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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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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Regional economic potential for recycling consumer waste electronics in the United States

Waste electronics are a growing environmental concern but also contain materials of great economic value. If properly recycled, waste electronics could enhance the sustainability of vital metal supply chains by offsetting the increasing demand for virgin mining. However, rapid changes in the size and composition of electronics complicate their end-of-life management. Here we couple material flow and geospatial analyses on over 90 critical consumer electronic products and find that over 1 billion devices, representing up to 1.5 million tonnes of mass, could be discarded annually in the United States by 2033. Emerging electronics such as connected home, health and augmented/virtual reality devices have become the fastest-growing types in the waste stream. Here we highlight policy opportunities to develop various sustainable circularity strategies around metal supply chains by showing the potential to integrate waste electronics and virgin mining pathways in western US regions, while new infrastructure designed specifically for waste electronics treatment is favourable in the central and eastern United States. Furthermore, we show the importance of building national-level refining and tear-down databases to improve electronics end-of-life management in the next decade.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Calculation of the Vertical Strata Load of Utility Tunnel Crossing Ground Fissure Zone

A ground fissure is a geological disaster in which the vertical dislocation of strata causes surface rupture. Ground fissures can cause extreme harm to the surface and underground buildings. Ground fissure activity can result in different settlement on the two sides of the strata, which will generate additional stress (pressure) that differs from the stress of the general stratum on underground structures across the ground fissure zone. It is essential to assess the effective stress of strata in the design of underground engineering structures across a ground fissure zone. The Xi’an ground fissure through a utility tunnel was focus of the research, and a physical model and data for oblique crossing of the 45° ground fissure were analyzed. A model of the utility tunnel structure was established, including the surrounding soil load as an active ground fissure environment. This model was used to calculate the vertical formation pressure of the overlying soil on the utility tunnel. A method to calculate the overlying load on the utility tunnel caused by ground fissure activity was proposed and compared with the calculation based on the A. Marston principle. The results showed that the ground fissure load calculation method based on the strata-holding effect can effectively calculate the earth pressure of the surrounding soil layer of the utility tunnel in the cross-ground fissure section. The results of this work provide guidance and reference value for the design of a utility tunnel in an area with the potential for a ground fissure.

Zhang, Dan↗
DOE OSTI2021

Multifidelity computing for coupling full and reduced order models

Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a multifidelity problem sharing an interface between various formulations or heterogeneous computational entities. To this end, we present a robust hybrid analysis and modeling approach combining a physics-based full order model (FOM) and a data-driven reduced order model (ROM) to form the building blocks of an integrated approach among mixed fidelity descriptions toward predictive digital twin technologies. At the interface, we introduce a long short-term memory network to bridge these high and low-fidelity models in various forms of interfacial error correction or prolongation. The proposed interface learning approaches are tested as a new way to address ROM-FOM coupling problems solving nonlinear advection-diffusion flow situations with a bifidelity setup that captures the essence of a broad class of transport processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Soft Matter Thermal and Mechnical Devices

The participant company, Treau, makes homes and buildings more comfortable with quiet, energy efficient, and easy to install heating and cooling systems. They entered the Cyclotron Road program with an idea for a heat exchanger and compressor and a general idea that the building heating and cooling sector was the best first target market. While at Cyclotron Road, they used the Cyclotron Road program staff and Berkeley Lab expertise to better understand the needs of the heating and cooling equipment market. This was critical to understand who the end customer was, and what features were needed in this market. They were then able to conduct product development with this target market/customer in mind. The Cyclotron Road program was also critical in building a manufacturing and scale-up plan that allowed the participant to build a credible growth and fundraising strategy. By the end of the program, the participant had a working prototype testing at Berkeley Lab’s HVAC testing facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Engineering microalgal cell wall-anchored proteins using GP1 PPSPX motifs and releasing with intein-mediated fusion

