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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 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 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 ↗

DOE OSTI2022

Performance Assessment of High-Efficiency Refrigerated Display Cases with Low-GWP Refrigerants: Preprint

As California policy makers enforce new regulations such as SB 1383 to achieve state greenhouse gas (GHG) reduction goals, it will be critical to understand the energy efficiency implications of low global warming potential (GWP) refrigerants in commercial refrigeration applications. The goal of this research project, funded by Commonwealth Edison was to assess the energy performance of two high efficiency medium-temperature, self-contained, reach-in display cases that utilized natural refrigerant propane (R-290), and hydrofluorocarbon (HFC) drop-in hydrofluoroolefin R-513a, respectively. Performance of these display cases were compared to a baseline fixture using HFC (R-134a) under equal conditions in a controlled environment chamber. These display cases were selected due to their widespread use in convenience stores, and small supermarkets. The high efficiency cases were equipped with energy efficient lighting, improved panel insulation, high efficiency evaporator and condenser fan motors, and high effectiveness heat exchangers. The test method used in this project was foundationally inspired by the ANSI/ASHRAE 72-2018 standard method to evaluate each case under equivalent conditions. However, minor modifications to this methodology were implemented to better represent more realistic operation of the units. While maintaining target product temperature, the energy efficient fixtures containing R-290 and R-513a consumed 61.8% to 32.6% less energy, respectively, than a baseline case using R-134a refrigerant. The daily energy consumption of the R-290, R-513a, and baseline display cases at the upper limit of environmental conditions was 4.30, 7.59, and 11.26 kWh/day, respectively.

alternative refrigerants↗

DOE OSTI2020

Enhanced carbon-transfer and -utilization efficiencies achieved using membrane carbonation with gas sources having a range of CO 2 concentrations

The economic viability of microalgal biofuels relies on increasing productivity in a cost-effective manner. As microalgal biomass contains > 50% carbon, a high rate of CO 2 delivery is required for high productivity, and inefficient CO 2 delivery amplifies operating costs. Membrane carbonation using non-porous hollow fiber membranes can ideally deliver CO 2 without bubble formation and high carbon transfer efficiency. Because CO 2 streams from industrial resources are not 100% CO 2 , the buildup of inert gasses can significantly lower the CO 2 delivery rate when the distal end of the membrane is closed. To overcome the buildup of inert gases, we managed the distal end of the membranes with three different approaches: fully open end, restricted bleed valve, and restricted bleed valve with pH-actuated venting. For all approaches, CO 2 was delivered to membranes ondemand based on a pH set point. Evaluating a wide range of CO 2 concentrations (10% to 100%), we found that all approaches eliminated the buildup of inert gases, could maintain target pH values and gave the same biomass productivities and carbon distributions. However, carbon transfer efficiency depended on the operation of the distal end. Fully open-end operation gave a poor carbon transfer efficiency because of excessive loss of CO 2 from the distal end. However, restricting the exit flow rate to ≤4 cm 3 /min mitigated the problems of excessive CO 2 loss, but without incurring a large loss of CO 2 -delivery flux. For the continuous cultivation, combining a restricted bleed valve with pH-actuated venting improved the carbon-transfer efficiency and -utilization efficiencies up to 85% and 67%, respectively, with a sufficient CO 2 delivery flux.

42 ENGINEERING↗

DOE OSTI2021

US building energy efficiency and flexibility as an electric grid resource

Buildings consume 75% of U.S. electricity; therefore, improving the efficiency and flexibility of building operations could increase the reliability and resilience of the rapidly-changing electricity system. We estimate the technical potential near- and long-term impacts of best available building efficiency and flexibility measures on annual electricity use and hourly demand across the contiguous U.S. Co-deployment of building efficiency and flexibility avoids up to 742 TWh of annual electricity use and 181 GW of daily net peak load in 2030, rising to 800 TWh and 208 GW by 2050; at least 59 GW and 69 GW of the peak reductions are dispatchable. Implementing efficiency measures alongside flexibility measures reduces the potential for off-peak load increases, underscoring limitations on load shifting in efficient buildings. Overall, however, we find a substantial building-grid resource that could reduce future fossil-fired generation needs while also reducing dependence on energy storage with increasing variable renewable energy penetration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Low temperature absolute internal quantum efficiency of InGaN-based light-emitting diodes

