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DOE OSTI2021

Best Practices Guide: Benchmarking Energy Efficiency in Laboratories

Purpose and Audience A wide spectrum of laboratory owners, ranging from universities to federal agencies, have explicit goals for energy efficiency and greenhouse gas reductions in their facilities. For example, new federal buildings and major renovations of existing buildings are to reduce fossil fuel-generated energy consumption by 90% in 2025, and 100% in 2030, compared with a 2003 baseline (FEMP n.d.). Minnesota SB2030 standard requires achieving an 80% reduction from the average building baseline for commercial, institutional, and industrial buildings (SB2030 n.d). A laboratory—new or existing—is much more likely to meet energy efficiency goals if quantitative metrics and targets are explicitly specified and tracked over the life cycle of the building, from design through construction, commissioning, operations, and renovations. If efficiency targets are not explicitly and properly defined, any additional capital costs or design time associated with attaining higher efficiencies can be difficult to justify relative to other priorities. The purpose of this guide is to provide guidance on how to specify and compute energy efficiency metrics and benchmarks for laboratories, at the whole-building as well as the system level. The information in this guide can be used to incorporate quantitative metrics and targets into new construction or retrofit of existing facilities. For information on strategies and technologies to achieve energy efficiency, the reader is referred to I2SL resources, including technology best practice guides and case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Pilot Testing of a Highly Efficient Pre-combustion Sorbent-based Carbon Capture System

