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799 records · Page 35

Internet of Things Data Characterization Process: Pattern of Life Behavioral Data Study

The HoneyBee™ TARDIS LDRD team completed a data scoping study that identified the initial processes and procedures to baseline the normal and expected behaviors during operability and interoperability of Internet of Things (IoT) device networks. This research is the initial step in developing a process (or methodology) to inform a much broader information framework incorporating machine learning to determine device pattern-of-life which enables the detection of abnormal IoT behaviors on an individual device, as well as in the context of a larger network.

97 MATHEMATICS AND COMPUTING

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry

Characterization of ceramic fuel powder packing fractions to support INFLUX

Triply periodic minimal surface (TPMS)-based structures show marked potential in novel nuclear reactor fuel designs, as their high surface area-to-volume ratio increases the efficiency of heat transfer out of the fuel, enabling safer, more innovative reactor designs. This milestone report addresses the role of dUO 2 powder processing route on the fill behavior of TPMS-based cladding shells to understand and advance the feasibility of manufacturing TPMS-based nuclear fuel forms. dUO 2 powder was processed through either a dry granulation route, varying consolidation pressure, or through milling, varying milling time, milling method and milled size distribution. The lowest tapped bulk densities (TBD), but best powder flowabilities, were obtained when testing unprocessed dUO 2 powder which was prone to self-agglomeration and formed low-density spheroids. The highest TBD and lowest flowabilities were obtained when using powder produced by hammer-milling dUO 2 powder to pass through a 200-mesh sieve, which led to particles with angular morphologies. Powder produced by dry granulation exhibited TBD that varied according to the consolidation pressure used to form the initial pellets and exhibited improved flowabilities when compared to hammer-milled material. Because of the large span of granule sizes formed as well as the irregular shape associated with the granules, a packing fraction of 0.69 was achieved, exceeding the analytical solution for random close packing of mono-sized spheres. TPMS polymer shells were loaded with unprocessed, granulated, and hammer-milled dUO 2 powders, and their qualitative packing behaviors were analyzed using x-ray computed tomography (xCT). TBDs calculated after loading TPMS polymer shells were 10-20% lower when compared to tapped bulk density measurements taken in a glass graduated cylinder, indicating a non-trivial impact on the tapped bulk density of either the TPMS channel size, TPMS channel surface material, powder cohesiveness, or a combination of the two parameters. A metallic zircaloy-4 TPMS shell will be loaded with hammer-milled dUO 2 powder upon receipt of the shell from Oak Ridge National Laboratory (ORNL) and shipped to Idaho National Labs (INL) for subsequent hot isostatic pressing (HIP) densification experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Multi‐Objective Optimization for Rapid Identification of Novel Compound Metals for Interconnect Applications

Abstract Interconnect materials play the critical role of routing energy and information in integrated circuits. However, established bulk conductors, such as copper, perform poorly when scaled down beyond 10 nm, limiting the scalability of logic devices. Here, a multi‐objective search is developed, combined with first‐principles calculations, to rapidly screen over 15,000 materials and discover new interconnect candidates. This approach simultaneously optimizes the bulk electronic conductivity, surface scattering time, and chemical stability using physically motivated surrogate properties accessible from materials databases. Promising local interconnects are identified that have the potential to outperform ruthenium, the current state‐of‐the‐art post‐Cu material, and also semi‐global interconnects with potentially large skin depths at the GHz operation frequency. The approach is validated on one of the identified candidates, CoPt, using both ab initio and experimental transport studies, showcasing its potential to supplant Ru and Cu for future local interconnects.