AbstractHarnessing and controlling the localization of recombinant proteins is critical for advancing applications in synthetic biology, industrial biotechnology, and drug delivery. This study explores protein anchoring and controlled release inChlamydomonas reinhardtii, providing innovative tools for these fields. Using truncated variants of the GP1 glycoprotein fused to the plastic-degrading enzyme PHL7, we identified the PPSPX motif as essential for anchoring proteins to the cell wall. Constructs with increased PPSPX content exhibited reduced secretion but improved anchoring, pinpointing the potential anchor-signal sites of GP1 and highlighting the distinct roles of these motifs in protein localization. Building on the anchoring capabilities established with these glycomodules, we also demonstrated a controlled release system using a pH-sensitive intein derived from RecA fromMycobacterium tuberculosis. This intein efficiently cleaved and released PHL7 and mCherry that was fused to GP1 under acidic conditions, enabling precise temporal and environmental control. At pH 5.5, fluorescence kinetics demonstrated significant mCherry release from the pJPW4mCherry construct within 4 hours. In contrast, release was minimal under pH 8.0 conditions and negligible for the pJPW2mCherry (W2) control, irrespective of the pH. Additionally, bands on the Western blot at the expected size of mCherry also showed its efficient release from the mCherry::intein::GP1 fusion protein at pH 5.5. Conversely, at pH 8.0, no bands were detected. This anchor-release approach offers significant potential for drug delivery, biocatalysis, and environmental monitoring applications. By integrating glycomodules and pH-sensitive inteins, this study establishes a versatile framework for optimizing protein localization and release inC. reinhardtii, with broad implications for proteomics, biofilm engineering, and scalable therapeutic delivery systems.Graphical Abstract

Kang, Kalisa (ORCID:0009000619398129)↗
DOE OSTI2025

Building High-Energy Silicon-Containing Batteries Using Off-The-Shelf Materials

The technology of silicon anodes appears to be reaching maturity, with high-energy Si cells already in pilot-scale production. However, the performance of these systems can be difficult to replicate in academic settings, making it challenging to translate research findings into solutions that can be implemented by the battery industry. Part of this difficulty arises from the lack of access to engineered Si particles and anodes, as electrode formulations and the materials themselves have become valuable intellectual property for emerging companies. Here, we summarize the efforts by Argonne’s Cell Analysis, Modeling, and Prototyping (CAMP) Facility in developing Si-based prototypes made entirely from commercially available materials. We describe the many challenges we encountered when testing high-loading electrodes (>5 mAh cm −2 ) and discuss strategies to mitigate them. With the right electrode and electrolyte design, we show that our pouch cells containing ≥ 70 wt% SiO x can achieve 600–1,000 cycles at C/3 and meet projected energy targets of 700 Wh L −1 and 350 Wh kg −1 . These results provide a practical reference for research teams seeking to advance silicon-anode development using accessible materials.

25 ENERGY STORAGE↗
DOE OSTI2026

Algebraic Multigrid with Filtering: An Efficient Preconditioner for Interior Point Methods in Large-Scale Contact Mechanics Optimization

Large-scale contact mechanics simulations are crucial in many engineering fields such as structural design and manufacturing. In the frictionless case, contact can be modeled by minimizing an energy functional; however, these problems are often nonlinear, nonconvex, and increasingly difficult to solve as mesh resolution increases. In this work, we employ a Newton-based interior-point (IP) filter line-search method, an effective approach for large-scale constrained optimization. While this method converges rapidly, each iteration requires solving a large saddle-point linear system that becomes ill-conditioned as the optimization process converges, largely due to IP treatment of the contact constraints. Such ill-conditioning can hinder solver scalability and increase iteration counts with mesh refinement. Here, to address this, we introduce a novel preconditioner, algebraic multigrid with filtering (AMGF), tailored to the Schur complement of the saddle-point system. Building on the classical AMG solver, commonly used for elasticity, we augment it with a specialized subspace correction that filters near null space components introduced by contact interface constraints. Through theoretical analysis and numerical experiments on a range of linear and nonlinear contact problems, we demonstrate that the proposed solver achieves mesh independent convergence and maintains robustness against the ill-conditioning that notoriously plagues IP methods. These results indicate that AMGF makes contact mechanics simulations more tractable and broadens the applicability of Newton-based IP methods in challenging engineering scenarios. More broadly, AMGF is well suited for problems, optimization or otherwise, where solver performance is limited by a low-dimensional subspace, such as those arising from localized constraints, interface conditions, or model heterogeneities. This makes the method widely applicable beyond contact mechanics and constrained optimization.