TDA developed and demonstrated a highly efficient pre-combustion carbon capture system. The overall objective of this work was to develop a new sorbent-based pre-combustion carbon capture technology for Integrated Gasification Combined Cycle (IGCC) power plants. In this project our goal was to demonstrate the techno-economic viability of the new technology by 1) demonstrating it in large-scale slipstream tests, and 2) carrying out a high fidelity engineering and cost analysis. TDA’s process used an advanced physical adsorbent that selectively removes CO 2 from coal-derived synthesis gas above the dew point of the gas at temperatures as high as 300°C. The sorbent consists of a mesoporous carbon whose surface was grafted with functional groups that remove CO 2 via a well-known acid-base interaction. As documented in bench-scale experiments and field tests with actual coal gas, the sorbent achieved a very high capacity for CO 2 at temperatures as high as 300°C. The sorbent bound CO 2 more strongly than common physical adsorbents, providing the chemical potential needed for the high temperature operation. However, because CO 2 does not form a true covalent bond with the surface sites (as is the case with chemical absorbents), the sorbent regeneration could be carried out with only a very small energy input. The heat input to regenerate our sorbent was only 4.9 kcal per mol of CO 2 , which is much lower than that for chemical absorbents (e.g., 29.9 kcal/mol CO 2 for sodium carbonate) and was similar to the requirements of physical solvents (e.g., 4 kcal/mol CO 2 for Selexol TM ). Because the sorbent operates above the dew point of the synthesis gas (unlike the Selexol TM process), a higher power cycle efficiency can be achieved. With previous DOE/NETL funding (Contract No. DE-FE-0000469), we demonstrated the techno-economic viability of the technology in bench-scale tests and slipstream demonstrations at the National Carbon Capture Center (NCCC), Wilsonville, Alabama and Wabash River IGCC plant in Terra Haute, Indiana. We demonstrated a stable working CO 2 capacity for over 11,650 cycles with simulated synthesis gas. We also evaluated its performance with actual synthesis gas in two test campaigns at the Wabash River IGCC Plant, Terre Haute, IN and the National Carbon Capture Center (NCCC), Wilsonville, AL. The slipstream tests clearly showed that the actual coal gas constituents and potential contaminants (e.g. trace metals, halides, tars) had no effect on the sorbent’s ability to remove CO 2 (the same sorbent beds were used in both field tests with no sign of deactivation for 2,000 cycles with over 26,750 SCF of gas treated). As expected, due to the high temperature CO 2 removal capability and low energy needed to regenerate the sorbent, the power cycle efficiency with our process was greater than 34% on a higher heating value (HHV) basis; in comparison, the same IGCC plant equipped with the Selexol TM solvent for carbon capture can only achieve 31.4% HHV efficiency. The capital cost for an IGCC system with TDA’s process is estimated as $2,417/kW e , which is 12% lower than that of the IGCC/ Selexol TM process. The levelized cost for electricity including the transport, storage and monitoring (TS&M) cost for CO 2 was calculated as $\$ $92.9/MWh (lowest reported to our knowledge), which is much better than the $105.2/MWh estimated for the IGCC/ Selexol TM process. In this project (DE-FE0013105), TDA Research, in collaboration with our partners Gas Technology Institute (GTI), Illinois Clean Coal Institute (ICCI), University of California, Irvine (UCI), University of Alberta (UOA), Siemens, NCCC and Sinopec advanced the technical maturity of the technology; scaling it up by a factor of 100. We optimized the reactor design using computational fluid dynamics (CFD); using adsorption modeling we improved the pressure swing adsorption (PSA) cycle sequence. We carried out two field test campaigns with a fully-equipped 0.1 MW e prototype unit (for a total of 844 hours) using actual synthesis gas to prove the viability of the new technology. A successful 30 day (707 hrs) evaluation was completed at NCCC under air blown gasification conditions. We demonstrated 97.3% carbon capture at 1,500 SLPM, 93% carbon capture at 1,800 SLPM, and 90% carbon capture at 2,100 SLPM in the NCCC tests. We also demonstrated the system for 137 hours at a Sinopec petrochemical plant under oxygen blown gasification, demonstrating 86% carbon capture at 2,660 SLPM. In collaboration with University of California, Irvine (UCI), we completed a techno-economic analysis (TEA) for TDA’s warm gas cleanup technology integrated to IGCC power plant. The net plant efficiencies (on a coal HHV basis) for the warm gas cleanup cases were estimated to be 34.0% for E-GasTM gasifier, 34.4% for GE gasifier, 33.4 for the Shell gasifier and 34.2 for the TRIG TM gasifier (Cases 2, 4, 6 and 8 in this study) with a catalytic combustor for CO 2 purification, which are significantly higher than those for the Cold Gas Case, or an increase of as much as 12% in the heat rate for Case 2, 6% for Case 4, 9% for Case 6, and 9% for Case 8. The 1st year cost of electricity with the transport, storage and monitoring (TS&M) costs for the CO 2 included was $\$ $129.2/MWh for the E-GasTM gasifier Warm Gas Cleanup Case, $\$ $131.9/MWh for the GE gasifier Warm Gas Cleanup Case, $\$ $146.8/MWh for the Shell Gasifier Warm Gas Cleanup Case, and $\$ $129.9/MWh for the TRIG TM gasifier Warm Gas Cleanup Case. For comparison, the costs for the baseline Cold Gas CO 2 removal with Selexol for the different gasifiers were: $\$ $146.6/MWh for the E-Gas TM gasifier, $\$ $142.2/MWh for the GE gasifier, $\$ $159.0/MWh for the Shell gasifier and $\$ $144.3/MWh for the TRIG TM gasifier. In summary, the costs for our system were 7 to 12% lower than the corresponding Cold Gas Cleanup cases. The results of this techno-economic analysis suggested that TDA’s high temperature PSA-based Warm Gas Clean-up Technology can make a substantial improvement in the IGCC plant thermal performance for achieving near zero CO 2 emissions for E-Gas TM , GE, Shell and TRIG TM gasifier based IGCC power plants. The capital expenses were estimated to be lower than that of Selexol’s™. Taken together, the higher net plant efficiency and lower capital and operating costs resulted in substantial reduction in the cost of carbon capture for the IGCC plant equipped with TDA’s high temperature PSA-based carbon capture system. Finally, in collaboration with Gas Technology Institute (GTI) we completed the environmental health and safety assessment for TDA’s warm gas carbon capture technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

HydroGEN Seedling: High-Temperature Reactor Catalyst Material Development for Low-Cost and Efficient Solar-Driven Sulfur-Based Processes

The HyS process, driven by solar power, has great potential to reach high-efficiency and low-cost hydrogen production without greenhouse gas emissions. The high-temperature section of the HyS cycle, which operates the catalytic decomposition of sulfuric acid into sulfur dioxide, oxygen, and water, is a fundamental part of the cycle affecting the overall plant efficiency and cost. Therefore, a high-performance catalyst (i.e., low cost, high catalytic activity, and low degradation catalyst) is of critical importance to achieve high efficiency and low hydrogen cost. Research and development has highlighted that a Pt-based monometallic catalyst had unacceptable catalytic activity and performance degradation for a high-efficiency and low-cost hydrogen production process. A high-efficiency solar receiver-reactor system, which incorporates the new catalyst, also needs to be developed to achieve the required plant efficiency and cost. Greenway Energy (GWE) and the University of South Carolina (USC), partnering with HydroGEN node laboratories Idaho National Laboratory (INL), Savannah River National Laboratory (SRNL), and National Renewable Energy Laboratory (NREL), propose the development of a new catalyst formulation, included in a novel solar receiver-reactor concept, to be tested experimentally in the last part of the project.

