FY2021 January Monthly Status Report for the Versatile Test Reactor
FY2021 January Monthly Status Report for the Versatile Test Reactor
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FY2021 January Monthly Status Report for the Versatile Test Reactor
This annual report of the Alternative Fuel Transportation Program, which ensures compliance with DOE regulations covering state government and alternative fuel provider fleets pursuant to the Energy Policy Act of 1992 (EPAct), as amended, provides fleet compliance results for manufacturing year 2021/fiscal year 2022.
It is my privilege to present this year’s annual report for the National Reactor Innovation Center (NRIC). Now rounding out our fourth year of operation, NRIC is poised for successfully delivering our most foundational promise: to accelerate the testing and demonstration of advanced nuclear technology by providing access to national laboratory assets and expertise. Some specific goals include: • Establish and maintain four new experimental facility capabilities: o MSTEC – 2025 o METL – Operational o HeCTF – Operational o Creep Frames – 2026 • Construct and operationalize two advanced reactor test beds (DOME and LOTUS) for integrated technology demonstrations and experimentation – 2028 • Complete minimum of two advanced nuclear technology tests – 2030 o Advanced Construction Technology – 2025 o Advanced Microreactor test in DOME or LOTUS – 2027 & 2029
FOURTH QUARTER / ANNUAL TRANSPORTATION REPORT FISCAL YEAR 2023
This annual report of the Alternative Fuel Transportation Program, which ensures compliance with U.S. Department of Energy regulations covering state government and alternative fuel provider fleets pursuant to the Energy Policy Act of 1992 (EPAct), as amended, provides fleet compliance results for manufacturing year 2022/fiscal year 2023.
The Microscopy and Characterization Suite (MaCS) laboratory at the Center for Advanced Energy Studies (CAES) and the National Synchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL) partner with the Nuclear Science User Facilities (NSUF). This partnership provides funding that allows researchers to access these facilities at no cost for studying irradiation effects on nuclear fuels and materials. Through NSUF, both MaCS and NSLS-II support post-irradiation examination (PIE) and irradiation activities for NSUF Rapid Turnaround Experiments (RTE) and NSUF Consolidated Innovative Nuclear Research (CINR) awards. This report details the work completed at these facilities for NSUF competitively selected awards during fiscal year 2024.
Final Technical Report for DE‐SC0020289
The FY25 Advanced Fuels Campaign (AFC) Accomplishments Report is a compilation of milestones and achievements from FY25.
Nonaqueous conversion-reaction sulfur chemistry has been attracting increasing attention over the past decade for the development of next-generation lithium-based batteries. Li–S batteries are currently approaching a nexus stage from lab-scale experiments to possible pragmatic applications. Inspired by the success of Li–S chemistry, other metal–sulfur batteries with a variety of metallic anodes, such as sodium, potassium, magnesium, calcium, and aluminum, have also started to attract attention. In comparison to lithium, Na, Mg, Al, K, and Ca are naturally more abundant and affordable. The Na-S, Mg-S, Al-S, K-S, and Ca-S battery systems provide a great potential for improving the volumetric energy density of sulfur-based batteries. The multivalent metal-sulfur systems, Mg-S, Al-S, and Ca-S, offer better safety features as well. However, the research and development on Na-S, Mg-S, Al-S, K-S, and Ca-S batteries is far behind the Li–S system due to many critical challenges. In this progress report, the fundamental principles of various metal–sulfur chemistries are first presented and compared. Then, the historical progress, recent advances, and key challenges of the Li–S, Na-S, Mg-S, Al-S, K-S, and Ca-S systems are summarized and discussed. Finally, future efforts and directions for both the fundamental and practical research are prospected.
