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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Retrofitting stoves with forced jets of primary air improves speed, emissions, and efficiency: Evidence from six types of biomass cookstoves

Incorporating jets of forced air into biomass cookstove combustion has been shown to potentially decrease harmful emissions, leading to a variety of designs in recent years. These have shown mixed success in terms of real-world performance, usability, and durability. The Jet-Flame forced draft retrofit accessory was recently developed to implement forced jets of primary air at a low cost into a wide range of types of cookstoves using a small 1.5-W fan housed in a low-cost cast iron body to be inserted beneath the fuel bed of a biomass cooking fire. This research sought to quantify the potential efficiency and emissions performance impacts of the Jet-Flame when installed in six different types of biomass cookstoves (three open or shielded fires and three rocket stoves) versus the natural draft performance of each. The effect of the operating fan voltage was also measured. A series of tests following a modified ISO 19867-1:2018 protocol were performed in the laboratory using the Aprovecho Laboratory Emissions Measurement System (LEMS) equipped with additional oxygen and temperature sensors. Results for each stove carefully tended with a single layer of sticks showed that the global average PM 2.5 reduction with the Jet-Flame was 89 % relative to the natural draft cases, with larger relative improvements seen in the most rudimentary stoves. CO was reduced by a global average of 74 %, reaching tier 4 or 5 for all stoves. Thermal efficiency was also improved by 34 % when calculated without taking into account the energy content of the remaining char (or 21 % with char), illustrating the value of burning char to provide cooking energy rather than leaving it unburned in the combustion chamber as is common in many natural draft stoves. Time to boil was also reduced by 8 %. In addition, adjusting the voltage of the jet-flame assisted in modulating firepower, improving the usability of the stove. These results indicate a strong potential for the Jet-Flame to help reduce emissions and fuel consumption in a wide range of cookstove designs at a relatively low cost or need for changes in behavior, fuel, or cooking device. The unit also provides enhanced usability in terms of ease of startup, cooking speed, low PM emissions at high power, and burning char. Additional studies are needed to measure performance in the field and under a variety of operational conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Robust hierarchical three dimensional nickel cobalt tungstate-MXene nanocomposite for high performance symmetric coin cell supercapacitors

Design of rational electrode materials with hierarchically structured pseudocapacitive materials has been identified as a successful strategy for revamping the electrochemical characteristics of supercapacitors. However, the simultaneous assurance of strong electrical conductivity and higher specific capacitance via a simple and cost-effective synthesis protocol is of concern today. In this work, Ni-CoWO 4 incorporated MXene nanocomposite has been successfully prepared by a facile hydrothermal process. The structure, morphology, stoichiometry, and chemical characterization of the prepared Ni-CoWO 4 , Ti 3 C 2 T x , and Ni-CoWO4@MXene nanocomposite were explored extensively. MXene demonstrated a layered 2D nanoscale structure whereas pure Ni-CoWO 4 was composed of spherical nanoparticles. The composite Ni-CoWO 4 @MXene revealed the morphology of spherical Ni-CoWO 4 nanoparticles decorated on MXene sheets. Furthermore, a series of electrochemical characterizations illustrated the contribution of the delightful morphology of Ni-CoWO 4 @MXene composite to excellent electrochemistry. The resultant Ni-CoWO 4 @MXene electrode exhibited high specific capacitance of 582 Fg -1 at 1 A g -1 and 93.5 % capacitance retention over the 10,000 cycles., which is higher than that of the individual counterparts Ni-CoWO 4 and MXene. The excellent electrochemical performance of Ni-CoWO 4 @MXene is attributed to the synergistic interaction between Ni-CoWO4 nanoparticles and nanolayered MXene that may create new active sites that enhanced the charge transfer, charge/discharge kinetics and the electrical conductivity. Significantly, the unique Ni-CoWO 4 @MXene supercapacitor prototype delivered a higher energy density of 85.7 Wh kg -1 and power density of 0.85 kW kg -1 establishing its superiority over other Cosingle bondW based supercapacitors. A theoretical study was also performed to correlate the improved charge storage capacity of the prepared Ni-CoWO 4 @MXene composite.