08 HYDROGEN↗
DOE OSTI2024

Protective Catalyst Systems on III-V and Si-based Semiconductors for Efficient, Durable Photoelectrochemical Water Splitting Devices

The overall goal of this project was to develop unassisted water splitting devices based on III-V materials, creating pathways to improve performance in terms of efficiency, improve durability, and cost. One major objective is to develop pathways to systems that can ultimately achieve > 20% solar-to-hydrogen (STH) efficiency. Another objective was to develop pathways to high efficiency systems that can operate on-sun for at least 2 weeks. With respect to cost, this research provide new approaches to tandem photoelectrode design and fabrication that one day may allow for costs to reach $200/m 2 . Two distinct water splitting schemes were explored: Scheme 1 aims to develop high efficiency devices with tandem III-V photoabsorbers (e.g. GaInP 2 /GaInAs) with Scheme 2 targeting cost reduction while maintaining high efficiency by growing InGaN on crystalline Si (InGaN/Si). Both schemes were employed to couple with thin film, semi-transparent, catalytic/protection layers containing reduced or zero precious metal content that can enhance durability while maintaining high efficiency and enabling low material costs. Overall the project greatly advanced the technology to developing high performance systems with increased durability, as demonstrated by true on-sun testing through partnership with the National Renewable Energy Laboratory (NREL).

08 HYDROGEN↗
DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

CRISPR-Cas9/Cas12a systems for efficient genome editing and large genomic fragment deletions in Aspergillus niger

CRISPR technology has revolutionized fungal genetic engineering by accelerating the pace and expanding the feasible scope of experiments in this field. Among various CRISPR-Cas systems, Cas9 and Cas12a are widely used in genetic and metabolic engineering. In filamentous fungi, both Cas9 and Cas12a have been utilized as CRISPR nucleases. In this work we first compared efficacies and types of genetic edits for CRISPR-Cas9 and -Cas12a systems at the polyketide synthase (albA) gene locus in Aspergillus niger. By employing a tRNA-based gRNA polycistronic cassette, both Cas9 and Cas12a have demonstrated equally remarkable editing efficacy. Cas12a showed potential superiority over Cas9 protein when one gRNA was used for targeting, achieving an editing efficiency of 86.5% compared to 31.7% for Cas9. Moreover, when employing two gRNAs for targeting, both systems achieved up to 100% editing efficiency for single gene editing. In addition, the CRISPR-Cas9 system has been reported to induce large genomic deletions in various species. However, its use for engineering large chromosomal segments deletions in filamentous fungi still requires optimization. Here, we engineered Cas9 and -Cas12a-induced large genomic fragment deletions by targeting various genomic regions of A. niger ranging from 3.5 kb to 40 kb. Our findings demonstrate that targeted engineering of large chromosomal segments can be achieved, with deletions of up to 69.1% efficiency. Furthermore, by targeting a secondary metabolite gene cluster, we show that fragments over 100 kb can be efficiently and specifically deleted using the CRISPR-Cas9 or -Cas12a system. Overall, in this paper, we present an efficient multi-gRNA genome editing system utilizing Cas9 or Cas12a that enables highly efficient targeted editing of genes and large chromosomal regions in A. niger.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Analytical Examination of the Relationship between Fuel Properties, Engine Efficiency, and R Factor Values

