathode+Anode with a total specific catalyst cost US$\$$1.27 kW −1 , surpassing the US Department of Energy’s Pt group metal loading and cost targets. This study provides valuable insights into catalyst design for the alkaline oxygen reduction reaction.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Quantum computing for finance

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. Here, we present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle. Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum techniques, as well as challenges that physicists could help tackle.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Observation of D 2 molecule line emission after massive D 2 injection into runaway electron plateaus in DIII-D

Molecular deuterium line emission is observed in both the visible and ultraviolet (UV) wavelength ranges after massive (> 100 Torr-L) injection of D 2 gas into post-disruption runaway electron (RE) dominated plasmas in the DIII-D tokamak. D 2 UV line emission is found to be the dominant source of radiated power, surpassing D Lyα. Interpretive modeling with a collisional-radiative model (CRM) indicates that D 2 radiation surpasses D radiation because Lyα is strongly trapped, while D 2 UV lines are mostly untrapped. The CRM also indicates that the D 2 line emission is completely dominated by RE impact (rather than thermal electron impact), so the D 2 line emission can serve as a good diagnostic for the spatial localization of REs. Analysis of D 2 visible lines indicates that the D 2 molecules in the plasma are thermally equilibrated with the background plasma, with vibrational, rotational, and kinetic temperatures all near 0.3 eV. D 2 spectroscopy therefore serves as a convenient diagnostic of background plasma temperature. As a result, measurement of D 2 radiated power also appears to serve as a useful diagnostic for constraining neutral transport modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Assessment of RELAP5-3D Code with Molten Salt Heat Transfer Experiments

The accurate thermal-hydraulic assessment of thermal storage systems is crucial for addressing the integrity and performance of the storage system design. This is particularly important for thermal storage systems using molten salts as a heat transport and storage medium, as the chemical corrosion and erosion by the high-temperature molten salts can cause serious damage to the structural components of the storage system. To understand these effects for TerraPower’s Natrium® Demonstration Reactor design, the system thermal-hydraulic analysis code, RELAP5-3D, is utilized to analyze the thermal storage system. This study evaluates two heat transfer correlations implemented in the RELAP5-3D code—the Dittus-Boelter and Gnielinski correlations—using selected benchmark cases from two molten salt heat transfer experiments conducted at Xi’an Jiao Tong University and the German Aerospace Center. The Nusselt numbers calculated using the Gnielinski correlation agree with the experimental data within ±5% of the relative deviations at 300°C and 400°C. With the increasing Reynolds numbers, the Dittus-Boelter correlation underestimates the Nusselt numbers by up to 22% compared to the Gnielinski correlation. Comparison of the RELAP5-3D calculation results with experimental data at a high temperature of 550°C revealed that the thermo-chemical characteristics of solar salt at high temperatures surpassing the decomposition temperatures of nitrate salts reduce the accuracy of heat transfer model of the RELAP5-3D code. Specifically, it has been observed that the temperatures of the wall surface and liquid near the wall can surpass the decomposition temperatures, even though the bulk temperature of molten salts remains significantly lower than these decomposition temperatures. In summary, this study recommends the use of the Gnielinski correlation for the heat transfer analysis of molten salt, rather than the Dittus-Boelter correlation.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2023

