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The Renewable Energy (RE) Data Explorer is an innovative and intuitive web platform from the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Partnership that enables users to easily access high-quality renewable energy resource data and applied analytics.
The hydrogen storage system modeling project aims to develop new and enhance existing material-based hydrogen storage system models and make them accessible to the research community through a public web page. Updating existing storage systems models supports material developers in evaluating the performance of their new materials in mobile and stationary applications relative to the available DOE Technical Targets. Developing new tools helps researchers evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. New models will also work for validating alternatives to material-based systems (liquefied & gaseous hydrogen), comparing various mobile and stationary use cases, and expand to include medium-, heavy-duty, and mining vehicles and stationary application(s).
An exemplary system, method, and computer-accessible medium for determining a property(ies) regarding an electrical grid(s) can be provided, which can include, for example, receiving a video(s) of the electrical grid(s), determining a flicker(s) in the electrical grid(s) based on the video(s), and determining the property(ies) based on the flicker(s). The flicker(s) can be a 120 Hertz flicker. The flicker(s) can be a flicker in a light(s) recorded in the video(s). A frequency and a phase of the flicker(s) can be determined.
An electronic device is described that handles control transfer instructions (CTIs) when executing instructions in program code. The electronic device has a processor that includes a branch prediction functional block and a sequential fetch logic functional block. The sequential fetch logic functional block determines, based on a record associated with a CTI, that a specified number of fetch groups of instructions that were previously determined to include no CTIs are to be fetched for execution in sequence following the CTI. When each of the specified number of fetch groups is fetched and prepared for execution, the sequential fetch logic prevents corresponding accesses of the branch prediction functional block for acquiring branch prediction information for instructions in that fetch group.
In accordance with the purpose(s) of the present disclosure, as embodied and broadly described herein, embodiments of the present disclosure, in one aspect, relate to methods of making a structure including nanotubes, a structure including nanotubes, methods of delivering a fluid to a cell, methods of removing a fluid to a cell, methods of accessing intracellular space, and the like.
The overall vision of this project is to provide ownership and support for maintaining existing material-based hydrogen storage systems models. This includes making models accessible to the research community through a public web page and updating and enhancing storage systems models to support material developers in assessing their materials relative to DOE vehicle-level targets. Key elements for FY24: Continue to update and enhance existing models for broader application and user-friendliness. Develop tools to evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. Expand the application of current hydrogen storage models beyond light-duty vehicles to include medium-, heavy-duty, and mining vehicles and stationary application(s). Develop models for alternatives, such as LOHCs, to material-based systems (liquefied & gaseous H2) and compare for various mobile and stationary use cases.
The present disclosure provides collaborative radiofrequency identification (RFID) readers that employ code division multiple access (CDMA) encoding to simultaneously broadcast to and read responses from tags in an overlapping reading zone with improved data synchronization and read yield rates. In some embodiments, a harmonic backscattering scheme is used to enable the system to have a much higher signal-to-noise ratio (SNR) and sensitivity, while the reader CDMA protocol can be integrated with an initial TDMA polling process or alternative tag CDMA scheme.
REopt is a techno-economic analysis platform accessible as a user-friendly web tool that facilitates life cycle cost analysis of distributed energy resources. It is typically used for preliminary assessments to identify the least-cost technology mix, system sizing, and operations strategies towards agency cost savings and resilience goals. This guide identifies and explains REopt inputs for federal life cycle cost analyses, modified from their commercial default values. These federal input defaults are based on statutory requirements for life cycle cost analyses of energy conservation measures at federal facilities per 10 CFR 436 Subpart A.
Innovative Interactive 3D Slice Visualization Tool: Bridging Accessibility, Insight, and Immersive Analysis for Complex Data Exploration
Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.
Rooftop solar photovoltaic (PV) adoption can benefit households by reducing electricity bills and enhancing energy resiliency. Low and moderate-income (LMI) households have been less likely to adopt PV and experience these benefits in the United States than higher-income households. Adopter income trends are often explored through quantitative analysis with limited explanatory power. Our quantitative analysis only explains around one-third of city-level variation in LMI adoption trends through socioeconomic factors such as median home values and income inequality and PV market factors such as cumulative adoption and incentives. We implement semi-structured interviews in three case studies of cities with relatively high rates of LMI PV adoption to better understand the factors that explain PV adopter income trends. The case studies partly reiterate findings from quantitative analysis, such as the role of PV incentives. The case studies reveal a broader set of LMI adoption drivers that are missed in quantitative analyses. The case studies show how city contexts can affect LMI adoption, such as the role of supportive city governments. The case studies also reveal the importance of partnerships, such as partnerships between city governments and state LMI PV program implementers. Finally, interviewees emphasized the importance of building trust among prospective LMI PV adopters. Interviewees suggested that partnerships, outreach, and consumer protection measures were crucial to building trust in PV installers among LMI households.
