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At least 217 records · Page 12

Technical Assistance Opportunities for Tribes

The National Renewable Energy Laboratory (NREL) offers many forms of technical assistance for Tribes to support local clean energy priorities and challenges. With broad support from the U.S. Department of Energy (DOE) and local partners, NREL provides technical expertise to enable data-driven, informed clean energy decision making. Technical assistance may address energy strategy, project financing, policy design and development, data analysis, economic development, infrastructure planning, energy justice, climate change, resilience, or other energy priorities. NREL has a long history of partnering with Tribes and Tribal organizations, including in Alaska Native Villages where the extreme Arctic climate poses unique energy challenges. NREL works directly with Tribes to find solutions that address their self-defined energy priorities, challenges, and goals.

Alaska native village↗

How to Design and Implement an Equitable Building Performance Standard: Lessons from the Building Performance Standards Technical Assistance Network

States and local governments seek to accomplish the intersecting goals of reducing greenhouse gas emissions, improving building operations, and bettering the daily lives of their communities. Building Performance Standards (BPS) have emerged as a critical policy lever to reach these intertwined climate and societal goals. These policies, if shaped and implemented well, have the chance to not only help reach our nation's climate, energy, and livability goals, but to do so with the active participation of those traditionally excluded from policy processes. This nascent policy movement provides jurisdictions across the country the opportunity to shape these policies from the outset to deliver comfort, health, and safety in our built environment for all. The US Department of Energy in partnership with our National Laboratories have been providing technical assistance for jurisdictions interested in, adopting, and implementing Building Performance Standards. Through this work, the BPS Technical Assistance Network (TA Network) has tracked and documented the innovative and equitable approaches to BPS across the country. The TA Network has crafted foundational technical analysis, such as building stock and emissions impacts, equity prioritization and peak load impacts, and aggregated cost benefit analysis. And by combining powerful technical analysis with dissemination of best practices resources to support equitable implementation, the TA Network provides jurisdictions with the tools and support necessary to embark on their ambitious policy goals.

building performance standards↗

Agrivoltaics Technical Assistance

The second in a series of five fact sheets about agrivoltaics based on themes from U.S. Department of Energy Clean Energy to Communities technical assistance projects, this document includes information about agrivoltaics technical assistance.

agriculture↗

Development and Validation of MALAMUTE model for Electric Field Assisted Sintering of Structural Materials

Fusion power plant designs feature extreme material performance requirements for structural material candidates. In addition to conventional alloys, more advanced composites and oxide dispersion strengthened (ODS) alloys are being explored, however, achieving the desired microstructures to maximize performance using traditional manufacturing methods can be challenging. The advanced manufacturing (AM) electric field-assisted sintering (EFAS) technique offers improved control over the final microstructure through higher heating and cooling rates and moderate pressures. Modeling and simulation tools show promise in elucidating the process-structure-property-performance (PSPP) correlation for AM-produced parts, including the EFAS process. An inherently multiscale process, the EFAS technique aligns well with the multiscale modeling capability of the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE)[cite]. We present here an electro-thermo-mechanical approach to modeling the EFAS process using the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) code. Prediction of the field and gradient distributions across the EFAS tooling is required to accurately describe the conditions for the lower-scale microstructural evolution models. In this work we present the MALAMUTE model developed to predict the electrical potential, temperature, and mechanical stress distribution across the EFAS graphite tooling and part at the larger engineering-scale. Validation of the MALAMUTE engineering-scale model is completed using data from experimental densification and pre-densified runs of iron powder via EFAS at 1000oC. These runs were conducted using a Thermal Technology DCS-5 EFAS system. Data collected during the experiment runs include the direct current (DC) supplied to the graphite tooling, the temperature of the graphite tooling as measured with a pyrometer, and the force applied to the top of the graphite tooling stack, and the data were recorded every 10 seconds. Our validation approach used the current and force data from the EFAS run as boundary condition inputs to the MAMALUTE simulation; the temperature data were used to evaluate the MALAMUTE EFAS model prediction. Results of the MALAMUTE simulations are employed to connect the external pyrometer temperature measurement to the temperature profile across the part undergoing consolidation. We investigate the impact of material property variation and mesh deformation on the temperature profile as predicted by MALAMUTE. We conclude by highlighting projects where the MALAMUTE EFAS modeling and simulation capabilities will be used to assist experimental design.