Photon interconversion generally describes processes which change the wavelength of the emitted light upon irradiation, with a gain in photon energy (upconversion), or a splitting of the incident photon energy to create multiple photons (downconversion). The focus of this progress report is placed on halide perovskite materials and their role in upconversion by triplet-triplet annihilation and downconversion via singlet fission in organic semiconductors, and a short perspective is given into quantum cutting and lanthanide-based upconversion applications. The current advances are highlighted regarding halide perovskites and perovskite-inspired materials with varying framework and material dimensionalities, as relating to photon interconversion processes. Here, the majority of the literature is based on 3D perovskites, which leaves room for growth for perovskite materials with varying dimensionalities. Gaps in the current field are emphasized, leading to a bright outlook on future possibilities of coupling perovskites to photon interconversion mechanisms, which can open the door for future breakthroughs in this field.
With the interfacial jamming of nanoparticles (NPs), a load-bearing network of NPs forms as the areal density of NPs increases, converting the assembly from a liquid-like into a solid-like assembly. Unlike vitrification, the lineal packing of the NPs in the network is denser, while the remaining NPs can remain in a liquid-like state. It is a challenge to determine the point at which the assemblies jam, since both jamming and vitrification lead to a solid-like behavior of the assemblies. Herein, we show a real-time fluorescence imaging method to probe the evolution of the interfacial dynamics of NP surfactants at the water/oil interface using aggregation-induced emission (AIE) as a reporter for the transition of the assemblies into the jammed state. The AIEgens show typical fluorescence behavior at densities at which they can move and rotate. However, when aggregation of these fluorophores occurs, the smaller intermolecular separation distance arrests rotation, and a significant enhancement in the fluorescence intensity occurs.
The state of health (SOH) is a critical measure for evaluating and predicting performance of redox flow batteries (RFBs). However, diagnosing SOH of RFBs is often challenging due to the overwhelming complexity of the electrolytes and associated electrochemical reactions. Designing active molecules or redoxmers that can autonomously exhibit property changes upon specific stimuli may provide a viable way for early diagnosis of SOH. Herein, a dimerized redoxmer, DGL-N-CH 3 , was designed and synthesized by linking blue-green fluorescent monomers through a diglycolamide linker. While DGL-N-CH 3 still maintains similar electrochemical behavior and strong fluorescence, we observe a unique side reaction when cycling DGL-N-CH 3 in H-cells, which leads to a side product, NHCH 3 -BzNSN via linker cleavage. Interestingly, NHCH 3 -BzNSN also emits fluorescence but at a longer wavelength. By taking advantage of this unique fluorescent change that corresponds to the growth of NHCH 3 -BzNSN, we successfully established the capacity decay of DGL-N-CH 3 H-cell cycling, exemplifying a proof-of-concept self-reporting redoxmer design towards in situ SOH monitoring.
The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.
Fluorescent protein reporters have been widely used for monitoring the expression of target genes in various engineered organisms. Although a wide range of analytical approaches (e.g., genotyping PCR, digital PCR, DNA sequencing) have been utilized to detect and identify genome editing reagents and transgene expression in genetically modified plants, these methods are usually limited to use in the late stages of plant transformation and can only be used invasively. Here we describe GFP- and eYGFPuv-based strategies and methods for assessing and detecting genome editing reagents and transgene expression in plants, including protoplast transformation, leaf infiltration, and stable transformation. These methods and strategies enable easy, noninvasive screening of genome editing and transgenic events in plants.
Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.
In today’s LCA world, one can encounter a variety of LCA practitioners and commissioners from different industries and fields of research who have different levels of expertise, experience, and expectations. Even those with more experience who are actively involved in the field of LCA can have rather varying opinions about what ISO 14044 requires (or does not require) regarding the preparation, critical review, and dissemination of third-party reports in accordance with ISO 14044:2006, clauses 5 and 6 (ISO 2006a).
Computing plays a significant role in all areas of high energy physics. The Snowmass 2021 CompF4 topical group's scope is facilities R&D, where we consider "facilities" as the computing hardware and software infrastructure inside the data centers plus the networking between data centers, irrespective of who owns them, and what policies are applied for using them. In other words, it includes commercial clouds, federally funded High Performance Computing (HPC) systems for all of science, and systems funded explicitly for a given experimental or theoretical program. This topical group report summarizes the findings and recommendations for the storage, processing, networking and associated software service infrastructures for future high energy physics research, based on the discussions organized through the Snowmass 2021 community study.
Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.