Isotope dependence of transport in ST40 hot ion mode plasmas

The ST40 compact, high-field spherical tokamak, operating at 2.1 T and with 1.8 MW of neutral beam heating, achieved central carbon impurity ion temperatures in excess of 10 keV, surpassing their business milestone of 100 M °C (8.6 keV). The high temperature discharges were in the hot ion mode, with $T_i \gg T_e$, and they were achieved in both hydrogen and deuterium plasmas with deuterium neutral beam injection. In order to achieve the high temperature scenarios, careful wall conditioning and scenario optimization was carried out in $H^0 \rightarrow H^+$, $D^0 \rightarrow H^+$, and finally in $D^0 \rightarrow D^+$ plasmas. The TRANSP transport code was employed to study the dependence of confinement and transport on isotopic mass, and the conditions that led to the high measured central ion temperatures in the $D^0 \rightarrow H^+$ and $D^0 \rightarrow D^+$ plasmas. The kinetic profiles input into TRANSP were inferred from line-of-sight and limited radial measurements as well as consistency with a number of other experimental constraints. The TRANSP results first showed that the main species central ion temperature was only 0.5–1 keV lower than the measured carbon impurity temperature, and thus in the high performance plasmas also surpassed the 100 M °C level. TRANSP also showed that while the electron thermal conduction loss was dominant, reductions in central ion transport, and an effective decoupling of the ions from the electrons, led to an increase in central ion temperatures with increasing plasma mass. In fact, the associated confinement times exhibited a strong dependence on the isotopic mass of the thermal plasma. These preliminary results are foundations for dedicated experiments with full kinetic profile measurements on ST40 in the next run campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples

We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter f NL loc via the large-scale scale-dependent bias in the power spectrum using 1,631,716 LRGs (0.6 < z < 1.1) and 1,189,129 QSOs (0.8 < z < 3.1). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative technique allowing the correction through the window matrix convolution. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure f NL loc = -3.6 -9.1 +9.0 at 68% confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to f NL loc = 3.5 -7.4 +10.7 at 68% confidence. Due to restricted selection in the LRG sample, the inclusion of the LRGs allows for 10% improvement. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of 2.3.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Broadband Solenoidal Haloscope for Terahertz Axion Detection

We introduce the Broadband Reflector Experiment for Axion Detection (BREAD) conceptual design and science program. This haloscope plans to search for bosonic dark matter across the [ 10 - 3 , 1 ] eV ([0.24, 240] THz) mass range. BREAD proposes a cylindrical metal barrel to convert dark matter into photons, which a novel parabolic reflector design focuses onto a photosensor. This unique geometry enables enclosure in standard cryostats and high-field solenoids, overcoming limitations of current dish antennas. A pilot 0.7 m 2 barrel experiment planned at Fermilab is projected to surpass existing dark photon coupling constraints by over a decade with one-day runtime. Axion sensitivity requires < 10 - 20 W / Hz sensor noise equivalent power with a 10 T solenoid and 10 m 2 barrel. We project BREAD sensitivity for various sensor technologies and discuss future prospects.

Liu, Jesse↗

DOE OSTI2021

Investigating realistic anode off-gas combustion in SOFC/ICE hybrid systems: mini review and experimental evaluation

Solid oxide fuel cells (SOFCs) have been deployed in hybrid decentralized energy systems, in which they are directly coupled to internal combustion engines (ICEs). Prior research indicated that the anode tailgas exiting the SOFC stack should be additionally exploited due to its high energy value, with typical ICE operation favoring hybridization due to matching thermodynamic conditions during operation. Consequently, extensive research has been performed, in which engines are positioned downstream the SOFC subsystem, operating in several modes of combustion, with the most prevalent being homogeneous compression ignition (HCCI) and spark ignition (SI). Experiments were performed in a 3-cylinder ICE operating in the latter modus operandi, where the anode tailgas was assimilated by mixing syngas (H 2 : 33.9%, CO: 15.6%, CO 2 : 50.5%) with three different water vapor flowrates in the engine’s intake. While increased vapor content significantly undermined engine performance, brake thermal efficiency (BTE) surpassed 34% in the best case scenario, which outperformed the majority of engines operating under similar operating conditions, as determined from the conducted literature review. Nevertheless, the best performing application was identified operating under HCCI, in which diesel reformates assimilating SOFC anode tailgas, fueled a heavy duty ICE (17:1), and gross indicated thermal efficiency ([Formula: see text]) of 48.8% was achieved, with the same engine exhibiting identical performance when operating in reactivity-controlled compression ignition (RCCI). Overall, emissions in terms of NO x and CO were minimal, especially in SI engines, while unburned hydrocarbons (UHC) were non-existent due to the absence of hydrocarbons in the assessed reformates.

