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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Discrimination of phosgene from cyanogen chloride in recovered chemical munitions using tagged neutron interrogation with high-resolution gamma-ray spectroscopy

The Associated Particle technique has recently been utilized with a germanium-based high-resolution $\gamma$-ray spectrometer and assessed for its capability to improve field identification of recovered chemical warfare (CW) materiel through prompt gamma-ray neutron activation analysis (PGNAA) measurements. An accurate chemical identification is necessary for the safe handling, destruction, and disposal of such hazardous items. A particularly challenging pair of CW agents commonly found in recovered munitions are phosgene (CG) and cyanogen chloride (CK), which have two of three elements in common, i.e. chlorine and carbon, but differ in the third being either oxygen or nitrogen. The detection of both latter elements is complicated by high oxygen concentration in the field environment which interferes with the small signal produced from the chemical agents. The matter is further complicated by the precautionary field practice of overpacking recovered munitions with vermiculite in larger steel multiple round containers (MRCs), which places additional oxygen-rich material around the munition while further attenuating an already weak signal emitted from the munition center. Here, this work reports quantitative results from realistic field measurements of CG and CK simulants in mock 4.2-inch mortar rounds overpacked with vermiculite in a large MRC. Results obtained with the AP technique are compared to those obtained with the traditional PGNAA approach for both overpacked- and bare-munition measurements. The AP technique is shown to provide a much more confident discrimination between the two chemicals, particularly for the more challenging field-relevant overpacked measurements, where a significant gain in sensitivity to all the key elements chlorine, carbon, nitrogen and oxygen is achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Reinforcement Learning for feedback-enabled cyber resilience

The rapid growth in the number of devices and their connectivity has enlarged the attack surface and made cyber systems more vulnerable. As attackers become increasingly sophisticated and resourceful, mere reliance on traditional cyber protection, such as intrusion detection, firewalls, and encryption, is insufficient to secure the cyber systems. Cyber resilience provides a new security paradigm that complements inadequate protection with resilience mechanisms. A Cyber-Resilient Mechanism (CRM) adapts to the known or zero-day threats and uncertainties in real-time and strategically responds to them to maintain the critical functions of the cyber systems in the event of successful attacks. Feedback architectures play a pivotal role in enabling the online sensing, reasoning, and actuation process of the CRM. Reinforcement Learning (RL) is an important gathering of algorithms that epitomize the feedback architectures for cyber resilience. It allows the CRM to provide dynamic and sequential responses to attacks with limited or without prior knowledge of the environment and the attacker. In this work, we review the literature on RL for cyber resilience and discuss the cyber-resilient defenses against three major types of vulnerabilities, i.e., posture-related, information-related, and human-related vulnerabilities. Here we introduce moving target defense, defensive cyber deception, and assistive human security technologies as three application domains of CRMs to elaborate on their designs. The RL algorithms also have vulnerabilities themselves. We explain the major vulnerabilities of RL and present develop several attack models where the attacker target the information exchanged between the environment and the agent: the rewards, the state observations, and the action commands. We show that the attacker can trick the RL agent into learning a nefarious policy with minimum attacking effort. The paper introduces several defense methods to secure the RL-enabled systems from these attacks. However, there is still a lack of works that focuses on the defensive mechanisms for RL-enabled systems. Last but not least, we discuss the future challenges of RL for cyber security and resilience and emerging applications of RL-based CRMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mitocans induce lipid flip-flop and permeabilize the membrane to signal apoptosis

Pancratistatin (PST) and narciclasine (NRC) are natural therapeutic agents that exhibit specificity toward the mitochondria of cancerous cells and initiate apoptosis. Unlike traditional cancer therapeutic agents, PST and NRC are effective, targeted, and have limited adverse effects on neighboring healthy, noncancerous cells. Currently, the mechanistic pathway of action for PST and NRC remains elusive, which in part inhibits PST and NRC from becoming efficacious therapeutic alternatives. Herein, we use neutron and x-ray scattering in combination with calcein leakage assays to characterize the effects of PST, NRC, and tamoxifen (TAM) on a biomimetic model membrane. We report an increase in lipid flip-flop half-times (t 1/2 ) (≈12.0%, ≈35.1%, and a decrease of ≈45.7%) with 2 mol percent PST, NRC, and TAM respectively. An increase in bilayer thickness (≈6.3%, ≈7.8%, and ≈7.8%) with 2 mol percent PST, NRC, and TAM, respectively, was also observed. Lastly, increases in membrane leakage (≈31.7%, ≈37.0%, and ≈34.4%) with 2 mol percent PST, NRC, and TAM, respectively, were seen. Considering the maintenance of an asymmetric lipid composition across the outer mitochondrial membrane (OMM) is crucial to eukaryotic cellular homeostasis and survival, our results suggest PST and NRC may play a role in disrupting the native distribution of lipids within the OMM. A possible mechanism of action for PST- and NRC-induced mitochondrial apoptosis is proposed via the redistribution of the native OMM lipid organization and through OMM permeabilization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Overexpression of a gibberellin 20-oxidase gene in poplar xylem led to an increase in the size of nanocellulose fibrils and improved paper properties

Cellulose, the major component of secondary cell walls, is the most abundant renewable long-chain polymer on earth. Nanocellulose has become a prominent nano-reinforcement agent for polymer matrices in various industries. We report the generation of transgenic hybrid poplar overexpressing the Arabidopsis gibberellin 20-oxidase1 gene driven by a xylem-specific promoter to increase gibberellin (GA) biosynthesis in wood. X-ray diffraction (XRD) and sum frequency generation spectroscopic (SFG) analyses showed that cellulose in transgenic trees was less crystalline, but the crystal size was larger. The nanocellulose fibrils prepared from transgenic wood had an increased size compared to those from wild type. When such fibrils were used as a reinforcing agent in sheet paper preparation, the mechanical strength of the paper was significantly enhanced. Engineering the GA pathway can therefore affect nanocellulose properties, providing a new strategy for expanding nanocellulose applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗
DOE OSTI2023

Electricity-driven recycling of ester plastics using one-electron electro-organocatalysis

Here, we report the catalytic use of electrochemically generated one-electron reducing agents to produce ester anion radicals that can decompose to acids and alcohols in the presence of oxygen. Through this approach, we demonstrate that molecular analogs of polyethylene terephthalate (PET) can be deconstructed into their molecular components. We additionally show efficient reductive scission of ester bonds in PET plastic using catalytically regenerated reducing agents based on benzimidazolium cations.

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

A transcriptional relationship with a natural product disrupts mitochondrial biogenesis

Discovery of new compound leads and oncology targets to treat cancer will require overcoming resistance to traditional therapies such as BRAF and mitogen-activated protein kinase inhibitors (MAPKi). In addition, potent new therapies will benefit from selective localization at the cancer site rather than general cell toxicity which can lead to undesired side effects. This selectivity can be gained by identifying new compound leads that are “prodrugs”, that is they are activated by mechanisms selective to cancer cells leading to strong pharmacological activity (Zhang, 2017). Continuing discovery of anticancer agents that overcome resistance and take advantage of cancer cell mechanisms will be greatly augmented by returning to the potent well of natural products; in fact, an analysis of a 70-year period ending in 2014 showed that nearly 50% of approved anticancer drugs are or are derived from natural products (Newman, 2016). Discovery of new agents with high potency and selectivity will require natural product research focused on discovering biologically active compounds with unique structures and mechanisms of action that utilize target cell functions.

Wright, Aaron T.↗
DOE OSTI2021

Ni(OH) 2 -free NiCu as a hydrogen evolution and oxidation electrocatalyst

In this work, we investigate the role of the nickel surface oxidation and the use of additional reducing agent in the synthesis process in the electrochemical activity of NiCu electrocatalysts for hydrogen oxidation reaction and hydrogen evolution reaction. In addition, the role of the carbon support morphology is also investigated: two different supports, DENKA black and Ketjenblack with widely different properties (specific surface, proportion of low strain carbons, etc.) are studied, and no difference are observed in their electrochemical activity. However, the use 4-aminoantipyrine as a reducing agent resulted in a dramatic increase in non-oxidized Ni at the electrocatalyst’ surface, concomitant to a large increase in its activity for both the hydrogen evolution and oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effect of crystallite size on lithium storage performance of high entropy oxide (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 nanoparticles

High-entropy oxides (HEOs), known for their high theoretical capacity and structural stability, are considered promising anode materials for next-generation lithium-ion batteries (LIBs). In this research, we synthesized a novel spinel-type HEO, (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 , using a solution combustion method. By adjusting the quantity of the combustion agent, we produced samples with varying crystallite sizes. The crystallite size of the HEOs initially enlarges with an increased combustion agent, then diminishes. The enhancement of crystallite size correlates with improved electrochemical performance for lithium storage. Notably, the (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 nanoparticles, with the largest crystallite size of 36.3 nm, demonstrated a reversible capacity of 343 mA h g -1 after 100 cycles at 100 mA g -1 , a capacity retention to 319 mA h g -1 after 1000 cycles at 1 A g -1 , and a commendable rate capability of 260 mA h g -1 at 2 A g -1 . Furthermore, this study underscores the pivotal role of crystallite size in LIB performance and presents a viable strategy to enhance the lithium storage capabilities of HEOs and other metal oxides.

25 ENERGY STORAGE↗
DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Efficient separation and coprecipitation for simplified cathode recycling

Hydrometallurgical recycling of spent lithium-ion batteries is among the most promising recovery approaches. The current hydrometallurgical method for battery recycling faces challenges such as complex separation and precipitation processes, and environmental concerns from the use of caustic inorganic acid and hazardous hydrogen peroxide. Our proposed modified method, namely polyol-metallurgy, uses citric acid in ethylene glycol as dual-function green solution to overcome these obstacles. This bifunctional solution leaches valuable metal ions from cathode materials (e.g., LiCoO 2 ), and then acts as chelating agents to selectively precipitate cobalt through an esterification reaction, without the need for additional precipitation agents. The leaching efficiency of cobalt and lithium reaches 99.55% and 97.65%, respectively, and more than 96% of cobalt could be directly self-precipitated and recovered. Further, the unique characteristics of the dual-function solution also avoids impurities from Al foils and PVDF/carbon black films, enabling the simple separation process. Therefore, the process can be completed in one-pot system with efficient leaching, separation and coprecipitation, making it more efficient and feasible for operation than existing alternatives.

25 ENERGY STORAGE↗
DOE OSTI2022

Enhanced Oblique Decision Tree Enabled Policy Extraction for Deep Reinforcement Learning in Power System Emergency Control

Deep reinforcement learning (DRL) algorithms have successfully solved many challenging problems in various power system control scenarios. However, their decision-making process is usually regarded as black-boxes. Furthermore, how DRL models interact with human intelligence remains an open problem. Thus, this paper proposes a policy extraction framework to extract a complex DRL model into an explainable policy. This framework includes three parts: 1) DRL training and data generation. We train an agent for a specific control task and generate data, which contains the control policy of the agent. 2) Policy extraction. We propose an information gain rate based weighted oblique decision tree (IGR-WODT) for DRL policy extraction. 3) Policy evaluation. We define three metrics to evaluate the performance of the proposed approach. A case study for the under-voltage load shedding problem shows that the IGR-WODT presents a performance enhancement compared with DRL, weighted oblique decision tree, and univariate decision tree. The proposed policy extraction method could provide an intuitive explanation of the neural network decision-making process to the dispatchers when making final decisions on power grid operation. Also, the resulted rule-based controller could replace the deep neural network-based controller in many field edge devices with limited computing resources, providing comparable performance.

deep reinforcement learning↗
DOE OSTI2024

Stabilizing a low temperature phase change material based on Glaubers salt

The aim of this research is to enhance the performance of Glauber's salt (sodium sulfate decahydrate, SSD) as a phase change material (PCM) for thermal energy storage applications, as well as for shipping of temperature-sensitive materials. The study investigates the effects of modifying SSD with potassium chloride (KCl) and ammonium chloride (NH 4 Cl) to achieve lower phase transition temperatures of between +6 °C and + 13 °C. Sodium polyacrylate (PAAS) is employed as a thickening agent to prevent phase separation, and borax is used as a nucleating agent to suppress supercooling. Various ratios of KCl:NH 4 Cl are tested, and the impact of PAAS concentration on phase segregation is explored. The results show that a 2 wt% concentration of PAAS effectively prevents phase separation. Samples with a KCl:NH 4 Cl ratio of 1:1.83 exhibit stable phase transition behavior and maintain latent heat values within the range of 130–140 J/g after 30 thermal cycles. Maintaining a total KCl and NH 4 Cl proportion of 10 wt% is crucial to achieve the desired lower melting temperature. As a result, the study highlights the significance of thermal cycling in improving the stability of the PCM. The optimized SSD-based eutectic PCM formulations hold promise for applications in the cold chain industry.

25 ENERGY STORAGE↗
DOE OSTI2023

Methane foam performance in oil-wet unconsolidated porous media: A systematic experimental investigation at reservoir conditions

Methane foam performance was systematically evaluated using high-pressure and high-temperature experiments performed on oil-wet proppant packs. The sensitivities of foam performance to various key factors, including surfactant concentration, foam quality, total injection rate, salinity, operating pressure, and initial oil saturation were examined. The results showed that even though the foamability and foam strength in oil-wet proppant packs were adversely affected by wettability and presence of oil, the steady-state pressure drops across the proppant packs were insensitive to the quantity of oil initially present. The presence of oil above the critical oil saturation impeded the onset of foam generation. This suggested that the foamability of surfactants depends on the synergetic effects of surfactant’s ionic nature and foam parameters, such as foam quality and total injection rate, on their ability to reduce the oil saturation to a threshold value below which favorable bubble generation sites could be created. It was observed that, for low injection rate, anionic surfactant was ineffective at low salinity conditions, while amphoteric agent performed well at all salinities. Additionally, an increase in salinity resulted in enhanced pressure drop across the proppant packs for both anionic and amphoteric surfactants. Further, the results also established that too high operating pressures are somewhat detrimental to the foam strength and stability, irrespective of the ionic nature of foaming agents and the wettability of the porous medium. For the anionic surfactant, the increase in the total flow rate was found to mitigate the adverse effects of low salt concentration and operating pressure. Results from quality-sensitivity foam tests identified two regions for the foam behavior, named low-quality and high-quality regimes, separated by the transition foam quality. Finally, we discuss the implications of the results for the design and effective implementation of enhanced oil recovery (EOR) schemes that deploy hydrocarbon-based foams.

02 PETROLEUM↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2024

Lignin - A green material for antibacterial application — A review

Lignin's antibacterial properties have become increasingly relevant due to the rise of microbial infectious diseases and antibiotic resistance. Lignin is capable of interacting electrostatically with bacteria and contains polyphenols that cause damage to their cell walls. These features make lignin a desirable material to exhibit antibacterial behavior. Therefore, lignin in antibacterial applications offers a novel approach to address the growing need for sustainable and effective antibacterial materials. Recent research has explored the incorporation of lignin in various biomedical applications, such as wound dressings, implants, and drug delivery systems, highlighting their potential as a sustainable alternative to synthetic antibacterial agents. Furthermore, the development of lignin-based nanomaterials with enhanced antimicrobial activity is an active area of research that holds great promise for the future. Here, in this review, we have provided a summary of how lignin can be incorporated into different forms, such as composite and non-composite synthesis of antibacterial agents and their performances. The challenges and future considerations are also discussed in this review article.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tunable structure and reinforcement of polyvinyl alcohol (PVA) hydrogels using fungal chitin particles

Polysaccharides, including chitin, are one of the most abundant biopolymers in nature and are increasingly recognized as a sustainable alternative to petroleum-derived plastics and synthetic fillers in polymer composites. Traditionally sourced from crustacean shells, chitin offers mechanical strength and biocompatibility with limitations also in processability and functionality. Fungal-derived chitin material represents a promising alternative, with advantages including scalable fermentation on low-cost substrates, absence of shellfish allergens, and tunable molecular architectures that vary by species, developmental stage, and growth environment. Here, in this study, we systematically examined chitinous materials obtained from taxonomically and functionally distinct fungi, Laccaria bicolor, Trichoderma reesei and Rhizopus oryzae, to assess their structural, chemical, and morphological properties as reinforcement agents in polymer composites. Mild alkaline pretreatment was employed to obtain mycelium chitin particles, thereby improving accessibility to chitin and co-occurring β-D-glucans while maintaining microparticle integrity. Comprehensive FTIR and solid-state NMR analyses revealed species-specific differences in chemical composition and microstructure, with R. oryzae exhibiting a unique spectral signature. These fungal-derived chitin were then incorporated into poly(vinyl alcohol) (PVA) hydrogels, where they acted as reinforcing fillers without the need for additional chemical crosslinkers. Comparative evaluation of hydrogel properties demonstrated that fungal chitin significantly enhanced mechanical performance, with all mycelium fillers mitigating the water weakening in PVA hydrogels. R. oryzae-derived composites tripled the hydrogel tensile strength while the submicron fibrous morphology in L. bicolor contributes to over 45 % tensile improvement in dry PVA composites. Our findings highlight the potential of fungal biomass as a tunable, sustainable platform for producing chitin-based reinforcing agents.

Chitin↗