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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Question-answering system extracts information on injection drug use from clinical notes

Background. Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods. Here, to address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information from temporally out-of-distribution data. Results. Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions. Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

60 APPLIED LIFE SCIENCES↗

Sintering protonic zirconate cells with enhanced electrolysis stability and Faradaic efficiency

The emerging applications of steam electrolysis and electrochemical synthesis at 300–600 °C set stringent requirements on the stability of protonic ceramic cells, which cannot be met by Ce-rich electrolytes. A promising candidate is Ce-free BaZr 0.8 Y 0.2 O 3–δ , but its usage has long been hindered due to the high sintering temperatures required for protonic devices. Here we resolved the issue through a co-sintering process, in which the shrinkage stress of a readily sinterable support layer helps to densify the pure BaZr 0.8 Y 0.2 O 3–δ electrolyte membrane at low temperatures. This approach eliminates Ce and harmful sintering aids in the dense zirconate electrolyte membrane, thereby enhancing the Faradaic efficiency and electrochemical stability, especially under harsh operating conditions. Here, the protonic zirconate cells have exceptional performance and demonstrate stable high-steam pressure electrolysis up to 0.7 atm steam pressure, –2 A cm –2 current density and over 800 h of dynamic operation at 600 °C. Our processing breakthrough enables stabilized protonic cells for demanding applications in future energy infrastructure.

25 ENERGY STORAGE↗

Pinning ångström-size solid ionic channels for rare-earth element separation

High-purity rare-earth elements are essential for modern technologies, yet current solvent extraction processes are energy-intensive and environmentally harmful because of inadequate selectivity and ligand toxicity. Although combining size exclusion and binding affinity can improve lanthanide separation, the role of long-range confinement remains underexplored. Here we report lanthanide separation in aqueous systems using extremely confined manganese oxide solid ionic channels with optimized layer spacing. Different lanthanides induce distinct solid-state phase transformations in manganese oxide, creating a strong driving force for separation. Two lanthanide groups, differing by ~1.4 Å in spacing, were identified and confirmed to be stable by density functional theory. The narrower confinement of heavier Group II lanthanides improves cross-group separation by increasing the dehydration barrier for lighter Group I lanthanides without inducing strong binding. Here, we further developed a strategy to pin the confinement dimensions and enhance same-group separation, increasing enrichment factors for La–Nd and La–Pr pairs from 1.6 ± 0.1 and 1.5 ± 0.1 to 5.4 ± 0.1 and 4.2 ± 0.1, respectively.

Chemical engineering↗

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↗

Influence of functional additives, fillers, and pigments on thermal and catalytic pyrolysis of polyethylene for waste plastic upcycling

Pyrolysis offers a relatively green and economical method to convert waste plastics into valuable chemicals and fuels without the need for harmful solvents, toxic chemicals, or costly high-pressure reactors. Despite its popularity among chemical upcycling technologies, industrial adoption suffers from feedstock heterogeneity, low-quality products, and catalyst deactivation. Most plastics in our daily lives are formulated with functional additives, fillers, and colorants. These additives remaining in end-of-life waste streams increase feedstock heterogeneity, creating a challenging issue in recycling plastics. Still, the potential impacts of additives on the chemical upcycling of plastics have been poorly understood. In this study, polyethylene compounded with a range of widely used additives (antioxidants, stabilizers, pigments, fillers, slip agents, and flame retardants) was subjected to both thermal pyrolysis and catalytic pyrolysis in different catalyst-to-feedstock contact modes. It showed that many inorganic additives, such as talc, kaolin, CaCO 3 , TiO 2 , carbon black, and zinc stearate, facilitated polymer decomposition during pyrolysis, increasing light hydrocarbons while also promoting aromatic and carbon residue formation. Conversely, antioxidants and stabilizers inhibited depolymerization, favoring heavier hydrocarbons. During catalytic pyrolysis with HZSM-5 zeolite, additives strongly enhanced aromatic and catalytic coke formation, especially when there was direct contact between plastics and catalysts. Although certain additives seem beneficial in the short term by promoting polymer cracking and improving the selectivity of aromatics, the transport of the additives and their degradation products and increased carbon coking can contaminate products, deactivate or modify catalysts, and foul reactors. These findings address a critical knowledge gap in effectively converting waste plastics via a greener route.