36 - MATERIALS SCIENCE↗

Microwave-assisted catalytic conversion of waste biomass and plastic feedstocks via thermochemical routes

Microwave-assisted catalytic conversion of waste feedstocks to fuels and value-added chemicals shows incredible promise as an efficient pathway to support the U.S. Department of Energy’s vision toward strengthening the nation’s energy independence. Microwave-heated systems have the potential to outperform conventional technologies through energy-efficient heating and improved product selectivity. This chapter emphasizes microwave-assisted catalytic approaches for waste conversion, allowing maximum energy recovery and extraction of valuable chemicals from waste feedstock such as biomass and plastics while reducing undesired byproducts. A gap remains in understanding how microwaves interact with materials to enable rapid and selective heating, which is crucial for improving catalytic efficiency. This chapter attempts to address this knowledge gap by proposing mechanisms that explain the microwave-catalytic interactions for efficient conversion of biomass-plastic wastes. In addition, comparisons with conventional catalytic technologies as well as the potential for scale ups and future commercialization of microwave-catalytic waste conversion technologies are also discussed.

microwave-assisted catalytic conversion↗

Defense Resilience Technical Assistance Options - Initial Overview

The Defense Resilience Technical Assistance (TA) project, a collaboration between the DOE Grid Deployment Office and the DoD, aims to enhance energy infrastructure at military installations and utilities and the surrounding community. It focuses on improving energy system performance, addressing power infrastructure inadequacies, enhancing power quality, reducing cyber sabotage impacts, and strengthening digital supply chains. Defense Resilience Technical Assistance Options - Initial Overview. Intend to tailor to the pilot installation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Experimental Methods for the Performance Test of Environment-Assisted Cracking (EAC) in Nuclear Industry and Examples through NSUF

Environmentally assisted cracking (EAC) is a critical failure mode in nuclear reactor environments, where materials are exposed to high temperatures, radiation, and corrosive media. Specific EAC studies in nuclear environments include stress corrosion cracking in primary water chemistry, irradiation-assisted stress corrosion cracking (IASCC) under neutron exposure, and hydrogen induced cracking (HIC) in reactor pressure vessels. The experimental methodologies of EAC include slow strain rate testing (SSRT), constant load, and cyclic loading techniques, conducted in autoclaves designed to simulate the reactor’s operational environments. This paper highlights several experimental case studies, especially on IASCC, conducted within the Nuclear Science User Facilities (NSUF).

36 - MATERIALS SCIENCE↗

Salt-Assisted 2H-to-1T' Phase Transformation of Transition Metal Dichalcogenides [plus supplemental information]

Phase engineering of nanomaterials (PEN) has demonstrated great potential in the fields of catalysis, electronics, energy storage and conversion, and condensed matter physics. Recently, transition metal dichalcogenides (TMDs) with unconventional metastable phases (e.g., 1T and 1T') have attracted increasing research interest due to their unique and appealing physicochemical properties. However, there is still a lack of a simple, universal, and controlled method for the preparation of large-scale and high-purity unconventional-phase TMD crystals, restricting their further fundamental study and practical applications. Here, a facile, one-step salt-assisted general strategy is reported for the controlled phase transformation of commercially available TMDs with conventional 2H phase, yielding a large amount of metastable 1T'-phase TMDs, including WS 2 , WSe 2 , MoS 2 , and MoSe 2 . It is found that the easily accessible metal salts, such as K 2 C 2 O 4 ·H 2 O, K 2 CO 3 , Na 2 CO 3 , Rb 2 CO 3 , Cs 2 CO 3 , KHCO 3 , NaHCO 3 , and NaC 2 O 4 , can be used to assist the 2H-to-1T' phase transformation, greatly simplifying the synthetic process for producing metastable 1T'-TMDs. Importantly, this method can also be used to prepare 1T'-TMD alloys, such as 1T'-WS 2x Se 2(1–x) . We report this newly developed strategy is robust and highly effective, which can also be used for the phase engineering of other materials with various polymorphs.