Objective: To develop and evaluate an automated system for identifying healthcare barriers focusing on transportation issues in veterans’ clinical notes using large language models (LLMs) and to assess the impact of different prompting strategies on classification performance and explanation consistency. Methods: We developed a hybrid system combining pattern matching for templated notes with LLM analysis for free-text notes. Using 2000 manually annotated clinical notes, we compared four prompting strategies (dual-role short, dual-role long, analysis-first, analysis-only) across Mistral-7B and Llama-3.1 models. We evaluated classification performance using standard metrics and assessed explanation consistency through embedding similarity analysis. Results: The analysis-first strategy achieved superior performance, with Mistral-7B reaching an F1 score of 0.914, outperforming traditional machine learning approaches (GBM: 0.786, BERT: 0.811). LLMs demonstrated higher explanation consistency within models (mean cosine similarity 0.887–0.908) compared to cross-model similarities (0.767–0.872). Pattern matching successfully handled 6.7% of templated notes deterministically. Mistral-7B showed greater internal consistency but higher abstention rates compared to Llama-3.1. Conclusion: Requiring LLMs to analyze evidence before classification improves both accuracy and explanation consistency for identifying transportation barriers in clinical notes. This approach enables automated barrier detection at scale while providing clinically relevant explanations, supporting both population-level healthcare planning and individual patient care decisions.
We present an approach for minimizing the critical current for the magnetization switching in magnetic tunnel junctions by optimizing the spatial distribution of the current density. We show that such a minimization is possible because critical current is determined by the condition of making one of the magnetization eigenstates grow in time. The excitation of the eigenstates is enhanced when the spatial distributions of the eigenstates and current density overlap. Critical current can be viewed as a functional of the current density spatial distribution and it can be minimized by optimizing this distribution. Such an optimization results in a major reduction of the critical current and increase of the switching efficiency, viz. the ratio between the energy barrier and critical current. The minimized critical current increases approximately linearly with the magnetic tunnel junction size, which is much slower than critical current for the case of a uniform current density. The optimized efficiency can be approximately a constant with respect to the magnetic tunnel junction size, which is much higher than the efficiency for the uniform current density. Additional optimization can be achieved by spatially modulating the material parameters, e.g., the saturation magnetization. The presented approach and obtained scaling of the critical current and efficiency offers opportunities for the magnetic tunnel junction optimization.
Brønsted (BAS), Lewis (LAS), and surface Brønsted (SBAS) acid sites have been investigated for polyethylene (PE) upcycling by zeolite catalysts, but there is no clear consensus regarding their catalytic roles, partly due to the complexity of the catalysts used and varying reaction conditions across studies. This work systematically determined how these sites impact PE conversion rates and product distributions by utilizing a suite of microporous MFI catalysts with varying Si/Al ratios, acid site densities, and inherent mesoporosities. PE conversion rates did not trend with total BAS or LAS densities due to a combination of internal mass transfer limitation and the apparent inability of LAS alone to cleave C–C bonds, but a strong, statistically significant correlation was present with respect to SBAS density and mesopore surface area, jointly, owing to accelerated polymer activation on external surfaces to smaller diffusion-limited chains. However, ingress of these SBAS-derived fragments ultimately remained rate limiting, as demonstrated by solid conversion rates that increased with mesopore surface area at similar SBAS density and likewise increased with SBAS density at similar mesopore surface area. In batch PE cracking reactions, light gaseous product selectivities were most sensitive to total BAS, with higher densities generally exhibiting higher selectivity to C 3 and linear C 4 –C 7 products and higher alkane/alkene product ratios, consistent with increased β-scission turnovers. Insights from this work help systematically clarify the roles of BAS, LAS, SBAS, and mesopores in PE cracking reactions and inform the development of tailored zeolite catalysts for efficient polyolefin upcycling.
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In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.
Abstract Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow.