High-Performance Flexible Bismuth Telluride Thin Film from Solution Processed Colloidal Nanoplates
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Despite its significant advantages as a baseload, low-carbon energy source, the U.S. nuclear power industry has faced increasing difficulties in maintaining economic competitiveness in a rapidly evolving energy market. The economic conditions faced by the current fleet of nuclear power plants (NPPs) in the U.S. deregulated electricity market require a concerted effort to mitigate specific cost factors. Many units are struggling to stay competitive, and some premature shutdowns have occurred. Besides, in response to the large penetration of renewable energy sources, the role of nuclear power plants as pure baseload units needs to be reconsidered. Based on these experiences, operational flexibility is considered a fundamental requirement for the next generation of nuclear reactors to be competitive in the future energy market. The deployment of advanced reactors capable of operating within a new power grid paradigm, known as the Integrated Energy System (IES) was investigated. This approach combines new reactor designs with Thermal Energy Storage (TES) technologies, allowing the nuclear reactor to maintain a steady power output without the need for constant adjustments in response to load demand fluctuations. With this configuration, the reactor operates as a baseload unit, experiencing only very gradual power transients, while the energy storage facility within the power conversion cycle acts as a peaking unit.
Nature offers inspiration for developing technologies that integrate the capture, conversion, and storage of solar energy. In this review article, we highlight principles of natural photosynthesis and artificial photosynthesis, drawing comparisons between solar energy transduction in biology and emerging solar-to-fuel technologies. Key features of the biological approach include use of earth-abundant elements and molecular interfaces for driving photoinduced charge separation reactions that power chemical transformations at global scales. Finally, for the artificial systems described in this review, emphasis is placed on advancements involving hybrid photocathodes that power fuel-forming reactions using molecular catalysts interfaced with visible-light-absorbing semiconductors.
This study evaluates and optimizes advanced nuclear reactors coupled with thermal energy storage (TES) systems in an Integrated Energy System (IES) architecture to enable advanced nuclear power plants (A NPP) to participate in multi-commodity markets, thus enhancing their economic competitiveness. Nuclear-TES coupling scenarios studied herein are designed attenuate the nuclear heat dynamics and defer energy delivery to a later time, enabling the nuclear reactor to continue operating at or near steady-state design conditions as usual while also enabling flexible generation. Three A-NPPs, namely, an advanced light-water reactor (A LWR), a high temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating the technoeconomic of thermally balanced energy storage coupling design for thermal power extraction. Each of the reactor technologies were evaluated in two different electricity markets. Stochastic optimization approach was adopted which included the evaluation of price signals from the Pennsylvania-New Jersey-Maryland (PJM) market, and Electric Reliability Council of Texas (ERCOT), using an autoregressive moving average (ARMA) model. Risk Analysis Virtual Environment (RAVEN) tool and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON), were used to perform dispatch and capacity optimization, using the price data provided by the ARMA models. The results from the Nuclear-TES use cases will be used to design and characterize dynamic integrated system behavior and feedback.
The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure and electricity. Growth in electricity demand from EV charging, coupled with growth in other sectors like data centers and electrification of other sectors, is impacting electricity infrastructure and load service request processes after two decades of relatively flat electricity demand. While most electric vehicle charging occurs at home, enroute and depot charging for medium and heavy-duty vehicles, both using high-powered EV charging, are critical to meet electric vehicle operational needs. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have expressed distress that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions.
Thermoelectric materials, which can convert waste heat into electricity or act as solid‐state Peltier coolers, are emerging as key technologies to address global energy shortages and environmental sustainability. However, discovering materials with high thermoelectric conversion efficiency is a complex and slow process. The emerging field of high‐throughput material discovery demonstrates its potential to accelerate the development of new thermoelectric materials combining high efficiency and low cost. The synergistic integration of high‐throughput material processing and characterization techniques with machine learning algorithms can form an efficient closed‐loop process to generate and analyze broad datasets to discover new thermoelectric materials with unprecedented performances. Meanwhile, the recent development of advanced manufacturing methods provides exciting opportunities to realize scalable, low‐cost, and energy‐efficient fabrication of thermoelectric devices. This review provides an overview of recent advances in discovering thermoelectric materials using high‐throughput methods, including processing, characterization, and screening. Advanced manufacturing methods of thermoelectric devices are also introduced to realize the broad impacts of thermoelectric materials in power generation and solid‐state cooling. In the end, this article also discusses the future research prospects and directions.