Mathematics and Computing↗
DOE OSTI2024

A multiphase flow model of water droplets dielectrophoretic-induced air dehumidification phenomena

Air humidity in indoor spaces plays a critical role in human comfort and health. Dehumidification systems are used for building humidity controls, but they can take significant energy consumption, especially in geographic locations with high outdoor humidity and warm climates. Consequently, there is a growing demand for innovative dehumidification processes that consume minimal energy. Dielectrophoretic air dehumidification represents one such promising approach. However, it has not garnered significant attention due to the absence of engineering models and simulation tools capable of evaluating its performance and limitations at large-scale airflows. A new numerical multiphase CFD model, which is also experimentally validated, is developed in a customized Reacting Foam solver based on OpenFOAM® version 9. The newly developed model seeks to decrease substantial energy consumption and lower costs by leveraging the dielectrophoretic phenomenon to regulate moisture levels in the air. The solver integrates a hybrid Eulerian-Lagrangian framework to track the droplet's trajectory and growth rate while solving the continuum equations for the moist air. An electrospray produces electrically charged droplets, which grow during their in-flight trajectories as water vapor condenses onto their surfaces. The role of electrostatic forces in promoting vapor condensation within a high-gradient electrical field is investigated, and the dielectrophoretic vapor nucleation process on charged water droplets is discussed. The CFD model was validated against results from the literature and from proof-of-concept experiments conducted by the authors, which showed a 2 % air dehumidification with a single electrospray and airflow rate of 5 cubic feet per minute. The simulation results indicated that augmenting the number of electrically charged spray droplets increased the dehumidification of the air to 25 %. The initial mean droplet diameter, the orientation of the injector and relative humidity significantly influence the assessment of dehumidification. As a result, scaling up this approach to larger airflow volumes is identified as a potential future research direction.

42 ENGINEERING↗
DOE OSTI2025

Practical Introduction to Benchmarking and Characterization of Quantum Computers

Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. These remarkable achievements have been facilitated by advances in quantum characterization, verification, and validation (QCVV). QCVV methods and protocols enable scientists and engineers to scrutinize, understand, and enhance the performance of quantum information-processing devices. In this tutorial, we review the fundamental principles underpinning QCVV, and introduce a diverse array of QCVV tools used by quantum researchers. We define and explain QCVV’s core models and concepts—quantum states, measurements, and processes—and illustrate how these building blocks are leveraged to examine a target system or operation. We survey and introduce protocols ranging from simple qubit characterization to advanced benchmarking methods. Along the way, we provide illustrated examples and detailed descriptions of the protocols, highlight the advantages and disadvantages of each, and discuss their potential scalability to future large-scale quantum computers. This tutorial serves as a guidebook for researchers unfamiliar with the benchmarking and characterization of quantum computers, and also as a detailed reference for experienced practitioners.

open quantum systems & decoherence↗
DOE OSTI2020

First Look West (FLoW 2.0) (Final Technical Report for Closeout)

DOE’s Cleantech UP was an annual business plan competition, operating nationally between 2015 and 2018 through eight regional nodes that included Caltech’s FLOW. Cleantech UP focused on supporting university students at all levels creating cleantech startups. FLOW operated nationally with a focus on California. In support of the DOE’s objectives FLOW developed an immersive five point program that targeted major gaps in the educational support and practical resources available to scientists and engineers starting their first cleantech companies that prevented such young innovators from becoming entrepreneurs. Specifically, the FLOW program augmented the number of participants entering the energy entrepreneurship pipeline via the Cleantech UP competition; helped the US remain competitive by increasing the viability and financing potential of these cleantech companies started by young academics; and helped build the regional, state and national infrastructure that spurs and supports entrepreneurship. Each year the FLOW featured two major judging rounds for candidates drawn from as many as 80 applicants annually, providing essential experience and feedback that helped define the direction of these young entrepreneurs. The FLOW winners competed at the DOE’s national event, and FLOW companies took the top prize twice in the total history of the DOE program which was started in 2011.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

