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At least 1,531 records · Page 85

Advanced techniques for characterization of ion beam modified materials

Understanding the mechanisms of damage formation in materials irradiated with energetic ions is essential for the field of ion-beam materials modification and engineering. Utilizing incident ions, electrons, photons, and positrons, various analysis techniques, including Rutherford backscattering spectrometry (RBS), electron RBS, Raman spectroscopy, high-resolution X-ray diffraction, small-angle X-ray scattering, and positron annihilation spectroscopy, are routinely used or gaining increasing attention in characterizing ion beam modified materials. The distinctive information, recent developments, and some perspectives in these techniques are reviewed in this paper. Applications of these techniques are discussed to demonstrate their unique ability for studying ion-solid interactions and the corresponding radiation effects in modified depths ranging from a few nm to a few tens of μm, and to provide information on electronic and atomic structure of the materials, defect configuration and concentration, as well as phase stability, amorphization and recrystallization processes. Finally, such knowledge contributes to our fundamental understanding over a wide range of extreme conditions essential for enhancing material performance and also for design and synthesis of new materials to address a broad variety of future energy applications.

36 MATERIALS SCIENCE↗

The high-redshift gamma-ray burst GRB 140515A

High-redshift gamma-ray bursts (GRBs) offer several advantages when studying the distant Universe, providing unique information about the structure and properties of the galaxies in which they exploded. Spectroscopic identification with large ground-based telescopes has improved our knowledge of this kind of distant events. We present the multi-wavelength analysis of the high-zSwift GRB GRB 140515A (z = 6.327). The best estimate of the neutral hydrogen fraction of the intergalactic medium towards the burst is x HI ≤ 0.002. The spectral absorption lines detected for this event are the weakest lines ever observed in GRB afterglows, suggesting that GRB 140515A exploded in a very low-density environment. Its circum-burst medium is characterised by an average extinction (AV ~ 0.1) that seems to be typical of z ≥ 6 events. The observed multi-band light curves are explained either with a very hard injected spectrum (p = 1.7) or with a multi-component emission (p = 2.1). In the second case a long-lasting central engine activity is needed in order to explain the late time X-ray emission. Furthermore, the possible origin of GRB 140515A in a Pop III (or in a Pop II star with a local environment enriched by Pop III) massive star is unlikely.

79 ASTRONOMY AND ASTROPHYSICS↗

Protein-based models offer mechanistic insight into complex nickel metalloenzymes

There are ten nickel enzymes found across biological systems, each with a distinct active site and reactivity that spans reductive, oxidative, and redox–neutral processes. We focus on the reductive enzymes, which catalyze reactions that are highly germane to the modern-day climate crisis: [NiFe] hydrogenase, carbon monoxide dehydrogenase, acetyl coenzyme A synthase, and methyl coenzyme M reductase. The current mechanistic understanding of each enzyme system is reviewed along with existing knowledge gaps, which are addressed through the development of protein-derived models, as described here. Finally, this opinion is intended to highlight the advantages of using robust protein scaffolds for modeling multiscale contributions to reactivity and inspire the development of novel artificial metalloenzymes for other small molecule transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Minimal implicit-solvent coarse-grained simulation of Pluronic block copolymers with ionic liquids