Chemistry

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

Abstract This review provides a comprehensive overview of the progress in light–material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Materials Science

Radiative divertor detachment and impurity transport with nitrogen and neon seeding in KSTAR H-mode plasmas

Achieving core-edge compatible divertor detachment is a critical requirement for stable operation in future fusion devices. This study compares nitrogen and neon seeding in KSTAR H-mode plasmas with carbon walls, combining experiments and SOLPS-ITER modelling to evaluate their radiative dissipation and core-edge compatibility. Experimentally, N seeding achieved stronger divertor detachment, with larger reductions in target particle and heat fluxes, a higher divertor radiation fraction, and a lower core radiation fraction than Ne. In contrast, Ne seeding triggered a significant rise in core radiation followed by H–L back transitions, limiting the maximum total radiated power fraction to roughly half that of N. SOLPS-ITER simulations reproduced the experimental trends and revealed that the better core-edge compatibility of N arises from its higher divertor retention in addition to its higher cooling factor. The relative positions of the stagnation points of impurity poloidal velocity and ionization sources did not explain the different divertor compression. Instead, in the present modelling, the higher impurity parallel particle flux, resulting from the higher parallel impurity velocity, explains the stronger nitrogen impurity compression in the divertor region. The parallel temperature distribution with N was more favourable for achieving higher impurity parallel velocity than with Ne, because the impurity velocity is governed by modifications of the main ion flow due to friction and thermal forces, both of which strongly depend on the temperature. Ultimately, this behaviour is attributed to the strongly divertor-localized radiation of N. These results demonstrate that N is more effective than Ne in achieving radiative divertor detachment while maintaining low core contamination in KSTAR, consistent with observations in other present tokamaks.

KSTAR

Remote-Contact Catalysis for Target-Diameter Semiconducting Carbon Nanotube Arrays

Electrostatic catalysis has been an exciting development in chemical synthesis (beyond enzymes catalysis1 ) in recent years, boosting reaction rates and selectively producing certain reaction products2 . Most of the studies to date have been focused on using external electric field (EEF) to rearrange the charge distribution in small molecule reactions such as Diels-Alder addition3 , carbene reaction4 , etc. However, in order for these EEFs to be effective, a field on the order of 1 V/nm (10 MV/cm) is required, and the direction of the EEF has to be aligned with the reaction axis5 . Such a large and oriented EEF will be challenging for large-scale implementation, or materials growth with multiple reaction axis or steps. Here, we demonstrate that the energy band at the tip of an individual single-walled carbon nanotube6 (SWCNT) can be spontaneously shifted in a high-permittivity growth environment, with its other end in contact with a low-work function electrode (e.g., hafnium carbide or titanium carbide7 ). By adjusting the Fermi level at a point where there is a substantial disparity in the density of states (DOS) between semiconducting (s-) and metallic (m-) SWCNTs8 , we achieve effective electrostatic catalysis for s-SWCNT growth assisted by a weak EEF perturbation (200V/cm). This approach enables the production of high-purity (99.92%) s-SWCNT horizontal arrays with narrow diameter distribution (0.95±0.04 nm), targeting the requirement of advanced SWCNT-based electronics for future computing9-11. These findings highlight the potential of electrostatic catalysis in precise materials growth, especially for s-SWCNTs, and pave the way for the development of advanced SWCNT-based electronics12.

Wang, Jiangtao [Department of Electrical Engineeri

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)

Answering old questions with new techniques: Understanding performance-limiting factors in transition metal dichalcogenide photoelectrochemical solar cells

In the late 1970s and early 1980s, several research groups reported high-efficiency and stable photoelectrochemical solar cells based on transition metal dichalcogenides (TMDS; e.g., MoS 2 , WSe 2 , and MoSe 2 ) immersed in iodide/tri-iodide electrolytes. A consensus emerged that smooth crystals were necessary for high efficiency based on significant evidence that rough crystals with exposed edge sites produced lower photocurrents and fill factors. However, anecdotal observations in the literature hinted at significant performance variation among apparently smooth crystals with the possibility of highly active “hot” edge sites. Furthermore, this mini-review article is a case study on how spatially resolved photoelectrochemical techniques developed in the 2020s are answering old questions regarding the origin of performance variation in high efficiency n-type TMD|I – ,I 3 – |Pt photoelectrochemical solar cells.

