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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Performance evaluation of an air conditioning system based on quasi isothermal dehumidifcation

This work presents a first study of novel air conditioning system based on quasi isothermal dehumidification combined with dew-point evaporative cooling through the Maisotsenko cycle (M-Cycle). The dehumidification process is realized in desiccant coated heat exchanger with heat rejection system. The key idea behind the solution is to maximize the cooling effectiveness by creating favourable conditions for dehumidification and evaporative cooling process. This is achieved by rejecting the heat of sorption in the desiccant system and providing cold and dry air for M-Cycle air cooler, which allows the system to be powered by using low-grade heat energy at 50 °C. The analysis is performed on the basis of experimentally validated numerical models of each component combined in a unified model of the system. The goal of the study is to determine the performance of the solution under different operational conditions. In addition two types of M-Cycle air coolers (i.e. cross-flow and regenerative unit) are compared to establish which unit is more suitable as the source of cooling energy for the system. It was established that proposed system is able to provide comfortable room parameters (supply air temperature equal 17 °C and humidity ratio equal 0.010 kg/kg-da) for outdoor air temperatures ranging from 28 to 36 °C and outdoor air humidity ranging from 0.010 to 0.018 kg/kg-da. This means that the proposed solution is able to provide comfortable conditions in temperate and humid climates. Results also indicate that the system consisting of the regenerative M-Cycle HMX allows better cooling load management, offers higher thermal Coefficient of Performance (COP th ) and uses less water compared to the system with the cross-flow HMX. However, the system with cross-flow heat and mass exchanger (HMX) has a relatively greater electrical Coefficient of Performance (COP el ) in most cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

DOE OSTI2022

High-Fidelity Heavy-Duty Vehicle Modeling Using Sparse Telematics Data

Heavy-duty commercial vehicles consume a significant amount of energy due to their large size and mass, directly leading to vehicle operators prioritizing energy efficiency to reduce operational costs and comply with environmental regulations. One tool that can be used for the evaluation of energy efficiency in heavy-duty vehicles is the evaluation of energy efficiency using vehicle modeling and simulation. Simulation provides a path for energy efficiency improvement by allowing rapid experimentation of different vehicle characteristics on fuel consumption without the need for costly physical prototyping. The research presented in this paper focuses on using real-world, sparsely sampled telematics data from a large fleet of heavy-duty vehicles to create high-fidelity models for simulation. Samples in the telematics dataset are collected sporadically, resulting in sparse data with an infrequent and irregular sampling rate. Captured in the dataset was geospatial information, time series measurements, and vehicle-specific metadata from a subset of 96 vehicles from varied geographic regions across North America. A series of custom algorithms was developed to process vehicle data and derive both vehicle model input parameters and representative drive cycles. Derived models provide a basis on which to simulate real-world vehicles and iterate on vehicle aerodynamics, auxiliary power loads, transmission shift schedules, and other parameters to achieve reduced fuel consumption and increase energy efficiency. Notably, these models were developed without the use of expensive field data collection, using only data collected through fleet telematics. Processed representative drive cycles are used to validate the fuel economy of derived models. The models developed through this research allow for more representative vehicle simulations with increased flexibility regarding vehicle-to-vehicle variations.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Electrochemically in situ formed rocksalt phase in titanium dioxide determines pseudocapacitive sodium-ion storage

Earth-abundant TiO 2 is a promising negative electrode for low-cost sodium-ion batteries (SIBs) owing to its high capacity, rapid (dis)charging capability, safe operation potential and nonflammability. Crystalline anatase TiO 2 is not suitable for reversible Na + (de)intercalation, but it displays pseudocapacitive response after repeated cycles. Herein, we find and demonstrate that ordered rocksalt (RS) NaTiO 2 nanograins are in situ formed by electrochemically cycling with Na + ions in anatase and amorphous TiO 2 . The in situ formed RS-NaTiO 2 follows a solid-solution reaction with small volume changes of only 2.0%, that determines the pseudocapacitive “mirror-like” cyclic voltammetry curve with a couple of broad redox peaks at 0.75 V vs. Na + /Na, a high capacity of 253 mAh g −1 , high-rate capability and thousands of stable cycles. The multistep crystalline-to-amorphous-to-RS transformations are able to be electrochemically activated during the aging process of assembled full cells. Our finding provides a direction for developing unconventional Ti-based high-performance active materials for SIBs with both high energy and power densities.