The objective of this project was to develop a novel catalytic reactor containing nano-engineered catalysts for the utilization of CO 2 (captured from coal-fired power plants and other CO 2 emitting sources) in dry methane reforming (DMR) (CO 2 + CH 4 → 2 H 2 + 2 CO) to produce synthesis gas (syngas). The technology aims to reduce CO2 emissions by developing beneficial uses for CO 2 from coal-fired power plants. It also offers an alternative to mitigate CO 2 emissions in areas where geologic storage may not be an optimal solution and/or utilization could significantly offset the costs of carbon capture and sequestration. The nano-engineered Ni-based catalyst was prepared by atomic layer deposition (ALD). The Ni particles were as small as ~2-4 nm. The nano-engineered catalyst showed CH 4 conversion >95%, H 2 /CO ratio in the range of 0.7-1.0, and CH 4 reforming rate as high as 2,500 L/h/gNi at 850 ºC and pressure of 15-25 psia. The Ni-based ALD catalyst also showed good stability in DMR reaction during a 200-h continuous operation at 850 °C. This is due to strong bonding between the nanoparticles and substrates since the Ni nanoparticles were chemically bonded to the substrate during the ALD process. The high thermal stability maintains the high dispersion of Ni nanoparticles, which can inhibit coke formation because their step edges are small enough to limit carbon nucleation and growth. Technoeconomic analysis (TEA) indicates the levelized cost of syngas (LCOS) is $172/ton with our technology, which is lower than the equivalent (molar) cost of hydrogen produced by steam methane reforming (SMR) or autothermal reforming (ATR). The major operating cost is natural gas feed and fuel, and the levelized cost is highly sensitive to the price of natural gas and relatively insensitive to the CAPEX. Revenues from syngas could have a significant impact on the net cost of electricity (COE), depending on the cost of natural gas and the selling price of syngas, estimated at $36 per MWh if the syngas were sold at $195 per ton. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare with SMR. The functional unit for the basis of comparison was defined as 1kg carbon monoxide in the product stream. The global warming potential (GWP) of our process was found to be 40% lower than the state-of-the-art SMR process. The sensitivity analysis confirms the emissions are most sensitive to the natural gas fuel requirements to deliver heat to the process.
Light-emitting diodes (LEDs) have enabled a historic increase in the conversion of electric energy to photons, but this is approaching a physical limit. The theoretical maximum efficiency occurs when all input energy is converted to energy in photosynthetic photons. Blue LEDs can be 93% efficient, phosphor-converted “whites” 76% efficient, and red LEDs 81% efficient. These improvements open new opportunities for horticultural lighting. Here we review (1) fundamental physics and efficiency of LEDs, (2) the current efficacy of LEDs, (3) the effect of spectral quality on crop yield, and (4) the potential efficacy of horticultural fixtures. Advances in the conversion of photons to yield can be achieved by optimization of spectral effects on plant morphology, which vary among species. Conversely, spectral effects on photosynthesis are remarkably similar across species, but the conventional definition of photosynthetic photons (400–700 nm) may need to be modified. The upper limit of LED fixture efficacy is determined by the LED package efficacy multiplied by four factors inherent to all fixtures: current droop, thermal droop, driver (power supply) inefficiencies, and optical losses. With current LED technology, the calculations indicate efficacy limits of 3.4 µmol J- 1 for white + red fixtures, and 4.1 µmol J -1 for blue + red fixtures. Adding optical protection from water and high humidity reduces these values by ~10%. We describe tradeoffs between peak efficacy and cost.
A cathode-side contact layer is required to provide and maintain stable electrical conduction paths between the interconnect and cathode in a solid oxide fuel cell (SOFC) stack assembly and thus minimize the ohmic resistance and stack power loss. Current cathode-interconnect contact materials are based on noble metals, electrically-conductive perovskites, their composite materials, etc. These materials are either too expensive or do not possess the overall balanced performance required for the cathode-side contact application. To achieve the DOE SOFC system cost and performance stability goals, a new generation of low-cost, high-performance contact materials needs to be developed. In this project, spinel-based materials thermally converted from the Fe-Ni and Co-Mn based alloy precursors were developed and validated for the cathode-side contact application. The precursor alloy compositions were optimized via a combination of composition screening in the (Ni,Fe) 3 O 4 and (Mn,Co) 3 O 4 spinel system, alloy design using physical metallurgy principles, and cost considerations. The alloy powders with the desired composition and particle size were manufactured via gas atomization. The optimal process parameters for thermal conversion of these alloy precursor layers to a spinel-based layer were identified, i.e., 900°C x 2h in air, which is close to the initial stack firing condition. The area-specific resistances (ASRs) of the interconnect/contact/cathode test assemblies with the developed contact layer were determined for various durations (up to 5000 h) under simulated cathodic operation conditions. Some of the alloy-derived spinel contacts exhibited the lowest ASR and ASR degradation rate. The in-stack performance of the most promising alloy-derived contact layer is currently being evaluated via stack testing. To reduce the stack cost, the Co-Mn based alloy powders were utilized as the precursor for synthesis of dense spinel-based interconnect coating. By optimizing both the initial powder size/distribution and the alloy powder composition, a dense (Mn,Co) 3 O 4 -based spinel coating was achieved. Furthermore, co-sintering of the coating/contact dual-layer structure under the initial stack firing condition was realized by utilizing the tailored Co-Mn alloy precursors. Cost analysis of the developed technology indicated a total stack cost reduction of around 10.6% with the implementation of co-sintering of the interconnect coating and the contact layer during initial stack firing. Since low-cost processes such as screen printing is utilized in the precursor application and no reduction heat treatment is needed for the coating formation, the developed technology can be readily implemented at the industrial partner’s manufacturing facilities with no additional capital investment needed.