PIPII cryoplant non thermal cycling updates

The Proton Improvement Plan-II (PIP-II) is a crucial upgrade to the Fermilab accelerator complex, featuring a new 800-MeV Superconducting Radio-Frequency (SRF) linear accelerator (LINAC) with 23 cryomodules operating at 2K. The LINAC thermohydraulic conditions are satisfied by the cryogenic subsystems: Cryogenic Distribution System (CDS), a helium refrigerator cold box (CB), a warm compression station (WCS) and a helium recovery system (RSYS). The accelerator has a strict requirement of non-thermal cycling of the LINAC cryomodules during planned and unplanned subsystem outages. This paper presents an integrated operating modes analysis of the of the LINAC/CDS thermohydraulic loads satisfied by the CB/WCS cooling system supported by the RSYS inventory management system. The study is based on latest cryoplant and CDS engineering deliverables, as well as the recent performance data from single cryomodule qualification tests performed at the Fermilab PIP-II Injector Test test s tand. The study evaluates both normal and abnormal operating modes, with a focus on identifying integrated scenarios that put subsystems components under stress. The conclusions of this study will help build redundancy to reduce the risk of thermal cycles during planned and unplanned subsystem outages.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Global Evaluation of Process Conditions and Wave Modes in a Rotating Detonation Engine

Rotating Detonation Engines (RDEs) show significant promise for enhancing the efficiency of gas turbine engines while maintaining low 𝑁𝑂𝑥 emissions. This work investigates the predictability of wave modes in a water-cooled RDE under varying operational conditions. Experimental data comprising over 6,700 samples was collected, including parameters such as flow rates, temperatures, pressures, and equivalence ratios. A machine learning approach using the XGBoost library was used to build a multi-class classifier, predicting wave modes based on these inputs. The model achieved a high accuracy of 97%, demonstrating that wave modes are not random but deterministic based on the process conditions. SHAP analysis was used to identify the most influential parameters affecting wave mode prediction. The results show that for the water-cooled NETL RDE, wave mode is determinant and predictable based on the process parameters.

Weber, Justin [NETL] (ORCID:0000000218487035)↗
DOE OSTI2021

A Markov framework for generalized post-event systems recovery modeling: From single to multihazards

State-dependent models can be used to represent the system recovery process as a series of stochastic transitions from lower to higher functional states. However, the applications of these models have been limited in scope and there is a lack of a generalized recovery modeling framework. A generalized framework would permit a robust forecasting of systems and system-of-systems recovery under multiple hazards, and more broadly, would contribute to community disaster preparedness. This paper develops a generalized post hazard-event recovery modeling framework based on state-dependent Markov-type processes. We then apply the proposed framework to solve a spectrum of problems that range from hind-casting single-system recovery following a single hazard event to forecasting post-event trajectories under multiple hazards and modeling the recovery of a system-of-systems. First, Markov chains are used to hind-cast the observed recovery for a portfolio of buildings affected by the 2014 South Napa, California, earthquake. Next, Markov processes are used to formulate a parametric post hazard-event recovery model, which can be updated using Bayesian statistics when relevant datasets become available. Semi-Markov processes are then used to develop a more general model of single hazard recovery, which accounts for the intensity of the loading and level of damage caused by the event. Semi-Markov processes with non-renewal features are then used to account for multihazard interactions in a post-event recovery model, and applied to a case study that involves a community in Charleston, South Carolina. Lastly, Markov-type processes are combined with Bayesian networks to model the recovery of residential, commercial, educational, and industrial buildings (system-of-systems) following a hazard event. Overall, these applications demonstrate the versatility of the Markov framework towards handling recovery problems with varying levels of complexity.

