SEARCH · Search NASA

Results for “reduced cost”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Accelerating Nuclear Facility Mission Completion Through an Improved Chemical Hazard Control Strategy - 20460

Code of Federal Regulation (CFR) 10 CFR 830, Nuclear Safety Management [1], explicitly identifies hazardous materials in addition to radioactive materials when establishing the scope of materials that must be evaluated in Hazard Category (HC) 1, 2, and 3 nuclear facilities. This inclusion has led to a near decade-long progression of more and more rigorous application of chemical hazard controls in these facilities. The progressive addition of more rigorous chemical hazard controls has occurred across the Department of Energy (DOE) Complex, having been driven by contractors and regulators alike. However, chemical hazards in other DOE facilities have been, and continue to be, controlled using traditional industrial safety centered strategies. Thus, identical chemical hazards are controlled using dramatically different approaches based solely on the facility type. Not only are the controls different, the analysis and derivation rigor and requirements are also significantly different. In particular, chemical control derivation and application in non-nuclear facilities are much less onerous than the comprehensive hazard analysis process used in nuclear facilities, even in circumstances in which chemicals are not initiators to, or do not exacerbate a nuclear event. While the derivation and control approaches used in these two types of facilities are disparate, the safety results are similarly effective based on a review of reported chemical events from 2014 through 2018. While both approaches achieve comparable safety outcomes, the approach used in nuclear facilities results in significantly greater preparation costs and implementation costs. Furthermore, the problem with the differing approach is not relegated to the control preparation and implementation burden. The operational impact of potentially unnecessary controls slows mission completion without a corresponding increase in safety, not to mention the dilution of the importance of Technical Safety Requirements. The proposed solution must first include a critical and thorough examination of DOE Complex and top-tier chemical industry chemical hazard control practices, coupled with a similar examination of the driving facility regulatory requirements. Results from the examination can then be used to fuel a bold departure from current chemical control practices in Hazard Category 1, 2, and 3 nuclear facilities. Development of an improved and consistent chemical hazard control process would follow, one that continues to ensure safety while accelerating mission completion and significantly reducing the burden associated with chemical hazard control development and implementation. The improved process must establish a hierarchy where radiological hazards are addressed using safety class and safety significant controls and chemical hazards are addressed using overarching safety management programs (with limited unique exceptions). The improved Hazard Category 1,2, and 3 nuclear facility chemical hazard control strategy, while compliant with 10 CFR 830 [1], would be founded on the requirements in 10 CFR 851, Worker Safety and Health Program [2], and the complementary DOE O 151.1D, Comprehensive Emergency Management System [3]. In this way, the Hazard Category 1, 2, and 3 nuclear facility chemical hazard control strategy would, wherever appropriate, be the same process used at other DOE Complex facilities. Ultimately, the improved process will maintain safety and significantly reduce costs and life cycle risk through faster mission completion. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Structural and Valence State Modification of Cobalt in CoPt Nanocatalysts in Redox Conditions

Platinum is the primary catalyst for many chemical reactions in the field of heterogeneous catalysis. However, platinum is both expensive and rare. Therefore, it is advantageous to combine Pt with another metal to reduce cost while also enhancing stability. To that end, Pt is often combined with Co to form Co-Pt nanocrystals. However, dynamical restructuring effects that occur during reaction in Co-Pt ensembles can impact catalytic properties. In this study, model Co 2 Pt 3 nanoparticles supported on carbon were characterized during a redox cycle with two in situ approaches, namely X-ray absorption spectroscopy (XAS) and scanning transmission electron microscopy (STEM) using a multimodal microreactor. The sample was exposed to temperatures up to 500 °C under H 2 , and then to O 2 at 300 °C. Irreversible segregation of Co in the Co-Pt particles was seen during redox cycling and substantial changes of the oxidation state of Co were observed. After the H 2 treatment, a fraction of Co could not be fully reduced and incorporated into a mixed Co-Pt phase. Re-oxidation of the sample increased Co segregation, and the segregated material had a different valence state than in the fresh, oxidized sample. Furthermore, this in situ study describes dynamical restructuring effects in CoPt nano-catalysts at the atomic scale that are crucial to understand to improve the design of catalysts used in major chemical processes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