Pluronic block copolymers, composed of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO) in a triblock structure (PEO–PPO–PEO), are well known for their amphiphilic character and ability to self‐assemble into micelles in aqueous solution. The addition of ionic liquids (ILs) can further modulate the core–shell structures of these copolymers, influencing their stability, critical micellization temperature, and size. However, fully atomistic simulations often become prohibitively expensive due to the size and complexity of these systems. In this work, coarse‐grained simulations using a minimal implicit‐solvent model were performed to examine how two classes of ILs, namely, 1‐alkyl‐3‐methylimidazolium ([C n C 1 im]) and 1‐alkyl‐3‐methylpyrrolidinium ([C n C 1 pyrr]), change the micellization of Pluronic block copolymers in aqueous solution. The effects of IL concentration and alkyl group length were investigated, and the model greatly improved the efficiency of simulating large‐scale micelle systems. Furthermore, the numerical simulations are qualitatively compared with experimental investigations. Our results show that adding ILs expands the micelle core by embedding IL tails among the PPO blocks, thereby increasing overall micelle size. Less polar ILs generally induce more pronounced micellar growth. However, the effect of IL tail length on conformation and micellar packing is non‐monotonic. Up to moderate chain lengths (around C8–C10), the IL tails can extend sufficiently to increase local separation within the micelle; at longer tail lengths, enhanced hydrophobic clustering and steric hindrance cause the tails to bend or fold, capping further expansion. In addition, although block copolymer chains tend to pack more closely in the presence of longer‐tailed ILs, the random coil size of an individual polymer chain does not necessarily shrink. Meanwhile, these insights provide a deeper understanding of how Pluronic/IL systems interact, informing applications in drug delivery, cosmetics, food, and environmental engineering. Finally, our minimal implicit‐solvent model can be applied to larger systems and longer timescales, substantially reducing computational cost while reproducing key structural trends observed experimentally.

Atomistic simulations↗

Fault Detection via Occupation Kernel Principal Component Analysis

Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In this letter, we present a novel principal component analysis (PCA) method that uses occupation kernels. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA. The occupation kernel PCA method is used to develop a reconstruction error approach to fault detection and its efficacy is validated using numerical simulations.

42 ENGINEERING↗

Fiber Optic Temperature Sensor Using Dual Air- Filled Fabry-Pérot Cavities With Variable Pressure

We present an approach for high temperature measurement using a pair of fiber-optic Fabry–Pérot (FP) cavities filled with gas of identical but variable pressure. One of the FPs (reference FP) is placed in the cold zone with a known temperature. The temperature of the measuring FP can be deduced by the spectral fringe shift vs. pressure of the two FPs. This method does not require measurement of the pressure or the knowledge of the optical properties of the gas. The use of gas as the sensing material and the measurement mechanism also implies long-term stability and eliminates the cross-sensitivity to strain. We fabricated the sensors and tested them for measuring temperature up to 800 °C. Here, the sensor shows good linearity in the range. Long-term test conducted at 800 °C exhibited the stability of the sensor with fluctuations of ≤0.3% over a duration exceeding 100 hours.

42 ENGINEERING↗

Innovations in Advanced Materials and Metals Manufacturing Project (IAM2)

This project, under the Jobs and Innovation Accelerator Challenge, Innovations in Advanced Materials and Metals Manufacturing Project, contracted with Cascade Energy to provide a shared energy project manager engineer to work with five different companies throughout the Portland metro grant region to implement ten energy efficiency projects and develop a case study to analyze the project model. As a part of the project, the energy project manager also looked into specific new technologies and methodologies that could change the way energy is consumed by manufacturers—from game-changing equipment and technology to monitor energy use to methodologies that change the way companies interact and use their machines to reduce energy consumption.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Subsystem Estimation: A Modal Decomposition Approach

In structural analysis it is often the requirement that the response of a critical subsystem must be extracted from the response of the overall structure even when not directly excited or sometimes even measured. Based on this requirement, a number of signal processing approaches evolve that can provide a meaningful solution to this troubling problem; however, there is a variety of prior information (parameters or data) that must be available. For instance, knowledge of subsystem bandwidth may be enough to design a simple filter if there is little or no overlap with other component systems. If this is not satisfactory and a specific spectral response is required, then a model-based approach can be applied using an available free-free response of the subsystem from calibration or acceptance tests. However, when assembled and coupled with the overall system, the subsystem boundary conditions have been altered and therefore its response is altered as well.