42 ENGINEERING↗

Solvent-mediated contaminant removal from plastic waste using thermodynamic modeling

Plastics recycling is hindered by the compositional complexity of plastic waste, which can include numerous polymer components as well as low concentrations of additives and non-intentionally added substances. These latter small-molecule species, which we collectively refer to as contaminants, can harm human health and will build up in recycled plastic causing environmental and downstream processing challenges if not removed. In this work, we present molecular modeling approaches using the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) to guide the selection of solvents that are capable of removing targeted contaminants from plastic waste. By considering the thermodynamic partitioning of contaminant species between a solvent phase and polymer phase, we identify guidelines for solvent selection to promote either the low-temperature extraction of contaminants from plastic waste or the removal of contaminants as part of a dissolution-based plastics recycling process. We present four case studies to illustrate the application of the computational approach to the removal of brominated flame retardants, phthalates, and selected perfluoroalkyl substances, and compare to both literature and newly collected experimental data to illustrate model prediction accuracy. Furthermore, the case studies highlight the capability of the modeling approach to help design recycling processes that explicitly account for contaminant removal, thereby increasing product purity during dissolution-based recycling or facilitating chemical recycling of contaminant-free plastics.

Zhou, Panzheng [University of, Wisconsin, Madison,↗

Scalable, low-cost ink-based processing of high-performance silver selenide thermoelectrics

The growing global energy demand and its accelerating contribution to climate change emphasize the urgent need for sustainable energy conversion/harvesting technologies. Thermoelectric (TE) devices offer a compelling route to directly convert waste heat into electricity and enable solid-state cooling without moving parts or harmful refrigerants. Achieving their full potential requires not only higher TE performance (zT) but also scalable, low-cost manufacturing processes. Here, we introduce a transformative ink-based processing approach for scalable manufacturing of high-performance silver selenide-based TE materials and devices. Using a simple, high-throughput ink-mixing and blade coating strategy, our Ag 2 Se-based materials under the optimized composition and processing conditions yield an ultrahigh room-temperature power factor of 2.8 mW m −1 K −2 , over 100% higher than baseline samples and a reproducible figure of merit zT of 1 at room temperature. A thermoelectric generator (TEG) achieves a very competitive power density of 112 mW cm −2 at a 90 °C temperature difference between the hot and cold sides of the device, which is among the highest reported for silver selenide-based TE devices to date. This facile, scalable ink-based processing establishes a practical pathway toward industrial-scale manufacturing and widespread adoption of thermoelectric devices, advancing sustainable energy technologies.

Bappy, Md. Omarsany [University of Notre Dame, IN ↗

Prioritizing circular economy strategies for sustainable PV deployment at the TW scale

Global decarbonization requires an unprecedented scale-up of photovoltaic (PV) manufacturing and deployment. The material demand and eventual end of life management associated with multi-TW scale deployment poses many challenges. Circular Economy (CE) and it's associated R-Actions (Reduce, Reuse, Recycle) have been proposed to mitigate end of life management and material sourcing concerns. However, CE metrics typically focus on a single product and only consider mass, excluding energy flows. This work leverages the PV in Circular Economy (PV ICE) tool to quantify the deployment, mass, and energy impacts of R-Actions and proposed sustainable PV designs in the context of achieving energy transition deployment goals (75 TW in 2050). 13 module scenarios are established and evaluated across 6 capacity, mass and energy metrics to identify tradeoffs and priorities. We find that increasing module efficiency can reduce near-term material demands up to 30% and improve energy metrics by up to 9%. Material circularity (recycling) can minimize lifecycle wastes and reduce material demands at the cost of higher energy demands. Increasing module lifetime, including reliability improvements and reuse strategies, is effective at reducing both material (>10%) and energy demands (24%). Uniquely, lifetime improvements maximize benefits and minimize the harms across all six metrics while achieving multi-TW scale deployment.

Photovoltaics↗

Anticathode effect on multimodal azimuthal oscillations in electron beam generated E×B plasma

Electron beam (e-beam) generated plasmas with applied crossed electric and magnetic (⁠E x B⁠) fields are promising for low-damage (gentle) material processing. However, these plasmas can be subject to the formation of plasma non-uniformities propagating in the ⁠E x B direction. These rotating plasma structures (or “spokes”) enhance the transport of charged species across the magnetic field, which can harm the gentle processing capability of the plasma. In this work, we investigate the role of electrostatically active boundaries on the spoke formation by incorporating a variable bias conducting boundary (known as an anticathode) placed on the axially opposite side of the cathode. Our findings indicate azimuthal mode suppression occurs when the anticathode is electron collecting. Furthermore, we show selective azimuthal mode suppression by biasing the anticathode to an intermediate potential between the cathode and anode potentials. In conclusion, these findings suggest a link between the axial electron confinement in the e-beam generated plasma and azimuthally propagating plasma structure formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multimodal azimuthal oscillations in electron beam generated E×B plasma