This project is intended to support the development of new traction drive systems that meet the targets of 100 kW/L for power electronics and 50 kW/L for electric machines with reliable operation to 300,000 miles. To meet these goals, new designs must be identified that make use of state-of-the-art and next-generation electronic materials and design methods. Designs must exploit synergies between components, for example converters designed for high-frequency switching using wide band gap devices and ceramic capacitors. This project includes: (1) a survey of available technologies; (2) the development of design tools that consider the converter volume and performance; (3) exercising the design software to evaluate performance gaps and predict the impact of certain technologies and design approaches, i.e. GaN semiconductors, ceramic capacitors, and select topologies; and (4) building and testing hardware prototypes to validate models and concepts. Early instantiations of the design tools enable co-optimization of the power module and passive elements and provide some design guidance; later instantiations will enable the co-optimization of inverter and machine. Prototype testing begins with evaluation of simpler conversion topologies (i.e. the half-bridge boost converter) and progresses with fabrication of prototype inverter drives.
The project aimed to develop a thermal energy storage battery that converts electricity to heat and stores heat at ultra-high temperatures (>2000°C) in graphite blocks. The thermal battery discharge uses TPV cells that directly convert thermal energy to electrical energy without any moving parts. All components of this technology were successfully demonstrated at the laboratory scale in this project. Development of extremely low cost (< $20/kWh) grid level energy storage is a crucial necessity to reach high penetrations of renewables. The thermal battery technology developed in this project is expected to meet the cost targets that would enable full renewable penetration. The project focused on four key aspects of this technology: Converting electricity to ultra-high temperature heat: This was done through development of graphite Joule heaters. Major issues related to arcing, heater evaporation and deterioration due to long term oxidation were addressed to ensure lifetime exceeding the service lifetime of the battery. Converting ultra-high temperature heat back to electricity: This was done through development of beyond state-of-the-art TPV cells. We demonstrated energy conversion efficiency of >40% that is a world record and exceeds the average energy conversion efficiency of turbines in the USA. The findings are peer-reviewed and published in Nature, and received a wide media attention globally. Protecting the TPV cells to ensure lifetime: Deposition of volatilized material, such as sublimated material or particles, on the TPV cell could greatly reduce the efficiency and lifetime of the TPV cells by blocking their view to the heat source and causing cell overheating. In this project we developed and demonstrated an approach that reduces the deposition rate, ensuring long > 30 year life. Technoeconomic feasibility and commercialization: In collaboration with the project’s technical advisory board, we developed a technoeconomic model. The model shows that, at large scales (> 1GWh) the thermal battery technology is projected to reach a cost of energy stored below $10/kWh-e, with a cost per unit power < $0.5/W-e and a roundtrip efficiency of 50%. These results, along with the technical achievements in the project led to the creation of a startup company (i.e., Fourth Power) that is pursuing commercialization of the technology.
Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H 2 ), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H 2 and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H 2 , and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H 2 and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping.
Electric vehicle (EV) adoption will expand beyond light-duty vehicles charging at lower-power public locations and family residences to include medium- and heavy-duty applications with more powerful charging at public stations and private depots. The Vehicle Grid Integration (VGI) and Smart Charge Management (SCM) pillar in EVs@Scale supports multiple projects. The FUSE project is developing and evaluating enabling technologies, charging solutions, and infrastructure design approaches to investigate the intricacies and potential benefits of vehicle grid integration and the application of smart charge management to charging of electric vehicles at scale. This presentation delves into the technical findings of this research in 2024.