The variability in gasoline energy content, though most frequently not a consumer concern, is an issue of concern for vehicle manufacturers in demonstrating compliance with regulatory requirements. Advancements in both vehicle technology, test methodology, and fuel formulations have increased the level of visibility and concern with regard to the energy content of fuels used for regulatory testing. The R factor was introduced into fuel economy calculations for vehicle certification in the late 1980s as a means of addressing batch-to-batch variations in the heating value of certification fuels and the resulting variations in fuel economy results. While previous studies have investigated values of the R factor for modern vehicles through experimentation, subsequent engine studies have made clear that it is difficult to distinguish between the confounding factors that influence engine efficiency when R is being studied experimentally. The proposed study focuses on an analytical approach to examining the heating value effects so that R values can be studied without the influence of confounding effects of other fuel properties. Data previously published for a 1.6-liter naturally-aspirated engine are used as a case study to explore the relationship between fuel properties, engine efficiency, and R factor values. The results demonstrate that engine efficiency does vary as a result of differences in heating value among fuels, although other factors that are variant among fuels also impact efficiency. R factor values depend not only on the difference in heating value between two fuels, but also on the directionality of the change and on engine operating loads. The latter is integral because the reference engine efficiency point is itself a function of the engine operating condition. R factor values asymptotically approach unity as engine operating load increases. Increasing engine efficiency causes R values for a given test fuel to increase. A method is presented for which the test data from only one fuel is required to establish R factor values for individual vehicles and test cycles. An alternative method of establishing Indolene fuel economy equivalency for certification tests is also discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Design and Development of a High-Efficiency Single Cylinder Natural Gas-Fueled Jet Ignition Engine

The current energy climate has created a push toward reducing consumption of fossil fuels and lowering emissions output in power generation applications. Combined with the desire for a more distributed energy grid, there is currently a need for small displacement, high efficiency engines for use in stationary power generation. An enabling technology for achieving high efficiencies with spark ignited engines for such applications is the use of jet ignition which enables ultra-lean (λ > ~1.6) combustion via air dilution.This paper provides a comprehensive review of the development of a 390cc, high efficiency single cylinder natural gas-fueled jet ignition engine operating ultra-lean. The engine was developed as part of the Department of Energy’s Advanced Research Projects Agency–Energy (DOE ARPA-E) GENSETS program. Design choices for minimizing friction are highlighted as well as test results showing further friction reduction through downspeeding. Extensive hardware optimization of the combustion system has been performed and results are presented for air-flow path optimization and the jet igniter. The efficiency benefits related to enleanment and downspeeding are analyzed using an efficiency loss breakdown based on the First Law of Thermodynamics. Through optimization efforts a peak brake thermal efficiency in excess of 34% was achieved, representing an increase of greater than 20% over the current state-of-the-industry for comparably sized CNG engines.

Peters, Nathan↗
DOE OSTI2015

Single-Crystalline InGaAs/InP Dense Micro-Pillar Forest on Poly-Silicon Substrates for Low-Cost High-Efficiency Solar Cells

The ultimate goal of this project is to develop a photovoltaic system high conversion efficiency (>20%) using high quality III-V compound-based three-dimensional micro-structures on silicon and poly-silicon. Such a PV-system could be of very low cost due to minimum usages of III-V materials. This project will address the barriers that currently hamper the performance of solar cells based on three-dimensional micro-structures. To accomplish this goal the project is divided into 4 tasks, each dealing with a different aspect of the project: materials quality, micropillar growth control, light management, and pillar based solar cells. Materials Quality: the internal quantum efficiency (IQE) - by which is meant here the internal fluorescence yield - of the micro-pillars has to be increased. We aim at achieving an IQE of 45% by the end of the first year. By the end of the second year there will be a go-no-go milestone of 65% IQE. By the end of year 3 and 4 we aim to achieve 75% and 90% IQE, respectively. Micropillar growth control: dense forests of micropillars with high fill ratios need to be grown. Pillars within forests should show minimum variations in size. We aim at achieving fill ratios of 2%, 10%, >15%, >20% in years 1, 2, 3, and 4, respectively. Variations in dimension should be minimized by site-controlled growth of pillars. By the end of year 1 we will aim at achieving site-controlled growth with > 15% yield. By end of year 2 the variation of critical pillar dimensions should be less than 25%. Light management: high light absorption in the spectral range of the sun has been to be demonstrated for the micropillar forests. By the end of year 1 we will employ FDTD simulation techniques to demonstrate that pillar forests with fill ratios <20% can achieve 99% light absorption. By end of year 2 our original goal was to demonstrate >85% absorption. By end of year 3 > 90% absorption should be demonstrated. Pillar based solar cells: devices will be studied to explore ways to achieve high open-circuit voltages which will lead to high efficiency micropillar-based solar cells. We will start on single pillar devices and the findings in these studies should pave the way for devices based on forests/ arrays of pillars. By the end of the second year we aim to demonstrate a single pillar device with an open-circuit voltage of 0.7 V, as well as a pillar-forest based device with 8% conversion efficiency. By the end of year 3 these numbers should be improved to 0.9 V open-circuit voltage for single pillar devices and >15% efficiency for forest/array-based devices. We will aim to realize a device with 20% efficiency by the end of the project period.