The Building Adapter: Automatic Mapping of Commercial Buildings for Scalable Building Analytics

This project creates new solutions for the manual metadata mapping problem: the costly process of creating a match between a building’s sensor data streams and the inputs of a building analytics engine. This goal is achieved by creating and improving techniques for metadata inference: automatically constructing new contextual information for sensing and control points based on the sensor point names and the raw time series values. The objective is to enable vendors to apply building analytics to 90% of buildings with no manual mapping, and to 10% of buildings with a 90% reduction in manual mapping. These targets are set for all types of metadata required by current analytics engines, including type, location, equipment type, and other relationships. The outcome of this project is a suite of solutions to the manual mapping problem collectively called the Building Adapter that allows vendors to apply analytics engines to new buildings at a significantly reduced cost.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

Toward achieving cost-effective hexagonal BN semi-bulk crystals and BN neutron detectors via halide vapor phase epitaxy

Presently, thermal neutron detectors fabricated from boron-10 enriched hexagonal boron nitride (h-10BN) ultrawide bandgap semiconductor grown by metal organic chemical vapor deposition (MOCVD) hold the record high detection efficiency among all solid-state detectors at 59%. To overcome the short comings of MOCVD growth, including inherently low growth rate and unavoidable impurities such as carbon in metal organic source, we demonstrate here the growth of natural hexagonal boron nitride (h-BN) semi-bulk wafers using halide vapor phase epitaxy (HVPE), which is an established technique for producing GaN semi-bulk crystals at a high growth rate. Electrical transport characterization results revealed that these HVPE grown materials possess an electrical resistivity of 1 × 1013 Ω cm, and a charge carrier mobility and lifetime product of 2 × 10−4 cm2/V s. Detectors fabricated from a 100 μm thick h-BN wafer have demonstrated a thermal neutron detection efficiency of 20%, corresponding to a charge collection efficiency of ∼60% at an operating voltage of 500 V. This initial demonstration opens the door for mass producing high efficiency h-BN semiconductor neutron detectors at a reduced cost, which could create unprecedented applications in nuclear energy, national security, nuclear waste monitoring and management, the health care industry, and material sciences.

Physics↗

DOE OSTI2021

Human-in-the-loop Sensing and Control for Commercial Building Energy Efficiency and Occupant Comfort

Most of the existing heating, ventilation and air conditioning (HVAC) systems in commercial buildings operate in a conservative manner by assuming maximum occupancy in each room during pre-specified periods of the week, leading to significant energy being wasted as rooms are over-conditioned compared to the actual requirements of the occupants. Though critical, our understanding of occupancy patterns and thermal comfort needs of the occupants in commercial buildings is lacking and it is well known that both of these quantities are stochastic and time-varying, thus requiring sensing solutions to estimate them. This project had the goal of designing, implementing and evaluating a hardware and software solution to ameliorate this challenge. In particular, a depth camera (one whose pixels reveal distance from the camera as opposed to color values) placed on doorways is used to detect entrance and exit events from thermal zones in the building, and thereby estimate their occupancy levels. This information is then fed to a novel control algorithm that can, through interactions with the HVAC system, learn how to provide control inputs that maximize comfort and minimize energy waste. The resulting system represents a significant improvement over existing controllers for commercial HVAC systems and allowed us to improve our understanding of the design of future human-in-the-loop control solutions. For this solution to be feasible, the project had target metrics for its performance and cost. In particular, entrance and exit events for occupants moving about the building would need to be detected with an accuracy higher than 97%; and the resulting control inputs derived from this information would need to lead to approximately 10% energy savings compared to a schedule-based controller. Furthermore, regarding the final hardware design, the project had a target bill of materials (BOM) cost for the sensing solution of less than US$200 per unit while using less than 25W of power on average. All of these target metrics were met or exceeded by our final proposed solution. We performed evaluations by deploying the system in over 20 rooms of different types across 6 commercial buildings in Pittsburgh, PA over the course of three years, and performing targeted controlled experiments to test its performance along the different metrics. The human-in-the-loop control solutions (both hardware and software) developed through this project are expected to lead to significant improvements in the comfort and energy efficiency of HVAC systems used in commercial buildings. The insights we developed through the project pave the way to HVAC systems that can condition interior spaces according to their real-time utilization and the thermal comfort needs of the occupants, thereby reducing energy use. They also open up a new learning-based way of configuring HVAC controllers without having to manually fine-tune them for each building. These innovations can significantly increase the adoption of novel control solutions by the industry and thereby save resources and reduce costs of operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗

DOE OSTI2023

Unlocking the Value of Deep Energy Retrofits

This publication is based on an extensive study conducted on behalf of the New York State Energy Research and Development Authority (NYSERDA) and the U S Department of Energy (DOE) to explore financial and risk products to accelerate the implementation of deep energy retrofit (DER) solutions to reduce costs These financial products are intended to speed market development via three fundamental themes: reallocating risk from building owners and lenders to insurers, quantifying and monetizing previously unrecognized value associated with DERs, and providing building owners and lenders with confidence in the performance of building systems Findings are based on a comprehensive analysis and characterization of 100+ existing DER case studies, and more than 40 qualitative interviews with industry experts, including insurers, researchers, building owners, and policymakers In addition, a quantitative model of overall project economics with baseline, high, and low cases was developed This data informed the analysis that resulted in three recommended financial product solutions, which were evaluated for their potential to raise projected cash flows and finance DERs: 1) Building System Performance and Energy Savings Guarantee; 2) Trade Credit Insurance; 3) Ancillary Revenue Contracts. This report identifies many value streams associated with DERs and introduces these three potential financial products, which aim to reallocate risks and reduce barriers to the adoption of advanced envelope DERs.

ancillary renenue contracts↗

DOE OSTI2024

Aqueous Processed All-Polymer Solar Cells with High Open-Circuit Voltage Based on Low-Cost Thiophene–Quinoxaline Polymers

Eco-friendly solution processing and the low-cost synthesis of photoactive materials are important requirements for the commercialization of organic solar cells (OSCs). Although varieties of aqueous-soluble acceptors have been developed, the availability of aqueous-processable polymer donors remains quite limited. In particular, the generally shallow highest occupied molecular orbital (HOMO) energy levels of existing polymer donors limit further increases in the power conversion efficiency (PCE). Here, we design and synthesize two water/alcohol-processable polymer donors, poly[(thiophene-2,5-diyl)-alt-(2-((13-(2,5,8,11-tetraoxadodecyl)-2,5,8,11-tetraoxatetradecan-14-yl)oxy)-6,7-difluoroquinoxaline-5,8-diyl)] (P(Qx8O-T)) and poly[(selenophene-2,5-diyl)-alt-(2-((13-(2,5,8,11-tetraoxadodecyl)-2,5,8,11-tetraoxatetradecan-14-yl)oxy)-6,7-difluoroquinoxaline-5,8-diyl)] (P(Qx8O-Se)) with oligo(ethylene glycol) (OEG) side chains, having deep HOMO energy levels (~–5.4 eV). The synthesis of the polymers is achieved in a few synthetic and purification steps at reduced cost. The theoretical calculations uncover that the dielectric environmental variations are responsible for the observed band gap lowering in OEG-based polymers compared to their alkylated counterparts. Notably, the aqueous-processed all-polymer solar cells (aq-APSCs) based on P(Qx8O-T) and poly[(N,N'-bis(3-(2-(2-(2-methoxyethoxy)-ethoxy)ethoxy)-2-((2-(2-(2-methoxyethoxy)ethoxy)ethoxy)-methyl)propyl)naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl)-alt-(2,5-thiophene)] (P(NDIDEG-T)) active layer exhibit a PCE of 2.27% and high open-circuit voltage (V OC ) approaching 0.8 V, which are among the highest values for aq-APSCs reported to date. This study provides important clues for the design of low-cost, aqueous-processable polymer donors and the fabrication of aqueous-processable OSCs with high V OC .