Tang, Dafu [Xiamen University (China); Innovation ↗

DOE OSTI2024

Data and scripts associated with “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” (v2)

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. This data package was originally published August 2024. It was updated January 2025 (modified files). See the change history in the readme more details. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

54 ENVIRONMENTAL SCIENCES↗

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 OSTI2026

Chloride modification of vacuum-assisted blade-coated perovskite solar cells and mini-modules in ambient environment

Scalable deposition of perovskite thin films under ambient conditions remains a key challenge for the commercialization of perovskite photovoltaics, primarily due to the difficulty of controlling crystallization kinetics and suppressing non-radiative recombination during film formation. In this work, we present an effective strategy to modulate crystallization kinetics and non-radiative recombination in vacuum-quenched blade-coated perovskite films processed in air using chloride-based additives. By systematically comparing PbCl 2 and 3-chloropropylamine hydrochloride (Cl-PACl), we elucidate how different chloride incorporation pathways influence crystallization behavior and optoelectronic properties. In situ transmission and in situ photoluminescence measurements reveal that PbCl 2 acts as a transient additive that slows intermediate/perovskite phase formation while suppressing non-radiative recombination, leading to improved film quality. In contrast, Cl-PACl introduces additional trap states that deteriorate optoelectronic performance. As a result, PbCl 2 -modified perovskite solar cells achieve a champion power conversion efficiency (PCE) of 24.2% and remarkable operational stability, retaining over 90% of their initial performance after 800 hours of continuous illumination. Furthermore, we successfully scaled the process, fabricating a perovskite mini-module that delivered a champion efficiency of 18.0%. This study underscores the critical importance of coupling vacuum-assisted blade coating with transient additive engineering for achieving high-performance, stable, and scalable perovskite photovoltaics processed in ambient air.

14 SOLAR ENERGY↗

DOE OSTI2021

Performance of a Natural Gas Solid Oxide Fuel Cell System With and Without Carbon Capture

The fuel cell program at the United States Department of Energy (DOE) National Energy Technology Laboratory (NETL) is focused on the development of low-cost, highly efficient, and reliable fossil-fuel-based solid oxide fuel cell (SOFC) power systems that can generate environmentally-friendly electric power with at least 90 percent carbon capture. NETL’s SOFC technology development roadmap is aligned with near-term market opportunities in the distributed generation sector to validate and advance the technology while paving the way for utility-scale natural gas (NG)- and coal-derived synthesis gas-fueled applications via progressively larger system demonstrations. The present study represents a part of a series of system evaluations being carried out at NETL to aid in prioritizing technological advances along research pathways to the realization of utility-scale SOFC systems, a transformational goal of the fuel cell program. In particular, the system performance of utility-scale NG fuel cell (NGFC) systems with and without carbon dioxide (CO2) capture is presented. The NGFC system analyzed features an external auto-thermal reformer (ATR) feeding the fuel to the SOFC system consisting of planar anode-supported SOFC with separated anode and cathode off-gas streams. In systems with CO2 capture, an air separation unit (ASU) is used to provide the oxygen for the ATR and for the combustion of unutilized fuel in the SOFC anode exhaust along with a CO2 purification unit to provide a nearly pure CO2 stream suitable for transport for usage in enhanced oil recovery operations or for storage in underground saline formations. Remaining thermal energy in the exhaust gases is recovered in a bottoming steam Rankine cycle while supplying any process heat requirements. A reduced order model (ROM) developed at the Pacific Northwest National Laboratory (PNNL) is used to predict the SOFC performance. The ROM, while being computationally effective for system studies, provides other detailed information about the state of the stack, such as the internal temperature gradient, generally not available from simple performance models often used to represent the SOFC. Such additional information can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall system reliability. The NGFC system performance was analyzed by varying salient system parameters, including the percent of internal (to the SOFC module) NG reformation—ranging from 0 to 100 percent—fuel utilization, and current density. The impact of advances in underlying SOFC technology on electrical performance was also explored.

solid oxide fuel cell (SOFC), natural gas fuel cel↗

DOE OSTI2025

High-Power Impulse Magnetron Sputter Deposition of Boron Carbide with Full-Face Erosion Magnetron and Mixed Ar-Ne Plasma

