In vivo therapeutic applications of phosphorus dendrimers: state of the art
Not Available
Mignani, Serge↗
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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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State-of-the-art on research and applications of machine learning in the building life cycle
Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Thermal energy storage in desalination systems: State of the art, challenges and opportunities
Not Available
Shabgard, H.↗
State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data
Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.
24 POWER TRANSMISSION AND DISTRIBUTION↗
The Artistry of Radiation Oncology: Raiders of the Lost Art
No abstract prepared.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Electrolyzer energy dominates separation costs in state-of-the-art CO 2 electrolyzers: Implications for single-pass CO 2 utilization
In low-temperature CO 2 electrolysis, a fundamental trade-off exists between maximizing electrolyzer performance and minimizing downstream CO 2 recovery. Here, by coupling a down-the-gas-channel electrolyzer model with a techno-economic analysis, we find that the optimal single-pass CO 2 conversion for ethylene production is typically low—on the order of 5%–10%—although larger optima are found if the H 2 faradic efficiency is very low. Similarly, strategies for eliminating carbonate crossover require more energy than downstream gas separation if they increase the cell potential by ~0.2 V; however, when CAPEX are accounted for, this “break-even” voltage increases to ~ 0.4 to 0.8 V for electricity prices varying from 6c/kWh to 1.5c/kWh. These findings are a consequence of the low energy requirements of industrial gas separation relative to electrochemical CO 2 reduction. Under most circumstances, maintaining near-optimal electrolyzer performance is more important than reducing or eliminating downstream gas separations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands
Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. In this work, we observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 10 6 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.
58 GEOSCIENCES↗
Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea
Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn- and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO 2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn-eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.
58 GEOSCIENCES↗
Development and assessment of hierarchical multi-reward reinforcement learning based potential for silicene with state-of-the-art models
We develop a new interatomic force field for Silicene, a 2D material with a buckled hexagonal lattice structure with high polymorphism. We introduce new parameterizations of a Tersoff model using a hierarchical multi-reward reinforcement learning (RL) methodology coupled with a continuous Monte Carlo Tree Search optimization. Our model significantly outperforms existing methods by enhancing the accuracy of predictions for the structural and thermodynamic properties of seven silicene polymorphs-including structure, energy, equation of state, elasticity, and phonon dispersion-when compared to established models. We further make a comprehensive comparison of the various models in predicting the mechanical and thermal properties of silicene. We trace the origin of the improved performance to the description of the angular dependence in the bond-order term, suggesting that modifying the angular terms in short-range models is essential to capture the structural diversity in low dimensional systems.
2D materials↗
A state of the art Lambertson septum magnet of the RHIC beam injection system
The beam injection system of the Relativistic Heavy Ion Collider (RHIC) is the last section of the beam transfer line which transports the beam from the Alternating Gradient Synchrotron (AGS) to RHIC and comes under the acronym AtR (AGS to RHIC). The Lambertson septum magnet is one of the magnetic elements of the RHIC injection system. This paper presents results from the 2D and 3D electromagnetic design of the RHIC Lambertson septum magnet which has unique design features to minimize the magnetic field at the circulated beam region including the fringe field regions at the entrance and exit of the magnet.
43 PARTICLE ACCELERATORS↗
The state of the art for neutron irradiation experiments from the perspective of the High Flux Isotope Reactor (HFIR)
Irradiation experiment campaigns are critical to advancing nuclear energy technologies by providing data on material performance under relevant radiation conditions. Successful irradiation experiments require integrated design efforts that balance technical goals with facility constraints. Here, this paper presents an expert-informed overview of irradiation experiment design at the High Flux Isotope Reactor. It addresses the nuclear materials research and irradiation experiment communities to guide them toward developing technically sound, facility-compatible campaigns. The High Flux Isotope Reactor is a multipurpose reactor supporting isotope production, neutron scattering, and materials testing. Its high, steady-state neutron flux is ideal for irradiation experiments, but successful execution demands coordinated thermal, structural, and reactor physics analyses. The paper outlines the complete development workflow from concept definition and design optimization to safety qualification and post-irradiation examination. Standardized capsule platforms are also discussed in terms of flexibility, specimen capacity, and thermal performance. Common failure modes such as unanticipated geometric variations, can impact temperature-dose profiles and compromise data reliability. Therefore, detailed thermal modeling and accurate as-built characterization are essential for meaningful post-irradiation data interpretation. Key recommendations include early engagement all stakeholders, clearly defined design expectations, and alignment of specimen geometries with post-irradiation examination capabilities. This approach reduces design iterations, enhances data quality, and supports more efficient use of irradiation resources. Strategic and well-planned irradiation testing not only improves individual campaign success but also accelerates the deployment of advanced nuclear technologies. By closing critical data gaps and reducing development risks, the nuclear materials community can more effectively contribute to the future of clean, resilient energy systems.
Experiments↗
Benchmarking state-of-the-art theory and empirical models of pionless neutrino-argon scattering in GENIE
Upcoming experiments need improved simulations of neutrino scattering. This work uses the popular GENIE event generator to test a variety of neutrino interaction models against recent MicroBooNE measurements of pionless charged-current interactions. The GENIE code can easily interchange model components, including nucleon form factor parameterizations, quasielastic cross-section calculations, treatments of the nuclear ground state and hadronic final-state interactions. Leveraging this software capability in comparisons with MicroBooNE data, the performance of some of GENIE’s most theoretically sophisticated model components is evaluated and contrasted with more empirically-driven alternatives.
Neutrino cross section↗
Additive manufacturing of nickel-based superalloys: A state-of-the-art review on process-structure-defect-property relationship
Fusion-based additive manufacturing (AM) has significantly grown to fabricate Nickel-based superalloys with design freedom across multiple length scales. Several phenomena such as feedstock/energy source/melt pool interactions, solidification and phase transformations occur during fusion-based AM processes of Nickel-based superalloys, which determine the ultimate microstructure and mechanical performance of the built parts. In this review, here we elaborate a comprehensive discussion on AM Nickel-based superalloys and influential factors including feedstock characteristics (powder morphology, chemistry, contamination, flowability, recycling) and AM processing (parameters, and powder spreading/wall/balling/spattering effects) on their microstructure (micro-segregation, phases formations and grain structures), defect generation (sub-surface/internal defects, microcracks, surface roughness, and residual stress). Furthermore, the mechanical properties of AM Nickel-based superalloys such as tensile, creep and fatigue at room/elevated temperatures are analyzed in accordance with the initial, and post processing effects. Additionally, the commonly utilized modeling approaches in literature to predict the microstructure and mechanical behavior of these alloys are highlighted. Finally, the current challenges and mitigation approaches for future research are identified considering the gaps in the AM Nickel-based superalloys.
36 MATERIALS SCIENCE↗
A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions
Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.
36 MATERIALS SCIENCE↗