1T′ phase↗

Microwave‐Assisted Synthesis of SrTiO 3 Nanocuboids without TiCl 4

Strontium titanate (STO) nanocuboids are a novel support for Pt nanoparticle catalysts (Pt/STO). The first of many steps in commercializing Pt/STO will be developing a scalable, environmentally sustainable, and cost‐effective STO nanocuboid synthesis. Herein, Sr–Ti–OH mixtures are synthesized from various Sr 2+ and Ti 4+ reagents and treated by convection‐ and microwave‐assisted heating to obtain STO nanoparticles. These experiments clarify how phase composition of the prehydrothermal Sr–Ti–OH mixture and choice of heating method affect final nanoparticle morphology. In Sr–Ti–OH mixtures synthesized with TiCl 4 , STO is the most stable phase and precipitates prior to heating, while titania sol–gels are the most stable phase when other Ti 4+ sources are used. STO nanocrystals always form when Sr–Ti–OH mixtures are treated by convection heating, though nanocuboids are only observed if STO precipitates from the Sr–Ti–OH mixture. Microwave‐assisted hydrothermal treatment more rapidly heats the precursor solution, and thus, STO nanocuboids can form from a variety of Sr–Ti–OH mixtures regardless of mixture composition. Two microwave syntheses of STO nanocuboids are reported: one which uses TiCl 4 as a Ti 4+ source, and another that uses titanium(IV) bis(ammonium lactato) dihydroxide ([NH 4 CH 3 CH(O)CO 2 ] 2 Ti(OH) 2 ), a water‐stable Ti 4+ complex.

Peczak, Ian L.↗

Quantum-assisted associative adversarial network: applying quantum annealing in deep learning

Abstract Generative models have the capacity to model and generate new examples from a dataset and have an increasingly diverse set of applications driven by commercial and academic interest. In this work, we present an algorithm for learning a latent variable generative model via generative adversarial learning where the canonical uniform noise input is replaced by samples from a graphical model. This graphical model is learned by a Boltzmann machine which learns low-dimensional feature representation of data extracted by the discriminator. A quantum processor can be used to sample from the model to train the Boltzmann machine. This novel hybrid quantum-classical algorithm joins a growing family of algorithms that use a quantum processor sampling subroutine in deep learning, and provides a scalable framework to test the advantages of quantum-assisted learning. For the latent space model, fully connected, symmetric bipartite and Chimera graph topologies are compared on a reduced stochastically binarized MNIST dataset, for both classical and quantum sampling methods. The quantum-assisted associative adversarial network successfully learns a generative model of the MNIST dataset for all topologies. Evaluated using the Fréchet inception distance and inception score, the quantum and classical versions of the algorithm are found to have equivalent performance for learning an implicit generative model of the MNIST dataset. Classical sampling is used to demonstrate the algorithm on the LSUN bedrooms dataset, indicating scalability to larger and color datasets. Though the quantum processor used here is a quantum annealer, the algorithm is general enough such that any quantum processor, such as gate model quantum computers, may be substituted as a sampler.

Wilson, Max (ORCID:0000000207983391)↗

Formation of misfit dislocation arrays and helium nanochannels near copper surface assisted by high-temperature graphene deposition

Misfit dislocation arrays (MDAs) at semi-coherent heterogeneous interface have been demonstrated effectiveness to trap and then outgas helium (He) for alleviating void swelling in metals, but limited by atomic-level thin film deposition that is difficult to scale-up for industrial production. In this work, we proposed an innovative strategy that could generate semi-coherent homophase interfaces in a same grain by varying surface energy density assisted by high-temperature graphene (Gr) deposition. This strategy transforms strain energy and surface energy, two originally distinctive processes into successive processes, and demonstrates experimentally and theoretically by introducing {111} copper (Cu) in a {100} Cu grain. Subsequent He implantation and electrical resistivity measurement results suggest that high-density MDAs originated at this {111}/{100} interface could form stable He nanochannels near Cu surface with Gr assistance, manifesting by ultra-low increased ratio of the electrical resistivity (i.e. ~3800% of Cu vs. ~90% of Gr/Cu) after He implantation. Finally, the present findings may provide a new strategy for efficiently managing He and achieving surface protection of advanced metals, merely by depositing a super-rigid material on metal surface to greatly reduce surface energy density.