Boron carbide (B 4 C) is an attractive inertial confinement fusion ablator material. The fabrication of B4C ablators by magnetron sputtering requires process optimization. To increase process flexibility, here we explore high-power impulse magnetron sputter (HiPIMS) deposition of B 4 C in pure Ar and mixed Ar-Ne plasmas. Here, the results show that higher plasma discharge currents can be reached with a mixed Ar-Ne plasma in the entire working pressure range studied (5 𝑡𝑜 50 mTorr). At 45 mTorr with 10% of Ne in the Ar-Ne mix, high peak target current densities of ~1 A cm −2 were demonstrated. Films deposited with such a mixed Ar-Ne plasma with a full-face erosion magnetron source on substrates biased at −25 V exhibited higher density and improved mechanical properties, albeit with higher compressive residual stresses compared to the case of HiPIMS deposition in a pure Ar plasma. This work demonstrates additional process flexibility of the HiPIMS discharge mode for the deposition of B 4 C coatings.

Ablator capsule↗

DOE OSTI2020

Using the Carbon Capture Simulation Initiative (CCSI) Tool to Design the Experiments in the Parametric Campaign of a Novel Compact Absorber for Carbon Capture

Gas absorption towers with structured packing and solvent have been used for Carbon Dioxide (CO 2 ) Capture for about many decades. To overcome process limitations and practical disadvantages for CO 2 capture from the stationary emitter (e.g. NG and coal power plant), many new designs have been proposed and explored at the various scales in the last decade with aim of either low energy penalty or low capital cost. To reduce the size of the absorption tower and hence the total cost of CO 2 capture, the University of Kentucky Center for Applied Energy Research Center (UK CAER) has designed and built a novel CO 2 capture absorption tower or Compact Absorber, integrated into an existing large-bench scale CO 2 capture unit. The Compact Absorber has three sections. The top of the column is a fogging section where the solvent is sprayed through a nozzle producing droplets flowing downward in a co-current fashion with the flue gas. The center of the column is a frothing section where the solvent and flue gas flow through regenerative frothing screens designed by Industrial Climate Solutions, Inc. The bottom of the column is a typical structured packing section were the flue gas and solvent flow in a counter-current fashion. The parametric campaign will be conducted in order to optimize the operating parameters for CO 2 capture including liquid/gas ratio, lean loading, and temperature, liquid residence time. A simulated flue gas with 14% CO 2 will be used along with a UK CAER developed proprietary solvent. The 100-hour parametric campaign is designed using a statistical approach of the Sequential Design of Experiments (sDOE). sDOE is one of the CCSI tools that provides an adaptive statistical approach for designing future experiments based on the results of previous experiments. Application of a typical DOE provides the user with the minimum number of experiments required to get the same data, but sDOE allows the user to make an informed choice of experiments based on the results of previous experiments. The complete absorption column has been constructed and has been partially commissioned. Initial data has been collected by operating using the fogging section and the frothing section. The fogging section produces solvent droplets of about 100 μm sauter mean diameter and as small as 25 μm using a hydraulic nozzle by BETE. The frothing section produces bubbles of about 5mm with high mixing of solvent promoting the higher mass transfer from gas to liquid. The absorber reaches the capture efficiency of about 50% with only two sections in operation. Based on the current results, it can be deduced that increasing the solvent feed temperature and including the packed section for absorption the capture efficiency will increase further. Initial data will be collected using all three sections of the absorber and will be used for sDOE. Non-Uniform Space Filling model of sDOE will be used to prioritize the input conditions resulting into maximum capture efficiency. sDOE is performed using the platform called Framework Optimization, Quantification of Uncertainty, and Surrogates (FOQUS). The method and results demonstrating the progress of the parametric campaign from the initial set of experiments to the final stage of obtaining optimized parameters using sDOE tool will be presented in detail.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

Fully integrated multi-phase buck converter with coupled air core inductors

A multi-phase buck switching converter having grouped pairs of phases, each phase using two magnetically coupled air-core inductors. For each group, a first driver circuit controlling switching of a first power transistor switching circuit coupled to a first air-core inductor output for driving an output load at the first phase. A second driver circuit controlling switching of a second power transistor switching circuit coupled to a second air-core inductor output for driving said output load at the second phase. The first and second phases are spaced 180° apart. The coupled air-core inductors per group of such orientation, separation distance and mutual inductance polarity relative to each other such that magnetic coupling between the two or more inductors at each phase results in a net increase in effective inductance per unit volume. Each air-core inductor is a metal slab of defined length, height and thickness formed using back-end-of-line semiconductor manufacturing process.