25 ENERGY STORAGE↗
DOE OSTI2023

Mechanically induced thermal runaway severity analysis for Li-ion batteries

Thermal runaway is one of the most important safety concerns in the deployment of Li-ion batteries. For this study, we developed a standardized single-side indentation test protocol to induce an internal short-circuit. Cell voltage, temperature, and applied compressive force are monitored as a function of time. Each cell is given an observed hazard severity (OHS in five categories) modified from the EUCAR table. Meanwhile a calculated hazard severity (CHS) is obtained solely based on temperature and voltage curves. The calculation formula considers the cell temperature, rate of temperature increase, cell capacity, state of charge (SOC), voltage drop, and voltage drop rate. Each term is assigned with an appropriate weight to scale the calculated score from 0 to100. This method was applied to >100 Li-ion batteries with various SOCs and chemistries, and their OHS and CHS were displayed against SOC. The purpose is to provide battery designers, manufacturers, and end-users a clear comparison of thermal runaway severity of different batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗
DOE OSTI2023

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Non-catalytic gas phase NO oxidation in the presence of decane

In this study, experiments without a catalyst revealed that NO was oxidized in a diesel exhaust gas phase mixture due to the presence of n -C 10 H 22 (decane). This reaction was observed to occur following the low temperature oxidation catalyst test protocol (LTC-D) defined by U.S. DRIVE. The purpose of LTC-D conditions is to simulate an aftertreatment diesel combustion gas mixture in order to test candidate catalyst materials. 100% NO conversion was observed, without a catalyst, after beginning to react at 330 °C accompanied by consumption of decane. After experiments that isolated hydrocarbons, ethylene was also observed to facilitate NO oxidation to a lesser degree (>470 °C). Density functional theory (DFT) calculations were conducted to investigate thermodynamically-possible initiating elementary steps during n -C 10 H 22 consumption and NO oxidation. Two feasible intermediate radicals to oxidize NO to NO 2 are ·C 10 H 21 O 2 and ·HO

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Gasoline fuels properties for multi-mode operation – Observations in a GDI and the CFR engine

The combustion behavior of five full boiling range RON98 gasoline blends was evaluated for multi-mode operation in a GDI and the CFR octane rating engine. The GDI engine tests were conducted with stoichiometric air-fuel ratio in spark-ignition (SI), and with air-diluted homogeneous charge compression ignition (HCCI) mode. In the CFR engine, the knocking combustion was analyzed under standard RON testing conditions at both peak knocking lambda and stoichiometric air-fuel ratios, whereas compression ignited operation was characterized by utilizing the HCCI number test protocol. Disparate knock limited SI and HCCI combustion behavior was observed for the test fuels, despite four of the fuels having the same RON and octane sensitivity. It was found that knock-limited combustion phasing in the GDI engine did not align well with the RON. However, a detailed comparison of knock-limited SI operation in the GDI and CFR engine revealed that a more appropriate effective RON based on a common knock intensity metric (MAPO) and stoichiometric air-fuel ratio resulted in comparable knock characterization between the two engine platforms. Furthermore, the critical intake air temperature and the critical compression ratio were proposed to characterize knock-limited SI operation, while the minimum intake air heating and compression ratio were used to define a fuel's autoignition propensity for compression ignition operation in the GDI and CFR engine, respectively. Finally, each fuel's characteristic compression ratio needed to obtain knock-limited SI (KLSI) and HCCI operation was used to calculate an effective multi-mode octane number (MM-ON) based on the primary reference fuel blends.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Opportunities and challenges in thermochemical conversion of municipal solid waste: A comprehensive review

Recent advancements in thermochemical conversion processes have elucidated new pathways for converting municipal solid waste into valuable resources. This review explores the primary thermochemical conversion methods, including combustion, gasification, pyrolysis, torrefaction, hydrothermal carbonization, and hydrothermal liquefaction, emphasizing their potential roles in waste management and energy recovery. Key challenges including feedstock variability, ash behavior, and scale-up limitations are discussed alongside opportunities for hybrid systems and circular economy integration. A comparative analysis of research publications indicates a significant focus on thermochemical pathways within the broader context of municipal solid waste research, underscoring the growing interest in these technologies. Recent advancements in each thermochemical process, alongside their operational, technical, and economic challenges, are discussed. Comparative data reveal that torrefaction enhances the hydrophobicity and grindability of municipal solid waste components, though its energy densification benefits are more modest than those observed in biomass. Hydrothermal carbonization and liquefaction are highlighted for their ability to process high-moisture and heterogeneous waste streams. The review also synthesizes recent findings on reactor configurations, emissions control, and synergistic effects in co-processing municipal solid waste fractions. The findings underscore the importance of developing standardized protocols for municipal solid waste characterization and the need for innovative hybrid systems to improve efficiency.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Preliminary proof-of-concept of real-time divertor heat flux control from infrared cameras with nitrogen injection in the DIII-D tokamak