42 ENGINEERING↗
DOE OSTI2021

Evaluation of Engineered Barrier Systems FY21 Report

This report describes research and development (R&D) activities conducted during fiscal year 2021 (FY21) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel and Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Energy (DOE). The R&D activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. A primary goal is to advance the development of process models that can be implemented directly within the Generic Disposal System Analysis (GDSA) platform or that can contribute to the safety case in some manner such as building confidence, providing further insight into the processes being modeled, establishing better constraints on barrier performance, etc.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review

Sensors are the key information source for fault detection and diagnostics (FDD) in buildings. However, sensors are often not properly designed, installed, calibrated, located, and maintained, which negatively impacts FDD performance. Several sensor-related FDD topics have been widely studied, covering a wide range of fault types and applications. However, it is difficult to get a clear picture of the technical development of sensor-related topics in FDD. A systematic review of sensor topics is needed to summarize the existing research in a logical way, draw conclusions on the current development, and predict the future development of sensors in building FDD. To address this gap, we conducted a comprehensive literature review of more than 100 FDD-sensor-related papers. In this article, we subdivide the FDD tasks into building-level, system-level, and component-level FDD, and review sensor-related topics in each category. Our major conclusions are: (a) current data-driven FDD research focuses more on FDD algorithms than sensors, (b) sensor “hardware” research topics are less studied than sensor “software” topics, (c) very few papers focus on sensor engineering as an integral aspect of FDD development, and (d) some important sensor topics, such as sensor cost-effectiveness and sensor schema/layout/location, are not well studied. Finally, we discuss the need for a systematic framework of FDD sensors and models to integrate sensor design/selection, sensor data analysis/mining, feature selection, physics-based or data-driven algorithm development, sensor fault detection, sensor calibration, and sensor maintenance. Finally, expert interviews are conducted to validate the above findings and conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Scalable modular dynamic molten salt reactor system model with decay heat

Nodal dynamic models allow rapid reduced-order simulations of complex systems. This paper presents a publicly available system dynamic model of a molten salt reactor system with a topology of the Molten Salt Reactor Experiment (MSRE), in MATLAB/Simulink, building upon a model previously published and validated with MSRE data. It adds scaling of nominal power, dynamic representation of decay heat generation, a generic decay heat removal system, improved documentation, modularity, and test cases. One hour of system transient runs in less than 10 min on a laptop. This model is intended for first order engineering calculations, developing insights into system transient behavior, equipment sizing, parameter sensitivity studies. The model contains an easy to use toolkit which can be customized and expanded to describe any molten salt reactor system. Finally, scenarios involving off-normal transients are presented. Relation between shutdown reactivity insertions, decay heat removal, core recriticality, and safe shutdown conditions are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Structure–Thermodynamic Relationship of a Polysaccharide Gel (Alginate) as a Function of Water Content and Counterion Type (Na vs Ca)

Biofilms are the predominant mode of microbial life on Earth, and so a deep understanding of microbial communities-and their impacts on environmental processes-requires a firm understanding of biofilm properties. Because of the importance of biofilms to their microbial inhabitants, microbes have evolved different ways of engineering and reconfiguring the matrix of extracellular polymeric substances (EPS) that constitute the main non-living component of biofilms. This ability makes it difficult to distinguish between the biotic and abiotic origins of biofilm properties. An important route toward establishing this distinction has been the study of simplified models of the EPS matrix. This study builds on such efforts by using atomistic simulations to predict the nanoscale (≤10 nm scale) structure of a model EPS matrix and the sensitivity of this structure to interpolymer interactions and water content. To accomplish this, we use replica exchange molecular dynamics (REMD) simulations to generate all-atom configurations of ten 3.4 kDa alginate polymers at a range of water contents and Ca–Na ratios. Simulated systems are solvated with explicitly modeled water molecules, which allows us to capture the discrete structure of the hydrating water and to examine the thermodynamic stability of water in the gels as they are progressively dehydrated. Our primary findings are that (i) the structure of the hydrogels is highly sensitive to the identity of the charge-compensating cations, (ii) the thermodynamics of water within the gels (specific enthalpy and free energy) are, surprisingly, only weakly sensitive to cation identity, and (iii) predictions of the differential enthalpy and free energy of hydration include a short-ranged enthalpic term that promotes hydration and a longer-ranged (presumably entropic) term that promotes dehydration, where short and long ranges refer to distances shorter or longer than ~0.6 nm between alginate strands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

pypolymix

SAND2026-16700O Pypolymix builds stochastic surrogate models using a lightweight Python library. Researchers working with large-scale scientific models can use it to enhance optimization and uncertainty quantification studies. Pypolymix enables the efficient construction of surrogate models and improves analysis and performance of complex simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