14 SOLAR ENERGY↗

DOE OSTI2021

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

DOE OSTI2020

Enabling high areal capacity for Co-free high voltage spinel materials in next-generation Li-ion batteries

The rapidly growing technological demand for lithium-ion batteries has prompted the development of novel cathode materials with high energy density, low cost, and improved safety. High voltage spinel, LiNi 0.5 Mn 1.5 O 4 (LNMO), is one of the most promising candidates yet to be commercialized. The two primary obstacles for this material are the inferior electronic conductivity and fast capacity degradation in full cells due to the high operating voltage. By systematically addressing these limitations, we successfully develop a thick LNMO electrode with areal capacity loadings up to 3 mAh·cm –2 . The optimized thick electrode is paired with a commercial graphite anode at both the coin cell and pouch cell level, achieving a full cell capacity retention as high as 72% and 78%, respectively, after 300 cycles. We attribute this superior cycling stability to careful optimizations of cell components and testing conditions, with a specific focus improving electronic conductivity and high voltage compatibility. These results suggest precise control of materials quality, electrode architecture and electrolyte optimization can soon support the development of a cobalt-free battery system based on a thick LNMO cathode (>4 mAh·cm 2 ), which will eventually meet the needs of next-generation Li-ion batteries with reduced cost, improved safety, and assured sustainability.

25 ENERGY STORAGE↗

DOE OSTI2025

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗

DOE OSTI2021

Technoeconomic Design of a Geothermal-Enabled Cold Climate Zero Energy Community

Development of a zero energy community is more costly in northern cold climates than in moderate regions. Building energy loads are higher, thanks to the colder weather, and site solar photovoltaics (PV) are less productive due to lower solar incidence and misalignment with the buildings’ energy needs (summer production, winter demands). Geothermal energy production can support a zero energy community through application of energy efficiency (demand design), geothermal production (supply design), and asset dispatch as an integrated techno-economic package. This article presents the process used to explore geothermal system integration, our findings, and technical challenges for community-scale adoption of geothermal as an electric and thermal resource. We show that under a wide range of conditions, community-scale geothermal electric power and direct-use thermal energy is economically competitive with “business-as-usual” design and construction practices for zero energy communities. Furthermore, geothermal-produced energy will be self-consumed to a much greater extent than PV, resulting in significant reductions in site energy import and export. We conclude that under appropriate conditions, community-scale geothermal can be the most economically favorable energy resource for northern-climate zero energy community developments. Ongoing geothermal research and development to improve performance and reduce costs will further enhance the value proposition for community-scale geothermal technologies. We expect that including geothermal power and thermal energy in zero energy community design can improve its cost-effectiveness and therefore enhance the benefits of zero energy in more northern climates.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Interactive Mesh Generation and Comparison Tools for Nuclear Energy Advanced Modeling & Simulation Phase I. Final Report

The promise of computer simulations for nuclear reactor designs is the opportunity to speed up the design process while also improving safety, providing more detail and higher fidelity, reducing cost, minimizing schedule risk, and avoiding many other potential problems; because simulations have the potential to be much less expensive and time-consuming than traditional development – where scale models and physical tests require construction and long lead times – it is possible to consider more alternatives and complete more comprehensive assessments before the design is finalized and constructed. As more design scenarios are studied by simulation, the speed that simulations promise is only available as long as bottlenecks are addressed for these scenarios. A frequent bottleneck is the amount of human labor required to describe the shape of the objects being designed and decompose the shape into simple elements, such as hexahedra, that are small enough to capture the physical phenomena of interest without being so small that even fast computers cannot perform the simulation in a reasonable amount of time. Recently, techniques for creating all-hexahedral decompositions have been developed, but they require some human input. Many simulation codes prefer all-hexahedral decompositions, so we proposed to evaluate the feasibility of these techniques on nuclear reactor geometries to see whether they required too much human input to be commercially viable. Our study concluded that they can be made viable with some additional software tools to reduce the amount of user input required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