14 SOLAR ENERGY

Superconducting Material Growth for Radio-Frequency (RF) Cavities

Superconducting radio-frequency (SRF) cavities, usually manufactured from Niobium (Nb), are vital components of modern particle accelerators because of their ability to achieve high acceleration gradients with little power dissipation. Naturally forming Nb surface oxides significantly alter cavity performance by changing surface resistance. A nondestructive characterization of oxide thickness is helpful for relating surface processing treatments to cavity performance. This work develops a protocol to measure Nb oxide thickness using Angle-Resolved X-ray Photoelectron Spectroscopy (ARXPS) while correcting instrumental errors. Using uniform bulk standard samples (Silver, Aluminum oxide, and Germanium), we determined a baseline correction factor to account for analyzer-related intensity evolution as the measurement angle increases. The correction factor was then applied to Nb 3d ARXPS data. Applying the Strohmeier equation to the corrected data yielded a Nb2O5 thickness of 6.04 nm, closely matching the 5.5 (±.05) nm value obtained from cross-sectional transmission electron microscopy. Our approach will bring a method to incorporate inherent errors in the thickness measurements using ARXPS and can be broadly applied to improve the accuracy of thickness measurements in a wide range of heterostructures.

Lambert, Nathan [Fermilab]

Reflection and refraction of directrons at the interface

Reflection and refraction are ubiquitous phenomena with extensive applications, yet minimizing energy loss and information distortion during these processes remains a significant challenge. This study examines the behavior of structurally stable solitons, known as directrons, in nematic liquid crystals interacting with an interface where the director field orientation changes, despite identical physical properties, external potentials, and boundary anchoring in the two regions. During reflection and refraction, the directrons maintain nearly constant structure and velocity, ensuring energy conservation and information integrity. Microscopic analyses of the director field and macroscopic evaluations of effective potential are employed to elucidate the dependence of reflection and refraction probabilities on the directron’s incident angle and the orientation difference across the interface. The findings provide valuable insights into the dynamics of solitary waves in structured liquid crystal systems, offering significant implications for the development of tunable photonic devices, reconfigurable optical systems, and nanoscale material engineering.

Science & Technology - Other Topics

Aliovalent gallium dopants remove Ti 3+ defects and improve photocatalytic and photoelectrochemical water oxidation properties of LaTiO 2 N

LaTiO 2 N is a promising semiconductor for the water splitting reaction due to its 2.1 eV band gap and stability against corrosion. However, its solar energy conversion is limited by Ti 3+ recombination defects introduced during ammonolysis. Here we show for the first time that Ti 3+ defects in LaTiO 2 N can be suppressed with incorporation of 2, 5, and 10% aliovalent gallium (Ga 3+ ) dopants during synthesis via the layered La 2 Ti 2 O 7 intermediate. Electron paramagnetic resonance (EPR) spectroscopy on the solid powders confirms a reduction in the Ti 3+ donor density from 2.97 × 10 17 cm −3 for the non-doped material to ∼6.24 × 10 16 cm −3 for 5% Ga-doped LaTiO 2 N. The remaining Ti 3+ defects are concentrated near the LaTiO 2 N surface, according to X-ray photoelectron spectroscopy. The defect reduction shifts the optical absorption edge from 2.02 to 2.09 eV and eliminates a broad absorption band at 1050 nm from the optical absorption spectra. It also removes a 1.0–1.7 eV sub-band gap photovoltage signal from surface photovoltage spectra. This suggests that empty Ti 3+ d-orbitals are located 1.0–1.7 eV above the LaTiO 2 N valence band edge. Removing these recombination states with increasing Ga 3+ content enhances the photoconversion efficiency of LaTiO 2 N during water oxidation. The optimized 2 wt% CoO x -loaded 5% Ga-doped LaTi O2 N material has a 16% AQE (400 nm) for O 2 production from aqueous silver nitrate solution and a ∼2.1 mA cm −2 water oxidation photocurrent at 1.23 V under 100 mW cm −2 Xe arc lamp illumination. The water oxidation photocurrent is stable during a 50 min test, and the Faraday efficiency for O 2 generation is 97%, confirming short-term corrosion stability of LaTiO 2 N. Altogether, these results provide a better understanding of the distribution, concentration, and impact of Ti 3+ defects on the optical, photovoltage, and photoelectrochemical properties of LaTiO 2 N. In combination with other defect control strategies, aliovalent Ga 3+ doping can help bring the solar energy conversion efficiency of LaTiO 2 N closer to the theoretical limit.