Chang-Hasnain, Constance↗
DOE OSTI2012

Development of Rear Contact Technologies for Next Generation High-Efficiency Silicon Solar Cells

Project Objective: The objective of this program is to develop low-cost high-quality rear contacts and fabricate production-ready high-efficiency monocrystalline (~20%) and multicrystalline (17-18%) silicon solar cells. This efficiency enhancement on thin Si wafers will help achieve the Solar America Initiative goal of a levelized cost of electricity less than 10¢ per kWh by 2015. Background: The efficiency of current c-Si solar cells is strongly dependent on back surface passivation because recent advances in crystal growth and cell processing can produce bulk diffusion lengths greater than the wafer thickness. Improving the rear contact quality realizes three benefits simultaneously: gain in absolute efficiency, ability to use lower quality thin wafers, and better Si utilization. In this project, we will investigate and develop four novel back contact technologies that can lower the back surface recombination velocity (BSRV) and enhance the back surface reflectance (BSR). These rear contact technologies include (a) novel dielectric passivation of the rear surface (b) local contact window opening through a dielectric by screen printing or laser patterning (c) a novel boron diffusion process for p+ back surface field (B-BSF) and (d) a-Si passivation of the p-type rear Si surface in conjunction with screen printed front contacts. Our device modeling and analysis shows that these technologies can raise production-ready large area cell efficiencies in our laboratory from 17.5-18.0% to ~20.0% and expedite their commercialization. These rear contact technologies will allow the use of thin Si wafers (100-150 μm) without any wafer warpage or compromise in cell efficiency.

14 SOLAR ENERGY↗
DOE OSTI2015

High-efficiency silicon heterojunction solar cells: Status and perspectives

Silicon heterojunction technology (HJT) uses silicon thin-film deposition techniques to fabricate photovoltaic devices from mono-crystalline silicon wafers (c-Si). This enables energy-conversion efficiencies above 21 %, also at industrial-production level. In this presentation we review the present status of this technology and point out recent trends. We first discuss how the properties of thin hydrogenated amorphous silicon (a-Si:H) films can be exploited to fabricate passivating contacts, which is the key to high- efficiency HJT solar cells. Such contacts enable very high operating voltages, approaching the theoretical limits, and yield small temperature coefficients. With this approach, an increasing number of groups are reporting devices with conversion efficiencies well over 20 % on both-sides contacted n-type cells, Panasonic leading the field with 24.7 %. Exciting results have also been obtained on p-type wafers. Despite these high voltages, important efficiency gains can still be made in fill factor and optical design. This requires improved understanding of carrier transport across device interfaces and reduced parasitic absorption in HJT solar cells. For the latter, several strategies can be followed: Short-wavelength losses can be reduced by replacing the front a-Si:H films with wider-bandgap window layers, such as silicon alloys or even metal oxides. Long- wavelength losses are mitigated by introducing new high-mobility TCO’s such as hydrogenated indium oxide, and also by designing new rear reflectors. Optical shadow losses caused by the front metallization grid are significantly reduced by replacing printed silver electrodes with fine-line plated copper contacts, leading also to possible cost advantages. The ultimate approach to minimize optical losses is the implementation of back-contacted architectures, which are completely devoid of grid shadow losses and parasitic absorption in the front layers can be minimized irrespective of electrical transport requirements. The validity of this approach was convincingly demonstrated by Panasonic, Japan in 2014, reporting on an interdigitated back-contacted HJT cell with an efficiency of 25.6%, setting the new single-junction c-Si record. Finally, given the virtually perfect surface passivation and excellent red response of HJT solar cells, we anticipate these devices will also become the preferred bottom cell in ultra-high efficiency c-Si-based tandem devices, exploiting better the solar spectrum. Such tandem cells have the potential to overcome the fundamental single-junction limit of silicon solar cells (29.4%). Combining HJT cells with perovskite solar cells as top cell appears to be particularly appealing.