H 2 O-assisted O 2 reduction by H 2 on Pt and PtAu bimetallic nanoparticles: Influences of composition and reactant coverages on kinetic regimes, rates, and selectivities

Hydrogen peroxide (H 2 O 2 ) can replace hazardous oxidants in industrial processes but is currently too expensive for many such applications. While direct synthesis of H 2 O 2 (H 2 + O 2 → H 2 O 2 ) may reduce costs in comparison to incumbent technology, current catalysts lack the requisite stability and selectivity. Here, we examine the direct synthesis of H 2 O 2 on bimetallic Pt 1 Au x (0 ≤ x ≤ 230) and Pt catalysts at steady-state in pure water and relate kinetic parameters for H 2 O 2 and H 2 O formation to possible active site structures informed by complementary characterization methods. X-ray photoelectron spectra show significant Pt surface enrichment compared to the bulk composition. Analysis of infrared spectra of mixed monolayers of 12 CO* and 13 CO* indicate that Pt and Au form substitutional surface alloys. The Pt 1 Au x nanoparticles with the greatest mole fractions of Au predominantly expose Pt monomers (i.e., isolated Pt atoms), yet Pt atoms exposed upon all these nanoparticles possess electronic structures distinct from bulk Pt. Despite these differences, rate measurements are consistent with product formation through proton-electron transfer pathways for all Pt 1 Au x catalysts. In situ XAS indicate that Pt remains metallic during H 2 O 2 synthesis. Under the most oxidizing conditions, selectivities toward H 2 O 2 increase strongly with the Au to Pt ratio from 2% for monometallic Pt to 85% for Pt 1 Au 170 . However, selectivities are similar among all catalysts within reducing conditions. Comparisons of apparent activation enthalpies for the formation of H 2 O 2 and H 2 O across these catalysts and the range of conditions suggest that Pt monomers within Au provide the greatest selectivities for H 2 O 2 formation, because these active sites present high barriers for O-O bond rupture. Further, selectivities decrease with increasing ratios of H 2 to O 2 pressures, because Pt atoms aggregate and form oligomers that readily dissociate dioxygen intermediates. The combined use of spectroscopy, kinetics, and concepts employed in reaching these conclusions take inspiration from the legacy of Prof. Michel Boudart, and specifically his elegant methods for interrogating bimetallic catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Amorphous 2D Materials – A Novel Platform for Remote Epitaxy and Nanopatterned Epitaxy of III-V Semiconductors with Low Decomposition Temperatures

III-V semiconductor materials such as indium phosphide (InP) offer outstanding photonic properties that outperforms silicon, but the cost of these wafers is extremely expensive. Although reusing original wafers can effectively minimize the cost, current techniques for wafer recycling of these substrates add significant costs in fabrication, nullifying the cost savings by reusing the wafers. Besides, unlike other III-V materials such as gallium arsenide (GaAs), commonly used epitaxial lift-off method for wafer recycling is not well studied for materials like InP due to lack of lattice-matched sacrificial layers, which makes reusing these wafers more difficult. Remote epitaxy and nanopatterned epitaxy are newly discovered methods that enable single-crystal growth of III-V semiconductor thin films and easy exfoliation of these grown films, thus promising for a new cost-effective pathway of reusing wafers. However, previous methods of transferring two-dimensional (2D) materials, which use polymethyl methacrylate (PMMA) or metal stressor layers to transfer 2D materials grown on foreign substrates like copper (Cu) or silicon carbide (SiC), introduce defects and damages on the 2D layer and/or substrates during the transfer process. Remote epitaxial and nanopatterned epitaxial films grown on the damaged 2D layer/substrate suffer from lower crystal quality and imperfect exfoliation, which undermines wafer reusability and device performance. Here we report the MBE growth of amorphous boron nitride (a-BN) on InP wafers at low temperature that enabled improved quality of remote epitaxial and nanopatterned epitaxial films and their perfect exfoliation. We show fully covered a-BN on InP substrates despite their low decomposition temperatures. The surface of a-BN coated InP substrate remains smooth with a RMS roughness of around 3Â. We also demonstrate 100% coverage of single-crystal InP thin films grown on a-BN, with the film's quality significantly improved compared to the case of transferred 2D materials. In addition, the growth and exfoliation were successfully repeated multiple times, proving the feasibility for InP wafer recycling. Through this low temperature MBE growth approach with remote epitaxy and nanopatterned epitaxy, we successfully demonstrate large-scale flexible thin film exfoliation and recycling of InP substrates, which will lead to new opportunities in InP thin film-based photonics and novel heterostructures with significantly reduced cost.