Wang, Li [University of California, Davis, CA (Uni

Raman enhancement induced by exciton hybridization in molecules and 2D materials

Abstract Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for trace-level fingerprinting. Recently, layered two-dimensional (2D) materials have gained significant interest as SERS substrates for providing stable, uniform, and reproducible Raman enhancement with the potential for trace-level detection. Yet, the development of effective 2D SERS substrates is still hindered by the lack of fundamental understanding of the coupling mechanism between target molecules and substrates. Here, we report a systematic excitation-dependent Raman spectroscopy investigation on the coupling between 2D materials such as SnS 2 , MoS 2 , WSe 2 , and graphene and small organic molecules like rhodamine 6G (Rh 6G). Strong coupling between SnS 2 and Rh 6G is found due to their degenerate excitons through Raman excitation profiles (REP), leading to the enhancement of Rh 6G vibrational modes that are observable down to 10 −13 M. Our study shows that exciton coupling in the substrate-adsorbate complex plays a vital role in the Raman enhancement effect, opening a new route for designing SERS substrates for high sensitivity.

Materials Science

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst

Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanotomography technique based on sparse dynamic imaging and 4D tomography modeling. We demonstrated the technique, using ptychographic x-ray computed tomography as its imaging modality, on resolving the in situ hydration process of polymer electrolyte fuel cell (PEFC) catalyst. The technique provides a 40-time increase in temporal resolution compared to conventional approaches, yielding 28 nm half-period spatial and 12 min temporal resolution. The results allow a quantitative characterization of the water intake process inside PEFC catalysts with nanoscale resolution, which is crucial for understanding their electrochemical mechanisms and optimizing their performance. Our technique enables high-speed operando nanotomography studies and paves the way for wider application of dynamic tomography at the nanoscale.

Science & Technology - Other Topics

The Hawaii Meteorology, Energy and Transmission (MET) Toolkit

Reliable long-term resource adequacy and grid planning in Hawaii require precise, multi-decadal meteorological records. This paper introduces the Hawaii Meteorology, Energy and Transmission (MET) Toolkit, a 26-year (2000-2025) high-fidelity atmospheric dataset developed by the National Laboratory of the Rockies (NLR). We present a validation study of the underlying WRF model configurations, comparing the legacy MYNN PBL scheme against an alternative YSU formulation. Using vertical lidar profiles and surface buoy data, our analysis identified a foundational geometric distortion in the legacy NOW-23 Hawaii dataset caused by an incorrect grid projection. When evaluated on a corrected, zero-distortion grid, the YSU scheme demonstrated superior performance in bias and cRMSE compared to the legacy setup. To address these findings, the MET Toolkit has been re-produced as a unified 26-year record using the optimized YSU setup and corrected geometry. This dataset offers the Hawaii power sector a robust, validated, and homogenous reference for future grid resilience and energy integration.

24 POWER TRANSMISSION AND DISTRIBUTION

Comparative Assessment of Battery Carbon Footprint Calculation Frameworks to Support U.S. Battery Manufacturing

A “battery passport” is a digital record that provides comprehensive information about an individual battery across its life cycle. This concept has been introduced by Battery Regulation (EU) 2023/1542 [1], which applies to batteries for electric vehicles (EVs), industrial batteries with a capacities greater than 2 kWh, and batteries for light means of transport (LMT) greater than 2kWh sold in the European Union (EU) market – impacting manufacturers and exporters across multiple jurisdictions globally. Among its reporting mandates, a key feature of battery passports is the requirement for a carbon footprint (CF) calculation methodology supported by enhanced data granularity to enable traceable and verifiable CF results. While no other jurisdictions have yet adopted formal battery passport requirements like the EU’s, some are developing CF calculation methods to comply with the EU Battery Regulation or are creating CF-related regulations that could evolve in a similar direction, reflecting the growing importance of battery CF guidelines for manufacturers seeking to remain competitive in global markets.

Zhang, Jingyi [Argonne National Laboratory (ANL),