14 SOLAR ENERGY↗
DOE OSTI2015

High-efficiency silicon heterojunction solar cells: Status and perspectives

Silicon heterojunction technology (HJT) uses silicon thin-film deposition techniques to fabricate photovoltaic devices from mono-crystalline silicon wafers (c-Si). This enables energy-conversion efficiencies above 21 %, also at industrial-production level. In this presentation we review the present status of this technology and point out recent trends. We first discuss how the properties of thin hydrogenated amorphous silicon (a-Si:H) films can be exploited to fabricate passivating contacts, which is the key to high- efficiency HJT solar cells. Such contacts enable very high operating voltages, approaching the theoretical limits, and yield small temperature coefficients. With this approach, an increasing number of groups are reporting devices with conversion efficiencies well over 20 % on n-type wafers, Panasonic leading the field with 24.7 %. Exciting results have also been obtained on p-type wafers. Despite these high voltages, important efficiency gains can still be made in fill factor and optical design. This requires improved understanding of carrier transport across device interfaces and reduced parasitic absorption in HJT solar cells. For the latter, several strategies can be followed: Short- wavelength losses can be reduced by replacing the front a-Si:H films with wider-bandgap window layers, such as silicon alloys or even metal oxides. Long-wavelength losses are mitigated by introducing new high-mobility TCO’s such as hydrogenated indium oxide, and also by designing new rear reflectors. Optical shadow losses caused by the front metalisation grid are significantly reduced by replacing printed silver electrodes with fine-line plated copper contacts, leading also to possible cost advantages. The ultimate approach to minimize optical losses is the implementation of back-contacted architectures, which are completely devoid of grid shadow losses and parasitic absorption in the front layers can be minimized irrespective of electrical transport requirements. The validity of this approach was convincingly demonstrated by Panasonic, Japan in 2014, reporting on an interdigitated back-contacted HJT cell with an efficiency of 25.6%, setting the new single-junction c-Si record. Finally, given the virtually perfect surface passivation and excellent red response of HJT solar cells, we anticipate these devices will also become the preferred bottom cell in ultra-high efficiency c-Si-based tandem devices, exploiting better the solar spectrum. Such tandem cells have the potential to overcome the fundamental single-junction limit of silicon solar cells (29.4%). Combining HJT cells with perovskite solar cells as top cell appears to be particularly appealing.

14 SOLAR ENERGY↗
DOE OSTI2015

Assessing Energy Efficiency Opportunities in US Industrial and Commercial Building Motor Systems

In 2002, the United States Department of Energy (USDOE) published an energy efficiency assessment of U.S. industrial sector motor systems titled United States Industrial Electric Motor Systems Market Opportunities Assessment. The assessment advanced motor system efficiency by providing a greater understanding of the energy consumption, use characteristics, and energy efficiency improvement potential of industrial sector motor systems in the U.S. Since 2002, regulations such as Minimum Energy Performance Standards, cost reductions for motor system components such as variable frequency drives, system-integrated motor-driven equipment, and awareness programs for motor system energy efficiency have changed the landscape of U.S. motor system energy consumption. To capture the new landscape, the USDOE has initiated a three-year Motor System Market Assessment (MSMA), led by Lawrence Berkeley National Laboratory (LBNL). The MSMA will assess the energy consumption, operational and maintenance characteristics, and efficiency improvement opportunity of U.S. industrial sector and commercial building motor systems. As part of the MSMA, a significant effort is currently underway to conduct field assessments of motor systems from a sample of facilities representative of U.S. commercial and industrial motor system energy consumption. The Field Assessment Plan used for these assessments builds on recent LBNL research presented at EEMODS 2011 and EEMODS 2013 using methods for characterizing and determining regional motor system energy efficiency opportunities. This paper provides an update on the development and progress of the MSMA, focusing on the Field Assessment Plan and the framework for assessing the global supply chain for emerging motors and drive technologies.