Lu, Kuangye↗

DOE OSTI2022

Amorphous 2D Materials – A Novel Platform for Remote Epitaxy and Nanopatterned Epitaxy of III-V Semiconductors with Low Decomposition Temperatures

III-V semiconductor materials such as indium phosphide (InP) offer outstanding photonic properties that outperforms silicon, but the cost of these wafers is extremely expensive. Although reusing original wafers can effectively minimize the cost, current techniques for wafer recycling of these substrates add significant costs in fabrication, nullifying the cost savings by reusing the wafers. Besides, unlike other III-V materials such as gallium arsenide (GaAs), commonly used epitaxial lift-off method for wafer recycling is not well studied for materials like InP due to lack of lattice-matched sacrificial layers, which makes reusing these wafers more difficult. Remote epitaxy and nanopatterned epitaxy are newly discovered methods that enable single-crystal growth of III-V semiconductor thin films and easy exfoliation of these grown films, thus promising for a new cost-effective pathway of reusing wafers. However, previous methods of transferring two-dimensional (2D) materials, which use polymethyl methacrylate (PMMA) or metal stressor layers to transfer 2D materials grown on foreign substrates like copper (Cu) or silicon carbide (SiC), introduce defects and damages on the 2D layer and/or substrates during the transfer process. Remote epitaxial and nanopatterned epitaxial films grown on the damaged 2D layer/substrate suffer from lower crystal quality and imperfect exfoliation, which undermines wafer reusability and device performance. Here we report the MBE growth of amorphous boron nitride (a-BN) on InP wafers at low temperature that enabled improved quality of remote epitaxial and nanopatterned epitaxial films and their perfect exfoliation. We show fully covered a-BN on InP substrates despite their low decomposition temperatures. The surface of a-BN coated InP substrate remains smooth with a RMS roughness of around 3Å. We also demonstrate 100% coverage of single-crystal InP thin films grown on a-BN, with the film's quality significantly improved compared to the case of transferred 2D materials. In addition, the growth and exfoliation were successfully repeated multiple times, proving the feasibility for InP wafer recycling. Through this low temperature MBE growth approach with remote epitaxy and nanopatterned epitaxy, we successfully demonstrate large-scale flexible thin film exfoliation and recycling of InP substrates, which will lead to new opportunities in InP thin film-based photonics and novel heterostructures with significantly reduced cost.

Lu, Kuangye↗

DOE OSTI2021

Remote Alaska Communities Energy Efficiency Competition: Energy Efficiency for the Gem of the Yukon (Final Report)