42 ENGINEERING↗

Nuclear data for space exploration

Understanding the harmful effects of galactic cosmic rays (GCRs) on space exploration requires a substantial amount of nuclear data. Specifically, the interaction of energetic GCR charged particles with spacecraft materials generates secondary radiations that, through energy deposition, can harm astronauts and electronic systems. By identifying the gaps in our knowledge of the relevant nuclear data—such as interaction cross sections—and identifying ways to fill those gaps—with measurements, compilations, evaluations, dissemination, reaction modeling, sensitivity studies, and uncertainty quantification—the safety and viability of space exploration can be improved. This work surveys the state of the art in this interdisciplinary field and identifies promising collaborative research topics that have significant potential to advance our understanding of the effects of the space radiation environment on space exploration.

42 ENGINEERING↗

Place Based STEM: Leveraging Local Resources to Engage K-12 Teachers in Teaching Integrated STEM and for Addressing the Local STEM Pipeline

Business, industry, parks, nature settings, government infrastructure, and people, can be invaluable resources for connecting STEM curriculum within context which results in conditions ideal for promoting purposeful learning of authentic STEM content. Thus, community-based STEM resources offer ideal context for teaching STEM content. A benefit of focusing teacher attention on these contextual, content aligned resources is that they are in every community; making place-based STEM education a possibility, regardless of the location of STEM teaching and learning. Further, associating STEM teaching and learning with local resources addresses workforce development and the STEM pipeline by exposing students to STEM careers and applications in their local communities. The desire to align STEM teaching and learning with local STEM related resources guided the design of our week-long integrated STEM K-12 teacher professional development (PD) program, i-STEM. We have completed four years of our i-STEM PD program and have made place-based STEM a major emphasis of our curriculum. This report focuses on the data collected in the fourth year of our program. Our week-long i-STEM PD served over 425 educators last summer (2013), providing them with in depth theme-based integrated STEM short courses which were limited to an average of 15 participants and whole group plenary sessions focused around placed based integrated STEM, inquiry, engineering design, standards and practices of Common Core and 21st Century skills. This state wide PD was distributed in five Idaho community colleges and took place over two weeks. The STEM short courses included topics on engineering for sustainability, using engineering to spark interest in STEM, municipal water systems, health, agriculture, food safety, mining, forestry, energy, and others. Integral to these short courses were field trips designed to connect the K-12 educators to the resources in their local communities that could be leveraged for teaching integrated STEM and provide a relevant context for teaching STEM content. Workplace presentations made by place-based STEM experts and provided teachers field trips to place-base STEM industries and business such as manufacturing plants, waste water treatment systems, mines, nature parks, food processing plants, research, hospitals, and laboratory facilities. We researched the 425 participants’ conceptions of place-based STEM prior to and after their taking part in the summer institutes, which included fieldtrips. Our findings revealed substantial increase in our participants’ knowledge, interest, and plans to use place-based resources for teaching integrated STEM. We detail the data analysis and provide a theoretical foundation and justification for the importance of place-based STEM to address the STEM pipeline for the future workforce.

99 GENERAL AND MISCELLANEOUS↗

Cyber Threat and Vulnerability Analysis of the U.S. Electric Sector

With utilities in the U.S. and around the world increasingly moving toward smart grid technology and other upgrades with inherent cyber vulnerabilities, correlative threats from malicious cyber attacks on the North American electric grid continue to grow in frequency and sophistication. The potential for malicious actors to access and adversely affect physical electricity assets of U.S. electricity generation, transmission, or distribution systems via cyber means is a primary concern for utilities contributing to the bulk electric system. This paper seeks to illustrate the current cyber-physical landscape of the U.S. electric sector in the context of its vulnerabilities to cyber attacks, the likelihood of cyber attacks, and the impacts cyber events and threat actors can achieve on the power grid. In addition, this paper highlights utility perspectives, perceived challenges, and requests for assistance in addressing cyber threats to the electric sector. There have been no reported targeted cyber attacks carried out against utilities in the U.S. that have resulted in permanent or long term damage to power system operations thus far, yet electric utilities throughout the U.S. have seen a steady rise in cyber and physical security related events that continue to raise concern. Asset owners and operators understand that the effects of a coordinated cyber and physical attack on a utility’s operations would threaten electric system reliability–and potentially result in large scale power outages. Utilities are routinely faced with new challenges for dealing with these cyber threats to the grid and consequently maintain a set of best practices to keep systems secure and up to date. Among the greatest challenges is a lack of knowledge or strategy to mitigate new risks that emerge as a result of an exponential rise in complexity of modern control systems. This paper compiles an open-source analysis of cyber threats and risks to the electric grid, utility best practices for prevention and response to cyber threats, and utility suggestions about how the federal government can aid utilities in combating and mitigating risks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Overview of SAVY-4000 Lifetime Extension Activities in Fiscal Year 2024