A method to reveal low temperature absolute internal quantum efficiency of an InGaN-based light-emitting diode (LED) is reported. Structural (via scanning electron and atomic force microscopies, x-ray diffraction, and Raman spectroscopy) and optical (via temperature- and power-dependent photoluminescence) properties of InGaN-based blue LEDs are coupled with a channel-based recombination model, which reveals the low temperature absolute internal quantum efficiency of the LED on traditional sapphire and emerging Si (111) substrates as 27.5% and 71.1%, respectively. High low-temperature absolute internal quantum efficiency of the former is attributed to its lower defect density and less strain. Furthermore, our results show assuming perfect (i.e., 100%) internal quantum efficiency in an InGaN-based LED at low temperatures could be misleading, and using negative thermal quenching properties of defect luminesce bands with a channel-based recombination model can be a method to quantify LED's less than ideal low temperature internal quantum efficiencies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass ( Panicum virgatum L.)

Switchgrass (Panicum virgatum L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, caffeoyl-CoA O-methyltransferase (CCoAOMT) and <alfin-like 6(AL6), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Variable-Speed Pump Efficiency Calculation For Fluid Flow Systems with and without Static Head

To accurately calculate pump energy savings gained from implementing variable frequency drive (VFD) controls, the variation of pump efficiency must be considered when operating conditions transition from the design operating point to new operating points. Many software tools require users to specify the new pump efficiency, or it is assumed to be unchanged. Unfortunately, many users have challenges of estimating the pump efficiency at new operating points. This paper presents a simplified method of estimating centrifugal pump efficiency at new operating speeds when the pump is controlled by a VFD. This methodology applies to systems with and without static head when the system curve is not affected by the change, and also systems where the change in operation changes the system curve.A hypothetical fluid flow system and centrifugal pump were used to demonstrate the calculation process for these scenarios. For this hypothetical system, the pump’s efficiency at new operating points was up to 5.4% lower than the design operating point.

42 ENGINEERING↗

DOE OSTI2022

Polymerized Small Molecular Acceptor with Branched Side Chains for All Polymer Solar Cells with Efficiency over 16.7%

The power conversion efficiencies (PCEs) of small molecule acceptor (SMA)-based organic solar cells have already exceeded 18%. However, the development of polymer acceptors still lags far behind their SMA counterparts mainly due to the lack of efficient polymer acceptors. In this work, a series of polymer acceptors named PY-X (with X being the branched alkyl chain) are designed and synthesized by employing the same central core with the SMA L8-BO but with different branched alkyl chains on the pyrrole motif. It is found that the molecular packing of SMA-HD featuring 2-hexyldecyl side chain used in the synthesis of PY-HD is similar to L8-BO, in which the branched alkyl chains lead to condensed and high-order molecular assembly in SMA-HD molecules. When combined with PM6, PY-HD-based all polymer solar cell (all-PSC) exhibits a high PCE of 16.41%, representing the highest efficiency for the binary all-PSCs. Moreover, the side-chain modification on the pyrrole site position further improves the performance of the all-PSCs, and the PY-DT-based device delivers a new record high efficiency of 16.76% (certified as 16.3%). The work provides new insights for understanding the structure–property relationship of polymer acceptors and paves a feasible avenue to develop efficient conjugated polymer acceptors.

14 SOLAR ENERGY↗

DOE OSTI2020

High-efficiency single-junction p-i-n GaAs solar cell on roll-to-roll epi-ready flexible metal foils for low-cost photovoltaics

We demonstrate the fabrication and characterization of high-efficiency, single-junction p-i-n GaAs solar cells, on flexible metal foil with epi-ready buffer via roll-to-roll fabrication. Single-junction p-i-n GaAs solar cells were fabricated using metal–organic chemical vapor deposition (MOCVD). Furthermore, an efficiency greater than 13% was obtained at 1 sun, which is the highest reported efficiency on GaAs photovoltaics directly deposited on metal tapes. This exceeds our previously reported study showcasing 11.5% efficiency on single-junction p-n solar cell structure. Improved morphology of p-i-n structure compared with p-n is explained by atomic force microscopy (AFM), scanning electron microscopy (SEM), and helium ion microscopy (HIM) measurements. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis showed reduced Zn diffusion in p-i-n cell compared with the p-n cell. We attribute the improvement in efficiency of p-i-n cells on flexible metal tapes to the quality of the junction, surface morphology, controlled diffusion of species within the active layers, and increase in absorption due to the optimized intrinsic layer thickness.

14 SOLAR ENERGY↗