Over the past decade, the City of Ruby has been proactive in working to reduce cost and energy use in the community. Ruby (Tl’aa’ologhe) is a remote city in Alaska located on the south bank of the Yukon River near the Kilbuck-Kuskokwim Mountains, about 50 air miles east of Galena and 230 air miles west of Fairbanks. As of 2019, the community has a population of over 150 people and most of Ruby’s residents are Koyukon Athabascan. Ruby has a long history of promoting local efficiency and clean energy in an effort to become more sustainable. Between 2007-2010, the community hosted Alaska’s first demonstration of an in-river hydrokinetic test project, sponsored by the Yukon River Inter-Tribal Watershed Council. In 2011, a 5kW solar photo-voltaic (PV) array was installed by the Interior Regional Housing Authority. In 2012, the community had a new power plant constructed by the Alaska Energy Authority that supplies waste heat to the washeteria, clinic and public safety garage, saving the community more than 4,000 gallons of heating fuel per year. The clinic, constructed by the Tanana Chiefs Conference, is one of the most energy efficient buildings in the interior and utilizes new building efficiency standards that were passed by the tribes. It has a 5kW solar PV array that provides energy into the local electric grid and offsets approximately 20% of the annual energy use. Building on this legacy, the City of Ruby entered into Department of Energy’s (DOE’s) Remote Alaska Communities Energy Efficiency Competition (RACEE) in 2016, pledging to reduce per-capita energy use 15% by 2020. During the second phase of the competition, 13 communities including Ruby were provided funding for tailored technical assistance to measure energy use and create energy efficiency plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Equipment List Comparing Balance of Plant Containing a Heat Pump against a Reference Electricity Generating Plant

Approximately two-thirds of U.S. energy consumption in the industrial and transportation sectors relies on fossil fuels. These sectors require high-quality heat, i.e., thermal energy at very high temperatures, for molecular transformation processes. The Integrated Energy Systems (IES) program aims to assess the economic potential of utilizing nuclear-grade heat from Advanced Reactors (ARs) to meet the high-quality heat demands. By having industrial processes (IPs) supplied with nuclear-generated heat, manufacturers could benefit from more stable and potentially lower energy costs, reducing reliance on volatile fossil fuel markets. The main outcome of the FY24 research was the thermodynamic assessment and gap analysis of steam generation for IP applications. The study completed in June 2024 demonstrated that the required steam temperatures could be achieved by integrating a heat pump into an AR power plant. After identifying the thermal demands of target IPs, multiple balance of plant configurations for the Xe-100 reactor by X-energy, incorporating a heat pump, were analyzed. Their technical feasibilities were assessed, including the design of suitable axial compressors for these applications. Comparative performance analysis showed that thermal efficiency alone is insufficient to evaluate system suitability. To address this, a new indicator (heat factor) was introduced in the report released in September 2024 to quantify the low-quality thermal power needed to produce one unit of high-quality heat for the IP. Results showed that integrating heat pumps into Rankine cycles enables higher steam temperatures, though at the expense of increased thermal energy input. This report builds upon and completes the foundational work previously undertaken. It focuses on the design of two Balance of Plant (BOP) configurations, both based on Rankine energy conversion cycles: “Case 1”, which involves electricity generation only, and “Case 2”, which combines electricity and high-temperature heat generation for industrial use. For each configuration, a comprehensive equipment list was developed, detailing all major components such as turbines, compressors, heat exchangers, pumps, and control systems. These lists will serve as the basis for future comparative cost analyses, with the goal of assessing the number and type of components required to integrate a heat pump into the Rankine cycle and to establish a heat transport system capable of delivering thermal energy from the nuclear plant to an industrial facility. Using the constitutive equations presented in the June 2024 milestone, the operating conditions of all BOP components for both “Case 1” and “Case 2” were evaluated. These parameters—such as temperature, pressure, mass flow rate, and steam quality—served as the basis for calculating the associated thermal and mechanical power flows. The net power required from the heat pump to raise the steam temperature to the target level was also determined. The thermodynamic performance of the configuration was then assessed using the heat factor metric. The key outcome of this analysis is a comparative table that presents the equipment that was used in the “Case 1” and “Case 2” configurations. This study offers a preliminary comparison of the two designs, providing insight into the impact of integrating a heat pump in terms of component requirements and thermal efficiency. This equipment list, together with the evaluated operating conditions, also serves as a foundation for the economic analyses scheduled for the current fiscal year.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