Engineering↗

DOE OSTI2024

An evaluation of GPT models for phenotype concept recognition

Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field. These processes rely on using ontology concepts, often from the Human Phenotype Ontology, in conjunction with a phenotype concept recognition task (supported usually by machine learning methods) to curate patient profiles or existing scientific literature. With the significant shift in the use of large language models (LLMs) for most NLP tasks, we examine the performance of the latest Generative Pre-trained Transformer (GPT) models underpinning ChatGPT as a foundation for the tasks of clinical phenotyping and phenotype annotation. The experimental setup of the study included seven prompts of various levels of specificity, two GPT models (gpt-3.5-turbo and gpt-4.0) and two established gold standard corpora for phenotype recognition, one consisting of publication abstracts and the other clinical observations. The best run, using in-context learning, achieved 0.58 document-level F1 score on publication abstracts and 0.75 document-level F1 score on clinical observations, as well as a mention-level F1 score of 0.7, which surpasses the current best in class tool. Without in-context learning, however, performance is significantly below the existing approaches. Our experiments show that gpt-4.0 surpasses the state of the art performance if the task is constrained to a subset of the target ontology where there is prior knowledge of the terms that are expected to be matched. While the results are promising, the non-deterministic nature of the outcomes, the high cost and the lack of concordance between different runs using the same prompt and input make the use of these LLMs challenging for this particular task.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Data for A Role for Differential Rubisco Activase Isoform Expression in C4 Bioenergy Grasses at High Temperature

Rubisco activase (Rca) facilitates the release of sugar-phosphate inhibitors at Rubisco catalytic sites during CO2 fixation. Most plant species express two Rca isoforms, the larger Rca-α and the shorter Rca-β, either by alternative splicing from a single gene or expression from separate genes. The mechanism of Rubisco activation by Rca isoforms has been intensively studied in C3 plants. However, the functional role of Rca in C4 plants where Rubisco and Rca are located in a much higher [CO2] compartment is less clear. In this study, we selected four C4 bioenergy grasses and the model C4 grass setaria ( Setaria viridis ) to investigate the role of Rca in C4 photosynthesis. All five C4 grass species contained two Rca genes, one encoding Rca-α and the other Rca-β, which were positioned closely together in the genomes. A variety of abiotic stress-related motifs were identified in the Rca-α promoter of each grass, and while the Rca-β gene was constantly highly expressed at ambient temperature, Rca-α isoforms were expressed only at high temperature but never surpassed 30% of Rca-β content. The pattern of Rca-α induction on transition to high temperature and reduction on return to ambient temperature was the same in all five C4 grasses. In sorghum ( Sorghum bicolor ), sugarcane ( Saccharum officinarum ), and setaria, the induction rate of Rca-α was similar to the recovery rate of photosynthesis and Rubisco activation at high temperature. This association between Rca-α isoform expression and maintenance of Rubisco activation at high temperature suggests that Rca-α has a functional thermo-protective role in carbon fixation in C4 grasses by sustaining Rubisco activation at high temperature.

Genomics↗

DOE OSTI2024

Coherent states of the Laguerre–Gauss modes

Large quantum photonic systems hold promise for surpassing classical computational limits, yet their state preparation remains a challenge. We propose an alternative approach to study multiparticle dynamics by mapping the excitation mode of these systems to physical properties of the Laguerre–Gauss modes. We construct coherent states establishing a direct link between excitation number dynamics and the evolution of the Laguerre–Gauss modes. This highlights the photon transverse spatial degree of freedom as a versatile platform for testing the fundamental aspects of quantum multiparticle systems.