This report provides an overview of activities engaged in during the 2024 fiscal year in support of the SAVY-4000 (hereafter “SAVY”) lifetime extension. As the final full year prior to the submittal of the technical basis, efforts were made to assess the current understanding regarding SAVY degradation in service as well as any knowledge that provided a more substantive view of the challenges that SAVYs face in storage. Close coordination with the stakeholders (i.e. LANL program office) ensured alignment with expectations regarding timelines for the remainder of the activities supporting the technical basis document for the lifetime extension request.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

U.S. Efforts in Support of Examinations at Fukushima Daiichi - September 2024 Meeting Notes

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. Commercial nuclear power plants. A collaborative U.S. and Japanese effort was initiated in 2014 by the Department of Energy Office of Nuclear Energy to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This document summarizes information presented at and findings, action items, and recommendations by U.S. and Japanese experts in reactor safety and plant operations during the September 2024 Forensics Effort meeting. Significant safety insights were obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties and knowledge gaps in severe accident modeling progression, these insights continue to be used to assess whether additional updates are needed in guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional safety and economic benefits to the operating fleet and new light water reactor (LWR) and non-LWR designs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Summary of a Workshop on Integrating Energy Equity into Power System Planning and Operation

On November 29 and 30, 2023, the Energy Systems Integration Group convened a one-and-a-half-day workshop in Arlington, Virginia, to improve knowledge and practices for integrating energy equity considerations into power system planning and operation. Workshop participants were invited to discuss approaches for integrating energy equity aspects into models and tools and to explore possible pathways for enhanced technical practices. Participants included utility planning and modeling practitioners, social science and energy justice academics, representatives from energy and environmental justice nongovernmental organizations, non-profits, consumer advocates, and representatives from the U.S. Department of Energy, national labs, and other government agencies. This report summarizes the discussion points and outcomes of the workshop, which prioritized the technical aspects of incorporating the challenges and solutions identified by electricity-futures stakeholders and communities. These technical activities include the fundamental grid structure and hardware, detailed modeling approaches that benchmark energy system performance and justify future investments, and engineering designs and limitations for potential solutions to meet energy equity goals in communities.

energy equity↗

Facile and Scalable Synthesis of Metal- and Nitrogen-Doped Carbon Nanotubes for Efficient Electrochemical CO 2 Reduction

Metal- and nitrogen-doped carbon (M–N–C) is a promising material to catalyze electrochemical CO 2 reduction reaction (CO 2 RR). However, most M–N–C catalysts in the literature require complicated synthesis procedures and produce small quantities per batch, limiting the commercialization potential. In this work, we developed a simple and scalable synthesis method to convert metal-impurity-containing commercial carbon nanotubes (CNTs) and nitrogen-containing organic precursors into M–N–C via one-step moderate-temperature (650 °C) pyrolysis without any other treatment nor the need to add metal precursors. Batches of catalysts in varied mass up to 10 g (150 mL in volume) per batch were synthesized, and repeatable catalytic performances were demonstrated. To the best of our knowledge, the 10 g batch is one of the largest batches of CO2RR catalysts synthesized in the literature while requiring minimal synthesis steps. The catalyst possessed single-atomic iron–nitrogen (Fe–N) sites, enabling a high performance of >95% CO product selectivity at a high current density of 400 mA/cm 2 and high stability for 45 h at 100 mA/cm 2 in a flow cell testing. The catalyst outperformed a benchmark noble-metal nanoparticle catalyst and achieved longer stability than many other reported M–N–C catalysts in the literature. The scalable and cost-effective synthesis developed in this work paves a pathway toward practical CO 2 RR applications. The direct utilization of metal impurities from raw CNTs for efficient catalyst synthesis with minimal treatment is a green and sustainable engineering approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing Protein Display on Bacterial Spores through an Extensive Survey of Coat Components