Rao, Prakash↗
DOE OSTI2019

15%-efficiency (Mg,Zn)CdTe solar cells with 1.7 eV bandgap for tandem applications

The overall objective of this project was to demonstrate a 15%-efficient Cd(Mg,Zn)Te solar cell with a bandgap of 1.7–1.9 eV. Such a cell would be a critical first step towards market-competitive flat-plate modules with efficiencies significantly higher than is achievable with single-junction silicon or thin-film modules. In particular, Cd(Mg,Zn)Te may be the optimum top cell for pairing with silicon in a tandem. It promises low cost and long-term stability not available with other top-cell candidates, and, while 1.5 eV polycrystalline CdTe cells have already achieved 22.1% efficiency, no serious efforts have been undertaken to demonstrate an efficient 1.7–1.9 eV Cd(Mg,Zn)Te cell. This project was the first such effort. To reach 15% efficiency, this project specifically aimed to develop (1) high-quality Cd(Mg,Zn)Te absorbers that minimize non-radiative recombination and thereby maximize the quasi-fermi level splitting, and (2) effective electron and hole (heterojunction) contacts that allow the full quasi-Fermi-level splitting (chemical potential) to be extracted at the metal electrodes (electrical potential). To this end, 1.7–1.9 eV Cd(Mg,Zn)Te absorber layers and heterojunction contacts were developed in parallel using molecular beam epitaxy (MBE) and close-space sublimation (CSS) growth; the former defines the upper bounds of performance and provides insight into material and device limitations, whereas the latter ensures that technology developed within the project is readily transferable to industry. Minority-carrier lifetime served as the primary metric for the first aim; open-circuit voltage (V oc ) and efficiency served as metrics for the second.

Holman, Zachary↗
DOE OSTI2021

Efficient Active Learning for Gaussian Process Classification by Error Reduction

Active learning sequentially selects the best instance for labeling by optimizing an acquisition function to enhance data/label efficiency. The selection can be either from a discrete instance set (pool-based scenario) or a continuous instance space (query synthesis scenario). In this work, we study both active learning scenarios for Gaussian Process Classification (GPC). The existing active learning strategies that maximize the Estimated Error Reduction (EER) aim at reducing the classification error after training with the new acquired instance in a onestep-look-ahead manner. The computation of EER-based acquisition functions is typically prohibitive as it requires retraining the GPC with every new query. Moreover, as the EER is not smooth, it can not be combined with gradient-based optimization techniques to efficiently explore the continuous instance space for query synthesis. To overcome these critical limitations, we develop computationally efficient algorithms for EER-based active learning with GPC. Further, we derive the joint predictive distribution of label pairs as a one-dimensional integral, as a result of which the computation of the acquisition function avoids retraining the GPC for each query, remarkably reducing the computational overhead. We also derive the gradient chain rule to efficiently calculate the gradient of the acquisition function, which leads to the first query synthesis active learning algorithm implementing EER-based strategies. Our experiments clearly demonstrate the computational efficiency of the proposed algorithms. We also benchmark our algorithms on both synthetic and real-world datasets, which show superior performance in terms of sampling efficiency compared to the existing state-of-the-art algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Efficiency Improvement Progress in Green, Yellow and Red III Nitride LEDs

Large improvements in the efficiencies of visible light emitting diodes (LEDs) have been realized over the last decade. Extending the range of wavelengths over which efficient emission can be realized continues to be a goal of active research. Efficiency droop refers to a non-thermal decrease in internal quantum efficiency with increasing current density that affects III-nitride LEDs in general, but more severely those with longer emission wavelengths. The so-called green gap is mainly related to the wavelength dependence of efficiency droop. The peak EQE in commercial green LEDs exceeds 60% but corresponds to a current density that is an order of magnitude lower than required for applications. In this presentation, we will review some of the underlying physics that contribute to the wavelength dependence of droop. We will discuss some challenges in the development of long wavelength III-nitride LEDs and possible strategies to mitigate efficiency droop based on the understanding that nonradiative Auger recombination is the root cause. One general strategy is to engineer the multi-quantum well active region to minimize the average carrier density. Another approach is to design wells with a more favorable balance between the radiative and Auger coefficients. Finally, we will present the current status of the performance of green, yellow and red III-Nitride LEDs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C$_3$F$_8$ dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. The PICO Collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C$_3$F$_8$ from calibration data taken with 5 distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 keV to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov-Chain Monte-Carlo (MCMC) routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 keV and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be $\geq 50\, \%$ for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be $\geq 50\, \%$ for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated data sets are used to calculate a p-value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