36 MATERIALS SCIENCE↗

CO 2 -assisted ethane aromatization over zinc and phosphorous modified ZSM-5 catalysts

The tandem reactions of CO 2 -assisted oxidative dehydrogenation and aromatization (CO 2 -ODA) of ethane were investigated over ZSM-5 modified with zinc (Zn) and phosphorus (P) by experimental studies and DFT calculations. The nature of active Zn species and their interaction with P were elucidated for understanding Zn/P-ZSM-5 catalyzed CO 2 -ODA reaction of ethane. Compared to the direct dehydrogenation and aromatization (DDA) reaction, the Zn/P-ZSM-5 catalyst possessed higher ethane conversion, enhanced aromatics yield, and better stability in the CO 2 -ODA reaction. Here, the presence of CO 2 reduced the carbon deposition, stabilized the Zn species, and thereby facilitated the generation of more liquid aromatics in CO 2 -assisted ethane aromatization. In situ characterization and DFT calculations provided insight into the mechanisms of CO 2 -ODA over the Zn/P-ZSM-5 catalyst.

36 MATERIALS SCIENCE↗

Microwave-assisted conversion of methane over H-(Fe)-ZSM-5: Evidence for formation of hot metal sites

We report microwave-assisted catalysis offers great promise as an “intensified” technology for chemical processing. The present study investigates microwave-assisted direct conversion of methane with focus on the design and evaluation of microwave-sensitive H-(Fe)ZSM-5 catalysts for the existence of hotspot formation. Isomorphous substituted H-(Fe)ZSM-5 catalysts are tuned to identify key design parameters that control their microwave sensitivity. Increasing the amount of Al and Fe substitution in the zeolite lattice is found to result in higher microwave sensitivity due to improved dielectric properties and hence facilitated microwave heating of the catalyst bed. Comparison between the performance of these catalysts in a conventional thermally-heated (CH) fixed-bed and a microwave (MW) reactor allows identification of the effect of microwave irradiation on the catalyst activity. Methane conversion is drastically enhanced at MW conditions (from 3% at CH conditions to 40% at MW conditions), indicating accelerated methane activation over the metal site and hence suggesting a hot metal site despite much lower catalyst bulk temperature measured in the microwave reactor. The existence of metal hotspot formation is further supported by the reaction product distribution and spent catalyst analysis. At MW conditions, C 2 (ethane and ethylene) and coke (mainly carbon nanotubes and nanofibers) selectivity are much higher at the cost of aromatics make compared to CH conditions. This can be explained by reduced aromatization activity at the Brønsted acid sites of the zeolite due to its lower relative temperature of the zeolite. The much-enhanced metal aggregation observed in the spent catalyst from the MW reactor along with the distribution of coke species further confirms the existence of selective heating (i.e. hotspot formation) occurring at the active metal site in the catalyst at MW conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemically-assisted removal of cadmium ions by redox active Cu-based metal-organic framework

An electrochemically-assisted wastewater treatment using Faradaic materials offers a promising technique for the selective removal of hazardous substances. Here, we demonstrate the reversible capture and release of cadmium ions in aqueous solutions, using a redox-active metal-organic framework (MOF) electrode. As-synthesized copper-based MOF (Cu-MOF-74; copper 2,5-dihydroxyterephthalate) is a highly attractive candidate for Faradaic electrosorption due to its large surface area, water stability, and redox-active metal nodes. Our work demonstrates the reversible capture and release of Cd 2+ ions assisted by the electrochemical redox reaction of Cu 2+ /Cu + within the MOF structure. Combined material characterization and electrosorption tests were carried out to determine the operational conditions for maximizing adsorption capacity, energy efficiency, and material stability, thus leading to excellent electrosorption (>100 mg g -1 ) and regeneration efficiency (>90%). This study demonstrates the feasibility of leveraging MOFs containing redox-active metal nodes for the selective separation of toxic cations, and paves the way for promising future applications of these 3-D porous structures for wastewater treatment and environmental remediation.