The profound stability of bacterial spores makes them a promising platform for biotechnological applications like biocatalysis, bioremediation, drug delivery, etc. However, though the Bacillus subtilis spore is composed of >40 types of proteins, only ∼12 have been explored as fusion carriers for protein display. Here, we assessed the suitability of 33 spore proteins (SPs) as enzyme display carriers by direct allele tagging at native genomic loci. Of the 33 SPs investigated, 26 formed functional fusions with β-glucuronidase (GUS)─a ∼272 kDa homotetramer. This almost triples the number of SPs assessed for enzyme display and doubles the number of functional fusions documented in the literature. We quantitatively assessed 1) SP promoter activation dynamics, 2) GUS activity on spores, 3) surface availability, and 4) protection from thermal and proteolytic degradation. Multicopy expression and pairwise coexpression of the most promising SP-GUS fusions highlighted the complexity of spore structure/assembly and the difficulty in predicting compatibility between different SP fusions. We also assessed the suitability of engineered spores to degrade PET (polyethylene terephthalate) films and found that surface-exposed SPs were most effective. Beyond the broad survey, a key outcome of our work was the identification of SscA (small spore coat assembly protein A) as an effective spore display carrier. SscA supported enzyme activity at least 4-fold higher than any other SP, including the well-established anchor, CotY. We attribute this to its promoter, which demonstrated early and sustained activation relative to other SPs and its small size (∼3 kDa), which likely minimally interferes with enzyme folding, oligomerization, and activity. Labeling and genetic studies, its hydrophobic nature, and low surface availability suggest that SscA assembles within the inner spore coat, which makes it stabilizing and suitable for many biocatalytic applications. Overall, this work serves as a knowledge base to advance the biotechnological utility of B. subtilis spores.

Bacillus subtilis↗

A review of hydrokinetic turbines and enhancement techniques for canal installations: Technology, applicability and potential

The hydrokinetic industry has advanced beyond its initial testing phase with full-scale projects being introduced, constructed and tested globally. However primary hurdles such as reducing the cost of these systems, optimizing individual systems and arrays and balancing energy extraction with environmental impact still requires attention prior to achieving commercial success. The present study addresses the advances and limitations of near-zero head hydrokinetic technologies and the possibility of increased potential and applicability when enhancement techniques within the design, implementation and operational phases are considered. Its goal is threefold: to review small-scale state-of-the-art near-zero hydrokinetic-current-energy-conversion-technologies, to assess barriers including gaps in knowledge, information and data as well as assess time and resource limitations of water-infrastructure owners and operators. A case study summarizes the design and implementation of the first permanent modern hydrokinetic installation in South Africa where improved outputs were achieved through optimization during each design and operation phase. Finally, an economic analysis validates a competitive levelized cost of energy and further emphasizes the broad potential that is relatively unexplored within existing water-infrastructure.

42 ENGINEERING↗

Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements

Here, this study presents a novel approach for the precise monitoring and prognosis of photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems. It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability of inverters, and the limitations of data-driven approaches that largely depend on simulated data. This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and weather-related factors based on domain knowledge. This approach effectively represents inverter stressors and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges operational data with domain knowledge features, redefining the prognosis challenge as a classification task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method developed on the well-trained model. The proposed models are rigorously trained and tested with real inverter data and a novel filtering method is included to address accidental failures in practical scenarios. The results validate the model's efficacy, and the directions for future research are also outlined.

42 ENGINEERING↗