COVID-19 pandemic has affected clean energy labor market. Using real-time job vacancy data, this study analyzes the impacts of the pandemic on the U.S. clean energy labor market in 2020, including biomass, energy efficiency (EE), electric vehicle (EV), power/microgrid, solar, and wind industries. This study identifies how COVID-health factors and public health interventions influence clean energy job availability during the early COVID pandemic. Overall, California had the most energy jobs and experienced a significant decrease in April 2020. EV and solar had the highest percentages of job vacancies during the pandemic in general. Still, lockdowns had the most severe influence on EE and wind jobs. Stay-at-home orders negatively affected clean energy job vacancies in biomass, EV, power/microgrid, and wind. Social-gathering restrictions, however, did not have much influence. Increased COVID tests at the state level had the strongest and most positive influence on clean energy job postings, indicating the importance of a state's ability to manage public health infrastructure or crisis issues. COVID hospitalizations negatively influenced the job vacancies in biomass and wind but did not affect the other four sectors; conversely, as COVID death numbers increased, the number of jobs in biomass, EV, power grid, solar, and wind decreased, but not in EE jobs.
Copper indium disulfide (CuInS2) is a semiconductor with a direct energy band gap of 1.53 eV, an optimal value for highly efficient thin-film solar cells. But it has reached only ~ 11 % power conversion efficiency, far less than the theoretically achievable value of ~ 30 %. The cause of this low performance is not understood. A single crystal grown from 1 mol% Cu-deficient melt was studied, using atomic resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) and electron dispersive spectroscopy (EDS). While the bulk crystal is exactly stoichiometric CuInS2, it contains nanometer-thick, structurally coherent, Cu-deficient interphases that form along rotational twin boundaries in the {112} plane. Transition zones from bulk crystal to interphase are observed, where In is seen to move from its normal site InIn in the chalcopyrite structure to a tetrahedral interstitial site Ini, while Cu remains in its normal CuCu position. Two InIn rows of the bulk crystal merge into one row of Ini, causing excess Ini in the interphase. The concentrations of CuCu and Ini reflect a ratio of Cu vacancies, VCu, to excess Ini of ~ 2. Their relative lattice positions, and the high electrical resistivity of the crystal, suggests that VCu and excess Ini ‘precipitate’ as self-compensating, electrically neutral, [VCu1- Ini2+ VCu1-] defect triplets. This is the first atomic-level observation of the ordered defect that has been invoked as the basic structural modifier in chalcopyrite compound homologs. The interphases introduce an optical gap of 1.47 eV. Electron trapping in band tail states, evident from a photoconductivity exponent of 0.54, is the likely cause of an unusually low electron mobility of 0.1 cm2V-1s-1. The overall result is that making CuInS2 slightly copper-poor inserts nanometer-thick layers of the interphase into the bulk crystal. This study shows that apparently conflicting results of the effect of Cu deficiency on CuInS2 thin-film solar cells may be resolved by analyzing structure and composition at nanometer spatial resolution.
The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021
The Mu2e experiment at Fermilab will measure the rate for neutrinoless-conversion of negative muons into electrons with never-before-seen precision. This experiment will use a pulsed 8 GeV proton beam with pulses separated by 1.7 µs. To suppress beam induced backgrounds to this process, a set of dipoles operating at 300 kHz and 4.4 MHz have been developed that will reduce the fraction of out-of-time protons at the level of 1E-10 or less. Selection of magnetic ferrite material for construction must be carefully considered given the high repetition rate and duty cycle that can lead to excess heating in conventional magnetic material. A model of the electromagnetic and thermal properties of candidate ferrite materials has been constructed. Magnetic permeability, inductance, and power loss were measured at the two operating frequencies in toroidal ferrite samples as well as in the ferrites from which prototype magnets were built. Additionally, the outgassing rates of the ferrite material was measured to determine vacuum compatibility. The outcome of this work is a detailed specification of the electrical and mechanical details of the ferrite material required for this application.
Thermoelectric materials, capable of converting temperature gradients into electrical power, have been traditionally limited by a trade‐off between thermopower and electrical conductivity. This study introduces a novel, broadly applicable approach that enhances both the spin‐driven thermopower and the thermoelectric figure‐of‐merit (zT) without compromising electrical conductivity, using temperature‐driven spin crossover. Our approach, supported by both theoretical and experimental evidence, is demonstrated through a case study of chromium doped‐manganese telluride, but is not confined to this material and can be extended to other magnetic materials. By introducing dopants to create a high crystal field and exploiting the entropy changes associated with temperature‐driven spin crossover, we achieved a significant increase in thermopower, by approximately 136 μV K −1 , representing more than a 200% enhancement at elevated temperatures within the paramagnetic domain. Our exploration of the bipolar semiconducting nature of these materials reveals that suppressing bipolar magnon/paramagnon‐drag thermopower is key to understanding and utilizing spin crossover‐driven thermopower. These findings, validated by inelastic neutron scattering, X‐ray photoemission spectroscopy, thermal transport, and energy conversion measurements, shed light on crucial material design parameters. We provide a comprehensive framework that analyzes the interplay between spin entropy, hopping transport, and magnon/paramagnon lifetimes, paving the way for the development of high‐performance spin‐driven thermoelectric materials.