Electron beam (e-beam) generated plasmas with applied crossed electric and magnetic (E×B) fields are promising for low-damage material processing. However, these plasmas can be subject to the formation of azimuthally propagating structures that enhance the radial transport of energetic charged species, which can harm the gentle processing capability of the plasma. In this work, we investigate the azimuthal structure formation in an e-beam generated E×B plasma using experimental diagnostics and 2D3V particle-in-cell simulations. Our findings demonstrate the formation of multiple simultaneously occurring azimuthally propagating modes that exhibit nontrivial radial dependence. It is suggested that the multimodal azimuthal spectrum is caused in part by the radial outflow of ions in the plasma.

electron beams↗

An improved method for quantitatively measuring antifouling coating performance using a mussel single thread tensile adhesion test

Surface biofouling reduces the efficiency and lifespan of equipment across many industries. The development of high-performance antifouling surfaces, such as foul release coatings, benefits from test methods that can quickly identify superior antifouling surfaces in the laboratory during material development. Existing test methods poorly discriminate between different foul release coatings. Here is presented a method to assess the ability of surfaces to resist mussel adhesion using a quantitative, controlled single thread adhesion test (STAT) method, allowing for meaningful comparisons between low adhesion foul release surfaces. This method provides greater accuracy and finer resolution than push-based mussel shear adhesion methods without the difficulties associated with mussel size, thread attachment angle, or harming the mussels. The single thread tensile method is demonstrated on a variety of standard and high-performance coatings, and it is shown that the method detects differentiation between commercial foul release coatings that could not be resolved using other methods.

42 ENGINEERING↗

Outlook for active plasma spectroscopy with entangled two-photon absorption

Entangled two-photon absorption (ETPA) exhibits a quantum-enhanced two-photon absorption cross-section and a linear scaling with incident power that exceeds classical two-photon absorption (TPA) at low photon flux. Here, we assess the feasibility and applications of ETPA for active plasma spectroscopy. The ETPA-absorbed power for an Ar + species in a helicon plasma scenario is calculated to be as high as 0.6 nW cm −1 along the incident beam path for nondegenerate-entangled photon pairs that are near-resonant with an intermediate level. The ETPA absorption power exceeds classical TPA and Bremsstrahlung emission, a necessary condition for a feasible fluorescence measurement. Applications of ETPA plasma spectroscopy may include trace impurity detection, ground-state excitation, and continuous-wave pumping for high-bandwidth turbulence measurements. Possible benefits of plasma measurements are less harm to optical components with lower incident flux and reduced stray light that can contaminate optical diagnostics.

active plasma spectroscopy↗

Turbulent drifts of impurity ions as an explanation for anomalous radial transport in the far-SOL of DIII-D

Abstract Successful fusion reactor operation relies on minimal core contamination by impurities, otherwise too much power may be radiated and harm performance. This requires reliable predictions of impurity transport from the scrape-off layer (SOL) into the core, beyond the traditional ‘anomalous’ diffusion approach. We report a set of far-SOL tungsten transport simulations that demonstrate the role of turbulent drifts on radial impurity transport. A turbulent plasma background is simulated using the gyrokinetic SOL code Gkeyll. Tungsten ions are followed within the plasma background using only their drifts. We find that tungsten tends to travel radially outwards with velocities between v r = 300–1200 m s −1 primarily due to polarization drift. We also extract an anomalous radial diffusion coefficient that varies from D r anom = 5–20 m 2 s −1 . These results are compared to and agree with previous interpretive modeling results. We also show how the turbulent polarization drift can transport some tungsten ions from the wall inwards with effective pinch velocities up to 10 000 m s −1 . We conclude that turbulent drifts are a likely explanation for historically anomalous radial impurity transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Analysis of the linear and nonlinear stability of Alfven eigenmodes and fish-bones in JET DT discharges: mode identification and shear flows generation