Morales Rodríguez, M. P.↗

DOE OSTI2020

Quantitative Long-Term Monitoring of the Circulating Gases in the KATRIN Experiment Using Raman Spectroscopy

The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and after only a few weeks of data recording, analysis of these data showed the success of KATRIN, improving on the known neutrino mass limit by a factor of about two. This success very much could be ascribed to the fact that most of the system components met, or even surpassed, the required specifications during long-term operation. Here, we report on the performance of the laser Raman (LARA) monitoring system which provides continuous high-precision information on the gas composition injected into the experiment’s windowless gaseous tritium source (WGTS), specifically on its isotopic purity of tritium—one of the key parameters required in the derivation of the electron neutrino mass. The concentrations cx for all six hydrogen isotopologues were monitored simultaneously, with a measurement precision for individual components of the order 10−3 or better throughout the complete KATRIN data taking campaigns to date. From these, the tritium purity, εT, is derived with precision of <10−3 and trueness of <3 × 10−3, being within and surpassing the actual requirements for KATRIN, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment

As a genre of physics-informed machine learning, differentiable process-based hydrologic models (abbreviated as δ or delta models) with regionalized deep-network-based parameterization pipelines were recently shown to provide daily streamflow prediction performance closely approaching that of state-of-the-art long short-term memory (LSTM) deep networks. Meanwhile, δ models provide a full suite of diagnostic physical variables and guaranteed mass conservation. Here, we ran experiments to test (1) their ability to extrapolate to regions far from streamflow gauges and (2) their ability to make credible predictions of long-term (decadal-scale) change trends. We evaluated the models based on daily hydrograph metrics (Nash–Sutcliffe model efficiency coefficient, etc.) and predicted decadal streamflow trends. For prediction in ungauged basins (PUB; randomly sampled ungauged basins representing spatial interpolation), δ models either approached or surpassed the performance of LSTM in daily hydrograph metrics, depending on the meteorological forcing data used. They presented a comparable trend performance to LSTM for annual mean flow and high flow but worse trends for low flow. For prediction in ungauged regions (PUR; regional holdout test representing spatial extrapolation in a highly data-sparse scenario), δ models surpassed LSTM in daily hydrograph metrics, and their advantages in mean and high flow trends became prominent. In addition, an untrained variable, evapotranspiration, retained good seasonality even for extrapolated cases. The δ models' deep-network-based parameterization pipeline produced parameter fields that maintain remarkably stable spatial patterns even in highly data-scarce scenarios, which explains their robustness. Combined with their interpretability and ability to assimilate multi-source observations, the δ models are strong candidates for regional and global-scale hydrologic simulations and climate change impact assessment.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

The Design of Optical Sensor for the Pinhole/Occulter Facility

Three optical sight sensor systems were designed, built and tested. Two optical lines of sight sensor system are capable of measuring the absolute pointing angle to the sun. The system is for use with the Pinhole/Occulter Facility (P/OF), a solar hard x ray experiment to be flown from Space Shuttle or Space Station. The sensor consists of a pinhole camera with two pairs of perpendicularly mounted linear photodiode arrays to detect the intensity distribution of the solar image produced by the pinhole, track and hold circuitry for data reduction, an analog to digital converter, and a microcomputer. The deflection of the image center is calculated from these data using an approximation for the solar image. A second system consists of a pinhole camera with a pair of perpendicularly mounted linear photodiode arrays, amplification circuitry, threshold detection circuitry, and a microcomputer board. The deflection of the image is calculated by knowing the position of each pixel of the photodiode array and merely counting the pixel numbers until threshold is surpassed. A third optical sensor system is capable of measuring the internal vibration of the P/OF between the mask and base. The system consists of a white light source, a mirror and a pair of perpendicularly mounted linear photodiode arrays to detect the intensity distribution of the solar image produced by the mirror, amplification circuitry, threshold detection circuitry, and a microcomputer board. The deflection of the image and hence the vibration of the structure is calculated by knowing the position of each pixel of the photodiode array and merely counting the pixel numbers until threshold is surpassed.

Greene, Michael E.↗