In future tokamak reactors like ITER and the Fusion Pilot Plant (FPP), real-time feedback control of heat flux to the plasma-facing components (PFC) will be critical for steady-state operation. This work presents the first experimental demonstration of real-time divertor heat flux estimation with infrared thermography and feedback control with impurity seeding on the DIII-D tokamak. The flexible infrastructure of the Plasma Control System (PCS) on DIII-D makes this new capability possible. The PCS software runs on a gateway computer system, and five real-time compute nodes. An array of low latency streaming digitizers from D-TACQ Solutions connects to these real-time computers to collect and process data, and send commands to actuators during plasma discharges. This system handles the signal IO from the tokamak and allows the PCS to utilize the diagnostic data necessary to perform control in real-time. Feedback control on heat flux was accomplished by feeding infrared camera data from the “Infrared TV” (IRTV) camera to a custom-developed User Datagram Protocol (UDP) server. This server transmits infrared data to a newly developed PCS algorithm that estimates the heat flux to PFC. Here, a proportional integral derivative (PID) controller minimizes the error between a heat flux reference and the real-time estimate by injecting nitrogen gas into the divertor.

Algorithm development↗
DOE OSTI2023

Multi-site evaluation of stratified and balanced sampling of soil organic carbon stocks in agricultural fields

Estimating soil organic carbon (SOC) stocks in agricultural fields is essential for environmental and agronomic research, management, and policy. Stratified sampling is a classic strategy for estimating mean soil properties, and has recently been codified in SOC monitoring protocols. However, for the specific task of estimating the SOC stock of an agricultural field, concrete guidance is needed for which covariates to stratify on and how much stratification can improve estimation efficiency. It is also unknown how stratified sampling of SOC stocks compares to modern alternatives, notably doubly balanced sampling. To address these gaps, we collected high-density (average of 7 samples ha -1 ) and deep (average of 75 cm) measurements of SOC stocks at eight commercial fields under maize-soybean production in two US Midwestern states. We combined these measurements with a Bayesian geostatistical model to evaluate stratified and balanced sampling strategies that use a set of readily-available geographic, topographic, spectroscopic, and soil survey data. We examined the number of samples needed to achieve a given level of SOC stock estimation accuracy. While stratified sampling using these variables enables an average sample size reduction of 17% (95% CI, 11% to 23%) compared to simple random sampling, doubly balanced sampling is consistently more efficient, reducing sample sizes by 32% (95% CI, 25% to 37%). The data most important to these efficiency gains are a remotely-sensed SOC index, SSURGO estimates of SOC stocks, and the topographic wetness index. We conclude that in order to meet the urgent challenge of climate change, SOC stocks in agricultural fields could be more efficiently estimated by taking advantage of this readily-available data, especially with doubly balanced sampling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulating water dynamics related to pedogenesis across space and time: Implications for four-dimensional digital soil mapping

Digital soil mapping (DSM) relies on machine-learning and geostatistics to represent soil property observations across space. DSM techniques are powerful but often empirical, being limited to the quality and density of point samples. Water dynamics are closely related to soil variability, and the physics that govern water movement are well known. Hydrological properties can hence be simulated by physical models through space and time, unveiling key characteristics about soils. We propose the use of hydrologic models to map soils across the surface (2D), depth (1D), and time (1D)–which provides a 4D approach to digital soil mapping (4DSM). The Distributed Hydrology Soil Vegetation Model (DHSVM) was applied to a watershed currently under pasture. Moisture sensors and wells were installed at different depths in the watershed on summit, sideslope and toeslope positions to validate the model. DHSVM simulations of soil moisture distribution and depth to saturation were performed during the hydrological year (October 2008-September 2009). Clusters of similar pixels based on soil moisture values were determined using Dynamic Time Warping (DTW) to align temporal data and K-means. Clustering was performed both seasonally and for the entire year. Temporal patterns simulated by DHSVM matched measurements given by moisture sensors and wells. Seasonal clusters differed from the annual cluster. Distinct clusters were observed for each season and with depth, showing that spatiotemporal soil variability is lost when statically assessing soils. Spatiotemporal clusters corroborated field observations of fragipan occurrence not explicitly spatially mapped by Soil Survey Geographic Database (SSURGO). If a connection can be made between water and soils, static and dynamic soil variability can be predicted using physically based hydrologic models. Hydrologic models can benefit soil mapping by enabling reliable 4D simulation of water dynamics, which are fundamental to soil variability and soil classification and directly relate to biological, physical and chemical soil processes not captured by typical soil sampling protocols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

From lab to table: Expanding gastronomic possibilities with fermentation using the edible fungus Neurospora intermedia

