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

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DOE OSTI2024

Guest Editorial Special Section on Advanced Medium-Voltage Power Electronics for Grid Interactive Applications

Medium-voltage power electronics (MVPE) plays essential roles in power grid modernization and links the MV distribution grid with low-voltage consumers and prosumers. Various MVPE devices, such as solid-state transformers or circuit breakers, inverter-based resources, power flow controllers, etc., bring the benefits of voltage conversion and power regulation in small footprint, power quality and efficiency improvements, and enhancements of grid controllability, flexibility, stability, and resilience. The MVPE also makes it possible for sustainable energy systems, such as solar/wind farms and energy storage generating facilities, to directly access to MV grids without multistage conversions. With their intrinsic intelligence and communications, MVPE enables many new smart grid functions and applications, e.g., dc interconnections and electric vehicle charging, which were not envisioned by traditional power grids otherwise. In addition, the integration of physical power processing units with cyber components forms a cyber-physical system, which is essential for long-term sustainability, development, and environmental preservation. Nonetheless, technical challenges on MVPE device reliability, scalable and efficient converter topologies, control stability, large-scale modeling and simulation, to name a few, need to be addressed and advanced to the next level. In conclusion, this Special Section on Advanced MV Power Electronics for Grid Interactive Applications in IEEE Transactions on Power Electronics (TPEL) provides an insight on some of the recent advances in MVPE and emerging challenges and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

How state transitions balance photosynthetic electron transport in plants – a quantitative study

In plants, the process of state transition regulates the allocation of sunlight energy between Photosystem II (PSII) and PSI. However, the implications of state transitions for harmonizing electron transport rates between photosystems, and a full quantitative picture of this process, remain underexplored. We integrated quantitative biology (biochemical and biophysical approaches) with in vivo spectroscopy on wild-type Arabidopsis and protein phosphorylation mutants. This combination facilitated monitoring of Chl redistribution and its functional implications for light harvesting and electron transport. Our findings demonstrate the reallocation of 12% of highly phosphorylated ‘extra’ light-harvesting complex II under state 2 from stacked to unstacked thylakoids. This reduces the number of Chls per PSII from 216 to 182, while increasing the number in PSI from 187 to 223. Such Chl redistribution compensates for differences in photosystem stoichiometry and photochemical quantum efficiencies, thereby precisely synchronizing electron transport rates in both photosystems. Mutant analyses corroborate that this regulatory mechanism involves reversible phosphorylation. We inferred that state transitions optimize linear electron transport, leaving no additional capacity for cyclic electron transport. Furthermore, the results suggest that the controversies about long-range migration of LHCII from stacked to unstacked thylakoid domains arise from differences in phosphorylation levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Local respiratory motion correction for PET/CT imaging: Application to lung cancer

Purpose: Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. Methods: Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. Results: Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid deformation model in LRMC led to over an order of magnitude gain in computational efficiency of the correction relative to the application of the deformable model to the whole FOV. Conclusions: The results of this study support the use of LMRC as a flexible and efficient correction approach for respiratory motion effects for single lesions in the thoracic area.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Voltage control of unidirectional anisotropy in ferromagnet-multiferroic system

Demonstration of ultralow energy switching mechanisms is imperative for continued improvements in computing devices. Ferroelectric (FE) and multiferroic (MF) order and their manipulation promise an ideal combination of state variables to reach attojoule range for logic and memory (i.e., ~30× lower switching energy than nanoelectronics). In BiFeO 3 (BFO), the coupling between the antiferromagnetic (AFM) and FE order is robust at room temperature, scalable in voltage, stabilized by the FE order, and can be integrated into a fabrication process for a beyond-CMOS (complementary metal-oxide semiconductor) era. The presence of the AFM order and a canted magnetic moment in this system causes exchange interaction with a ferromagnet such as Co 0.9 Fe 0.1 or La 0.7 Sr 0.3 MnO 3 . Previous research has shown that exchange coupling (uniaxial anisotropy) can be controlled with an electric field. However, voltage modulation of unidirectional anisotropy, which is preferred for logic and memory technologies, has not yet been demonstrated. Here, we present evidence for electric field control of exchange bias of laterally scaled spin valves that is exchange coupled to BFO at room temperature. We show that the exchange bias in this bilayer is robust, electrically controlled, and reversible. We anticipate that magnetoelectricity at these scaled dimensions provides a powerful pathway for computing beyond modern nanoelectronics by enabling a new class of nonvolatile, ultralow energy computing elements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗
DOE OSTI2026