Zhang, Xin↗

DOE OSTI2021

Fully integrated multi-phase buck converter with coupled air core inductors

Zhang, Xin↗

DOE OSTI2021

Towards single-chip radiofrequency signal processing via acoustoelectric electron–phonon interactions

Abstract The addition of active, nonlinear, and nonreciprocal functionalities to passive piezoelectric acoustic wave technologies could enable all-acoustic and therefore ultra-compact radiofrequency signal processors. Toward this goal, we present a heterogeneously integrated acoustoelectric material platform consisting of a 50 nm indium gallium arsenide epitaxial semiconductor film in direct contact with a 41° YX lithium niobate piezoelectric substrate. We then demonstrate three of the main components of an all-acoustic radiofrequency signal processor: passive delay line filters, amplifiers, and circulators. Heterogeneous integration allows for simultaneous, independent optimization of the piezoelectric-acoustic and electronic properties, leading to the highest performing surface acoustic wave amplifiers ever developed in terms of gain per unit length and DC power dissipation, as well as the first-ever demonstrated acoustoelectric circulator with an isolation of 46 dB with a pulsed DC bias. Finally, we describe how the remaining components of an all-acoustic radiofrequency signal processor are an extension of this work.

36 MATERIALS SCIENCE↗

DOE OSTI2022

In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Lithography-Free Mesa Isolation by Laser Ablation for Multijunction III-V Photovoltaic Space Power Generation

Eliminating photolithography from photovoltaic device processing is a significant opportunity for cost reduction and increased manufacturing throughput. In this work, we test femtosecond laser ablation and scribing as an alternative to contact photolithography and wet chemical etching for mesa isolation of multijunction devices. We demonstrate that upright multijunction devices isolated by using the laser as a scribe to cleave through the substrate had virtually no performance loss when compared to a baseline device processed with photolithography. By contrast, devices isolated by laser ablating through the active layers have performance losses that cannot be fully eliminated with postprocess etching. This demonstration of photolithography-free mesa isolation with no performance losses is promising as a pathway to less expensive and higher throughput III-V device manufacturing.

14 SOLAR ENERGY↗

DOE OSTI2025

Net Present Value Optimization of a Natural Gas Combined Cycle Plant with CO 2 Capture using a Water-Lean Solvent Considering Transient Electricity Price for Multiple Regions

Global CO 2 emissions are increasing at about a 1.5% rate per year. Fossil fuel-based plants are one of the main contributors to this rise. In the power generation industry, fossil fuel plants are dominant, and many plants are under development. In this study, a natural gas combined cycle (NGCC) power plant with postcombustion capture using a leading water-lean solvent is considered. For optimal design and operating schedule, large-scale dynamic optimization is undertaken for net present value (NPV) optimization. The first principle dynamic model of NGCC is developed, including a model of the highly efficient H-class gas turbines. For computational tractability of the dynamic optimization problem, a reduced-order model is developed by using the Hankel singular value decomposition. A waterlean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine, is used for carbon capture. A model of the capture system is developed in Aspen Plus, which is used to develop a reduced-order model by using ALAMO, a machine learning software. In addition, a reduced model of the CO 2 compression system with a dehydration unit is also considered. The integrated system is used for NPV optimization by using the Python-based PYOMO platform. The PCC process is analyzed for three configurations-conventional packed bed, rotating packed bed (RPB), and a combination of RPB and direct contact cooler. The NPV optimization is performed for 14 regional markets by considering year-long clustered and continuous locational marginal price data with a 1 h interval. Optimization results show that the PCC can achieve 90% CO 2 capture with a positive NPV for six regions. Sensitivity studies conducted by using the PCC configurations indicate that the process is economically feasible for 9 regions out of 14 regional electricity markets with NPV values in the range of 33−540 $MM.

cabon capture↗

DOE OSTI2025

Upstream considerations for gas fermentation processes

Gas fermentation enables the production of fuels, chemicals, and foods from gaseous carbon sources and could serve as a technology for valorizing carbon that may otherwise be emitted to the atmosphere. In this review, we focus on upstream feedstock considerations: the supply of carbon and the supply of electrical power. Electrical power serves a dual role, providing both process energy and biochemical redox potential (via hydrogen or reduced intermediates). We define gas fermentation as bioprocesses involving gaseous feedstocks metabolized by microbes, distinct from microbial electrosynthesis. Trends in CO 2 point sources and low-carbon electricity systems are analyzed, highlighting opportunities and challenges for future deployment. This review synthesizes current knowledge and identifies key R&D priorities for process integration at industrial scale.

09 BIOMASS FUELS↗