Fermentation is a powerful tool for enhancing flavor, improving sustainability, and expanding creative possibilities in the kitchen. However, most fermentations done in gastronomic contexts are restricted to a small set of readily available microbial species. Expanding beyond this limited biological diversity holds promise to unlock new gastronomic innovation. Here, we explore novel culinary applications of Neurospora intermedia, an edible fungus traditionally used in Java, Indonesia to produce the fermented food oncom. Our work demonstrates that N. intermedia can be readily used in the production of oncom-like meat alternatives with non-traditional substrates, as well as in the production of enzymes for starch-to-sugar conversion. As an example, we harness secreted N. intermedia starch-degrading enzymes to produce an amazake that has a distinct volatile aroma composition compared to traditional amazake produced with Aspergillus oryzae. In addition to providing texture and flavor, N. intermedia can be used to add an orange color to dishes due to the development of brightly colored spores and aerial mycelia. This property, along with its secreted enzymes, was utilized to create a dish for fine-dining restaurant Alchemist in Copenhagen, Denmark. Overall, the novel foods produced in this study were rated favorably in consumer trials, indicating a broad sensory appeal of N. intermedia across different culinary applications and cultural contexts. The protocols and approaches presented in this study represent a new addition to the chef's toolbox that hold promise to expand gastronomic possibilities with fermentation in restaurants and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A comprehensive techno-eco-assessment of CO 2 enhanced oil recovery projects using a machine-learning assisted workflow

Carbon dioxide enhanced oil recovery (CO 2 -EOR) projects not only extract residual oil but also sequestrate CO 2 in the depleted reservoirs. Here, this study develops a machine-learning-based workflow to co-optimize the hydrocarbon recovery, CO 2 sequestration volume and project net present value (NPV) simultaneously. Considering the trade-off relationships among the objective functions, support vector regression with Gaussian kernel (Gaussian- SVR) proxies are coupled with multi-objective particle swarm optimization (PSO) protocol and generate Pareto optimal solutions. Taking advantage of the high computational efficacy of the proxy model, economic uncertainties introduced by tax credits, capital costs and oil price are investigated by this study. The results indicate that the tax incentive policy (Section 45Q) plays a vital role in enhancing the economic returns of CO 2 -EOR projects, especially under the depression of crude oil market. The proposed workflow has been successfully implemented to optimize a water alternative CO 2 (CO 2 -WAG) injection project in a depleted oil sand in the US. The optimization results yield an incremental oil production of 15.8 MM STB and 1.37 MM metric tons of CO 2 storage in a 20-year development strategy, with the highest project NPV to be 205.6 MM US dollars.

03 NATURAL GAS↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
DOE OSTI2020

Macrovoid-free high performance polybenzimidazole hollow fiber membranes for elevated temperature H 2 /CO 2 separations

Thermally robust membranes are required for H 2 production and carbon capture from hydrocarbon fuel derived synthesis (syn) gas. Polybenzimidaole (PBI) materials have exceptional thermal, chemical and mechanical characteristics and high H 2 perm-selectivity for efficient syngas separations at process relevant conditions. The large gas volumes processed mandate the use of a high-throughput, small footprint hollow fiber membrane (HFM) platform. Here in this work, an industrially attractive spinning protocol is developed to fabricate PBI HFMs with unprecedented H 2 /CO 2 separation performance. A unique dope composition incorporating an acetonitrile diluent is discovered enabling asymmetric macro-void free PBI HFM fabrication using a water coagulant. The influences of dope viscosity, coagulant chemistry, and air gap on HFM morphology are evaluated. Elevated temperature (up to 350 °C) H 2 permeances of 400 GPU with H 2 /CO 2 selectivities > 20 are achieved. This unprecedented separation performance is a ground breaking achievement at temperatures traditionally considered out-of-reach for polymeric membranes.

08 HYDROGEN↗
DOE OSTI2026

Application of trichloroacetimidate-mediated benzylation to the detection of pinacolyl methylphosphonic acid in standardised proficiency test matrices

Here, a procedure for the qualitative analysis of pinacolyl methylphosphonic acid (PMPA), a degradation product from the nerve agent Soman (GD), is presented. The protocol involves the derivatization of PMPA with benzyl trichloroacetimidate resulting in its benzylation under neutral conditions, a desirable attribute in the presence of other base-sensitive analytes. The method was found to perform well in the detection of this Schedule 2 chemical, spiked at low concentrations, in three different test matrices, two soils and one liquid, featured in different Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency tests.

Chemistry↗