The plasma in future nuclear fusion reactors will be heated by neutral beam injectors (NBIs) and high frequency electromagnetic waves as well as fusion born alpha particles. Energetic particles (EPs), with energies up to two orders of magnitude larger than the thermal plasma, can trigger EP driven modes and induce harmful EP losses, reducing the plasma heating efficiency and the economical viability of the reactor. The present study is dedicated to analyze the Alfven Eigenmode (AE) activity in JET D–T discharges, the closest experiment to reactor-like operation performed until now. There, EP driven modes are induced by the combined effect of tangential NBIs and ion cyclotron resonance heating (ICRH) driven EP. Linear and nonlinear simulations are performed with the gyro-fluid FAR3d code to analyze the AE activity observed in the discharge 99896. The linear simulations reproduce the unstable n = 3 to 5 toroidal AEs (TAE) at the inner plasma region observed in the experiment, triggered by highly energetic passing deuterium populations injected by the tangential NBIs, further accelerated by the effect of the ICRH up to 1 MeV. In addition, fish-bones triggered by energetic trapped hydrogen induced by the ICRH are also reproduced. On the other hand, the alpha particles density is too small to destabilize AEs in the experiment. Nonetheless, increasing artificially the alpha density by one order of magnitude, an n = 1 beta induced AE can be destabilized in the inner plasma region. Nonlinear simulations indicate the generation of zonal structures during the AE/fish-bone saturation phase. TAE and fish-bones causes a rather weak increase of the passing D and trapped H EP (around 2%), respectively. Shear flows and zonal currents are generated during the saturation of TAE and fish-bones. Nonlinear simulations performed for D–T and pure deuterium thermal plasma indicate AE/fish-bone activity is weaker and shear flows are less intense in the pure deuterium case, trends consistent with the experimental observations that also indicates a deterioration of the thermal plasma confinement. Therefore, both numerical studies and experimental evidence indicate the generation of shear flows by AE/fish-bones could be connected with an improvement of the thermal plasma confinement.

AE↗

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗

Including frameworks of public health ethics in computational modelling of infectious disease interventions

Decisions on public health interventions to control infectious diseases are often informed by computational models. Interpreting the predicted outcomes of a public health decision requires not only high-quality modelling but also an ethical framework for assessing the benefits and harms associated with different options. The design and specification of ethical frameworks matured independently of computational modelling, so many values recognized as important for ethical decision-making are missing from computational models. We demonstrate a proof-of-concept approach to incorporate multiple public health values into the evaluation of a simple computational model for vaccination against a pathogen such as SARS-CoV-2. By examining a bounded space of alternative prioritizations of three values relevant to public health ethics (aggregate clinical burden, equity in clinical burden, equity in adverse effects from vaccination), we identify value trade-offs, where the outcomes of optimal strategies differ depending on the ethical framework. This work demonstrates an approach to incorporating diverse values into decision criteria used to evaluate outcomes of models of infectious disease interventions.

"Mathematical Biology"↗

Ethical considerations in infectious disease modelling for public health policy: the case of school closures

Mathematical models of infectious diseases are frequently used as a tool to support public health policy and decisions around the implementation of interventions such as school closures. However, most publications on policy-relevant modelling lack an ethical framework and do not explicitly consider the ethical implications of the work. This creates a risk that the unintended consequences of interventions are overlooked or that models are used to justify decisions that are inconsistent with public health ethics. In this article, we focus on the case study of school closures as a commonly modelled intervention against pandemic influenza, COVID-19 and other infectious disease threats. We briefly review some of the key concepts in public health ethics and describe approaches to modelling the effects of school closures. We then identify a series of ethical considerations involved in modelling school closures. These include accounting for population heterogeneity and inequalities; including a diversity of viewpoints and expertise in model design; considering the distribution of benefits and harms; and model transparency and contextualization. Furthermore, we conclude with some recommendations to ensure that policy-relevant modelling is consistent with some key ethics values.

97 MATHEMATICS AND COMPUTING↗

Performance Evaluation of a Single-Phase Grid-Forming Inverter Through Hardware Experiments

This study conducts hardware experiments to assess the performance of a commercial single-phase grid-forming (GFM) inverter using a purely hardware-based approach. We adhere to a testing protocol for the GFM inverter and enhance it by exploring the transient performance of GFM inverters across various grid dynamic events. Quantifiable performance metrics are established for each testing scenario to gain insights into the performance of the single-phase GFM inverters. Based on the comprehensive tests, the following observations are summarized: 1) The performance of the single-phase GFM inverter is satisfactory, and it is capable of being the islanding master for residence homes when the main grid is gone. 2) For frequency response, the inverter is able to stay connected but cannot inject the needed active power to support the grid. This may be improved by the manufacturer by using droop control. 3) The GFM inverter exhibits harmful transients in voltage and frequency during islanding operation, which can be enhanced by maintaining the same operating points before and after the breaker is open.

black start↗