Detect the Unobservable: Abnormality Detection in mixed Autonomy for Lane Change Maneuver with Following Vehicles’ Trajectories Only

Highly Automated Vehicles (HAVs) and Advanced Driver-Assistance Systems (ADAS) are transforming modern transportation with enhanced mobility, safety, and efficiency. Despite their advantages, cybersecurity vulnerabilities in these systems can lead to abnormal behavior, posing significant risks to surrounding human-driven vehicles (HDVs) in mixed traffic environments. Here, this article addresses the challenge of detecting abnormal lateral movements of HAVs/ADAS vehicles using only trajectory profiles of following HDVs. Specifically, we propose a novel modeling approach that captures both normal and abnormal lateral behaviors through vehicle kinematics, integrated decision-making processes, vehicle control using symbolic regression for lane change vehicles. Additionally, we introduce an abnormality detection framework that relies on observable HDV data, even in occlusion scenarios. The framework evaluates the sensitivity of various car-following models to detect abnormal behaviors, providing insights into the interaction between HAVs/ADAS and HDVs in mixed autonomy systems.

Connected and Automated vehicles↗
DOE OSTI2025

GRinding Automated Classification Engine

This work is an ML-driven framework for automated surface analysis of microscopy images. We create a training dataset by imaging stainless steel samples to benchmark four developed deep neural network architectures. These models, based on a YOLOv8n-cls backend, integrate image features and process metadata using various fusion methods to distinguish between acceptable and unacceptable surface finishes. This code is associated with publication "Classifying Alloy Surface Preparation Quality with Metadata-Infused Machine Learning for Rapid Alloy Discovery" for project APEX LDRD-ER (25-ERD-039)

Gongora, AldairE [Lawrence Livermore National Labo↗
DOE OSTI2019

Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS

The effective identification of clouds and monitoring of their evolution are important toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation algorithm is developed using image processing techniques. This method integrates morphological image gradient magnitudes to separate cloud systems and patches boundaries. A varying scale kernel is implemented to reduce the sensitivity of image segmentation to noise and to capture objects with various finenesses of the edges in remote sensing images. The proposed method is flexible and extendable from single to multispectral imagery. Case studies were carried out to validate the algorithm by applying the proposed segmentation algorithm to synthetic radiances for channels of the Geostationary Operational Environmental Satellite ( GOES-16) simulated by a high-resolution weather prediction model. The proposed method compares favorably with the existing cloud-patch-based segmentation technique implemented in the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall retrieval algorithm. Evaluation of event-based images indicates that the proposed algorithm has potentials comparing to the conventional segmentation technique used in PERSIANN-CCS to improve rain detection and estimation skills with an accuracy rate of up to 98% in identifying cloud regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

FastProNGS: fast preprocessing of next-generation sequencing reads

Background Next-generation sequencing technology is developing rapidly and the vast amount of data that is generated needs to be preprocessed for downstream analyses. Yet, until now, software that can efficiently make all the quality assessments and filtration of raw data is still lacking. Results We developed FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest. Read information before and after filtration can be output in plain-text, JSON, or HTML formats with user-friendly visualization. Conclusions FastProNGS is a rapid, standardized, and user-friendly tool for preprocessing next-generation sequencing data within minutes. It is an all-in-one software that is convenient for bulk data analysis. It is additionally very flexible and can implement different functions using different user-set parameter combinations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Designing Critical Experiments Using Gaussian Process Optimization

New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Photonic crystal nanobeam biosensors based on porous silicon

Photonic crystal (PhC) nanobeams (NB) patterned on porous silicon (PSi) waveguide substrates are demonstrated for the specific, label-free detection of oligonucleotides. These photonic structures combine the large active sensing area intrinsic to PSi sensors with the high-quality (Q) factor and low-mode volume characteristic of compact resonant silicon-on-insulator (SOI) PhC NB devices. The PSi PhC NB can achieve a Q-factor near 9,000 and has an approximately 40-fold increased active sensing area for molecular attachment, compared to traditional SOI PhC NB sensors. The PSi PhC NB exhibits a resonance shift that is more than one order of magnitude larger than that of a similarly designed SOI PhC NB for the detection of small chemical molecules and 16-base peptide nucleic acids. Furthermore the design and fabrication of PSi PhC NB sensors are compatible with CMOS processing, sensor arrays, and integration with lab-on-chip systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scalable low-loss cryogenic packaging of quantum memories in CMOS-foundry processed photonic chips