42 ENGINEERING↗

Effects of support and promoter on Ru catalyst activity in microwave-assisted ammonia synthesis

Microwave-assisted ammonia synthesis is a promising alternative to the energy-intensive Haber-Bosch process, specially at small- and medium-scale with renewable H 2 as resource. Here, we report that Cs promoted Ru/CeO 2 catalyst exhibits considerable activity at 533 K and ambient pressure. In this work, the combined theoretical and experimental approaches are adopted to optimize the electronic and geometric structures of Ru on the catalysts. Both DFT modeling work and structural characterization show that the strong interaction between Ru and CeO 2 results in the formation of highly dispersed Ru particles favoring ammonia synthesis. The higher electron donating ability of CeO 2 and lower electronegativity of Cs promoter result in higher electron density on Ru reducing the N≡N dissociation barrier. Finally, the work demonstrates the potential of microwave-assisted catalytic process in activating stable molecules for ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microwave-assisted synthesis of mixed-linker covalent organic frameworks enabling tunable and ultrahigh iodine capture

The use of covalent organic frameworks (COFs) for hazardous radioiodine capture has been highly sought after recently. However, the synthesis of high-performance COF adsorbents while circumventing the limitations of traditional solvothermal methods remains largely unexplored. Herein, we for the first time combine microwave-assisted synthesis and mixed-linker strategy to fabricate multivariate COF adsorbents (X% OMe-TFB-BD COFs, X% = 0, 33, 50, 67, and 100 mol%) with varying ratios of benzidine (BD) and 3,3'-dimethoxylbenzidine (BD-OMe) linkers in a rapid and facile manner. Adjusting the BD-OMe/BD mole ratios has led to distinct variations in density, crystallinity, porosity, morphology, and thermal/chemical stability of the resultant COFs, which empowered fine-tuning of the adsorption performance towards static iodine vapor. Remarkably, the 50% OMe-TFB-BD COF exhibited an ultrahigh iodine adsorption capability of 8.2 g g –1 , surpassing those of single-component COFs, mixed-linker COFs with other methoxy content, physically blended mixtures, and most existing COF adsorbents. Moreover, 50% OMe-TFB-BD COF was recyclable seven times without obvious loss in its adsorption capacity. Finally, this work underscores the substantial potential of microwave-assisted mixed-linker strategy as a viable approach for developing multivariate COFs with shortened reaction times, precisely tailored pore environment, and tunable sorption properties, which are of considerable promise for environmental remediation and other niche applications.

36 MATERIALS SCIENCE↗

Mechanochemical synthesis of hydraulically reactive calcium silicate minerals via thermally-assisted mechanical grinding

This study explores a thermally assisted mechanochemical approach alternative to conventional cement synthesis as a potential to produce hydraulically reactive calcium silicate phases. Ball milling of mixed CaO/SiO 2 feedstocks at temperature ranges 100-300 °C increases the formation of the Ca-O-Si bonds and precursor reactivity. Spectroscopic analyses (FTIR, MAS-NMR, UV-Vis DRS) indicate increasing amorphization with milling temperature, attributed to improved mixing and thermally assisted diffusion. Upon hydration, all treated samples exhibit exothermic heat release, with the sample prepared at 300 °C showing the most pronounced reactivity. Thermal analysis reveals weight loss consistent with C-S-H formation, confirming cement-like behavior. In summary, moderate thermal input during milling promotes structural activation and enhances downstream hydraulic reactivity, providing a proof-of-concept for energy-reduced cement precursor processing.

Alite↗

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