Optically linked solid-state quantum memories such as color centers in diamond are a promising platform for distributed quantum information processing and networking. Photonic integrated circuits (PICs) have emerged as a crucial enabling technology for these systems, integrating quantum memories with efficient electrical and optical interfaces in a compact and scalable platform. Packaging these hybrid chips into deployable modules while maintaining low optical loss and resiliency to temperature cycling is a central challenge to their practical use. We demonstrate a packaging method for PICs using surface grating couplers and angle-polished fiber arrays that is robust to temperature cycling, offers scalable channel count, applies to a wide variety of PIC platforms and wavelengths, and offers pathways to automated high-throughput packaging. Using this method, we show optically and electrically packaged quantum memory modules integrating all required qubit controls on chip, operating at millikelvin temperatures with <3 dB losses achievable from fiber to quantum memory for the TE 0 mode at a wavelength of 737 nm.

Bernson, Robert [Tyndall National Institute, Cork ↗
DOE OSTI2012

A Unified Anatomy Ontology of the Vertebrate Skeletal System

The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

ZEB1 insufficiency causes corneal endothelial cell state transition and altered cellular processing

The zinc finger e-box binding homeobox 1 (ZEB1) transcription factor is a master regulator of the epithelial to mesenchymal transition (EMT), and of the reverse mesenchymal to epithelial transition (MET) processes. ZEB1 plays an integral role in mediating cell state transitions during cell lineage specification, wound healing and disease. EMT/MET are characterized by distinct changes in molecular and cellular phenotype that are generally context-independent. Posterior polymorphous corneal dystrophy (PPCD), associated with ZEB1 insufficiency, provides a new biological context in which to understand and evaluate the classic EMT/MET paradigm. PPCD is characterized by a cadherin-switch and transition to an epithelial-like transcriptomic and cellular phenotype, which we study in a cell-based model of PPCD generated using CRISPR-Cas9-mediated ZEB1 knockout in corneal endothelial cells (CEnCs). Transcriptomic and functional studies support the hypothesis that CEnC undergo a MET-like transition in PPCD, termed endothelial to epithelial transition (EnET), and lead to the conclusion that EnET may be considered a corollary to the classic EMT/MET paradigm.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Building Diagnostic Market Deployment (Final Report)

Operational faults are pervasive across the commercial buildings sector, wasting energy and increasing energy costs by up to about 30% (Mills 2009, Liu et al. 2003, Claridge et al. 2000, Katipamula and Brambley 2008, and Brambley and Katipamula 2009). Automated fault detection and diagnostic (AFDD) tools provide capabilities essential for detecting and correcting these problems and eliminating the associated energy waste and costs. The U.S. Department of Energy's (DOE) Building Technology Program (BTP) has previously invested in developing and testing of such diagnostic tools for whole-building (and major system) energy use, air handlers, chillers, cooling towers, chilled-water distribution systems, and boilers. These diagnostic processes can be used to make the commercial buildings more energy efficient. The work described in this report was done as part of a Cooperative Research and Development Agreement (CRADA) between the U.S. Department of Energy's Pacific Northwest National Laboratory (PNNL) and KGS Building LLC (KGS). PNNL and KGS both believe that the widespread adoption of AFDD tools will result in significant reduction to energy and peak energy consumption. The report provides an introduction and summary of the various tasks performed under the CRADA. The CRADA project had three major focus areas: (1) Technical Assistance for Whole Building Energy Diagnostician (WBE) Commercialization, (2) Market Transfer of the Outdoor Air/Economizer Diagnostician (OAE), and (3) Development and Deployment of Automated Diagnostics to Improve Large Commercial Building Operations. PNNL has previously developed two diagnostic tools: (1) whole building energy (WBE) diagnostician and (2) outdoor air/economizer (OAE) diagnostician. WBE diagnostician is currently licensed non-exclusively to one company. As part of this CRADA, PNNL developed implementation documentation and provided technical support to KGS to implement the tool into their software suite, Clockworks. PNNL also provided validation data sets and the WBE software tool to validate the KGS implementation. OAE diagnostician automatically detects and diagnoses problems with outdoor air ventilation and economizer operation for air handling units (AHUs) in commercial buildings using data available from building automation systems (BASs). As part of this CRADA, PNNL developed implementation documentation and provided technical support to KGS to implement the tool into their software suite. PNNL also provided validation data sets and the OAE software tool to validate the KGS implementation. Finally, as part of this CRADA project, PNNL developed new processes to automate parts of the re-tuning process and transfer those process to KGS for integration into their software product. The transfer of DOE-funded technologies will transform the commercial buildings sector by making buildings more energy efficient and also reducing the carbon footprint from the buildings. As part of the CRADA with PNNL, KGS implemented the whole building energy diagnostician, a portion of outdoor air economizer diagnostician and a number of measures that automate the identification of re-tuning measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Field Assessment of Energy Audit Tools for Retrofit Programs

This project focused on the use of home energy ratings as a tool to promote energy retrofits in existing homes. A home energy rating provides a quantitative appraisal of a home's asset performance, usually compared to a benchmark such as the average energy use of similar homes in the same region. Home rating systems can help motivate homeowners in several ways. Ratings can clearly communicate a home's achievable energy efficiency potential, provide a quantitative assessment of energy savings after retrofits are completed, and show homeowners how they rate compared to their neighbors, thus creating an incentive to conform to a social standard. An important consideration is how rating tools for the retrofit market will integrate with existing home energy service programs. For residential programs that target energy savings only, home visits should be focused on key efficiency measures for that home. In order to gain wide adoption, a rating tool must be easily integrated into the field process, demonstrate consistency and reasonable accuracy to earn the trust of home energy technicians, and have a low monetary cost and time hurdle for homeowners. Along with the Home Energy Score, this project also evaluated the energy modeling performance of SIMPLE and REM/Rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Computer-Based Procedures for Field Workers - Identified Benefits

The Idaho National Laboratory (INL) computer-based procedure (CBP) research team is exploring how best to design a CBP system that will deliver the intended benefits of increased efficiency and improved human performance. It is important to note that no “off-the-shelf” technology exists for the type of CBP system that is investigated and developed by the INL researchers. As more technology is integrated into the procedure process the importance of an appropriate and methodological approach to the design of the procedure system increases. Technological advancements offer great opportunities for efficiency and safety gains, however if the system is not designed correctly there is a large risk of unintentionally introducing new opportunities for human errors. The INL research team is breaking new ground in the area of CBPs with the prototype they have developed. Current electronic procedure systems are most commonly electronic versions of the paper-based procedures with hyperlinks to other procedures, limited user input functionality, and the ability to mark steps completed. These systems do not fully exploit the advantages digital technology. It is a part of the INL researchers’ role to develop and validate new CBP technologies that greatly increase the benefits of a CBP system to the nuclear industry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Novel concepts for the compression of large volumes of carbon dioxide-phase III

In the effort to reduce the release of CO 2 greenhouse gases to the atmosphere, sequestration of CO 2 from Integrated Gasification Combined Cycle (IGCC) and Oxy-Fuel power plants is being pursued. This approach, however, requires significant compression power to boost the pressure to typical pipeline levels. The penalty can be as high as 8-12% on a typical IGCC plant. The goal of this research is to reduce this penalty through novel compression concepts and integration with existing IGCC processes. The primary objective of the study of novel CO 2 compression concepts is to reliably boost the pressure of CO 2 to pipeline pressures with the minimal amount of energy required. Fundamental thermodynamics were studied to explore pressure rise in both liquid and gaseous states. For gaseous compression, the project investigated novel methods to compress CO 2 while removing the heat of compression internal to the compressor. The highpressure ratio, due to the delivery pressure of the CO 2 for enhanced oil recovery, results in significant heat of compression. Since less energy is required to boost the pressure of a cooler gas stream, both upstream and inter-stage cooling is desirable. While isothermal compression has been utilized in some services, it has not been optimized for the IGCC environment. Phase I of this project determined the optimum compressor configuration and developed technology concepts for internal heat removal. Other compression options using liquefied CO 2 and cryogenic pumping were explored as well. Preliminary analysis indicated up to a 35% reduction in power is possible with the new concepts being considered. In the Phase II program, two experimental test rigs were developed to investigate the two concepts further. A new pump loop facility was constructed to qualify a cryogenic turbopump for use on liquid CO 2 . Also, an internally cooled compressor diaphragm was developed and tested in a closed loop compressor facility using CO 2 . Both test programs successfully demonstrated good performance and mechanical behavior. In Phase III, a pilot compression plant consisting of a multi-stage centrifugal compressor with cooled diaphragm technology has been designed, constructed, and tested. Comparative testing of adiabatic and cooled tests at equivalent inlet conditions shows that the cooled diaphragms reduce power consumption by 3-8% when the compressor is operated as a back-to-back unit and by up to 9% when operated as a straight-though compressor with no intercooler. The power savings, heat exchanger effectiveness, and temperature drops for the cooled diaphragm were all slightly higher than predicted values but showed the same trends.

54 ENVIRONMENTAL SCIENCES↗