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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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

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

AI↗
DOE OSTI2024

Core Model Proposal #377: Breaking out food processing sector in GCAM

Purpose: This Core Model Proposal (CMP) expands the representation of detailed industry (CMP-326) in GCAM by separating the food processing sector from the aggregate “other industry sector”. Historical energy use is calibrated to IEA data for food processing, with some infilling for regions with limited IEA data. Food processing is linked to the GCAM food demand module, setting the energy demand for food processing in future periods based on food demand. While the direct price feedback is currently muted and the linkage is represented at the aggregated regional level, this CMP establishes the groundwork for a more detailed connection between the agrifood sectors and energy sectors in future work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Extraction of Value-Added Products from Food Processing Waste Using Dimethyl Ether

Poster for 2024 Intern Poster Session. Food production waste can be valorized to create a circular economy. Traditional extraction methods require pretreatment of the sample through heating or cell disruption, but this contributes to a majority of the process's energy usage for wet biomass. Using dimethyl ether extraction can combine the dewatering and extraction processes into one to skip the pretreatment step while still maintaining similar extraction rates.

09 BIOMASS FUELS↗
DOE OSTI2024

Extraction of Value-Added Products From Food Processing Waste Using Liquid Dimethyl Ether

Technical presentation for 2024 Intern Poster Session. Food production waste can be valorized to create a circular economy. Traditional extraction methods require pretreatment of the sample through heating or cell disruption, but this contributes to a majority of the process's energy usage for wet biomass. Using dimethyl ether extraction can combine the dewatering and extraction processes into one to skip the pretreatment step while still maintaining similar extraction rates.

09 BIOMASS FUELS↗
DOE OSTI2021

Optimal Financing Decision in a Contract Food Supply Chain with Capital Constraint

To solve the financing problem of the food producers, we consider a two‐echelon contract food supply chain composed of a family farm with capital constraints and a food processing enterprise. With no capital constraints as the benchmark model, we analyze optimal decisions of the family farm and the food processing enterprise in the case of bank financing with bank participation only and bank financing with “government, bank, and insurance” coparticipation. Then, we discuss how the risk of yield uncertainty influences the optimal decisions and profits of the family farm and the food processing enterprise under different financing situation. Meanwhile, the reason why the government subsidizes agriculture is explored, and the policy of minimum purchase price of the food is initiated when the market price is too low. Finally, the numerical examples and sensitivity analysis are presented. The results show that the bank financing with “government, bank, and insurance” coparticipation improves the welfare of supply chain members more obviously than the bank financing with bank participation only; when the rice price is too low, the policy of minimum purchase price of food is initiated, which increases the revenue and the growing enthusiasm of the family farm; the profits of the family farm and the food processing enterprise will decrease as the risk of yield uncertainty increases in the case of bank financing, and the risk of yield uncertainty will be reduced for the family farm when bank financing with “government, bank, and insurance” coparticipation.

Luo, Ying (ORCID:0000000158101443)↗
DOE OSTI2022

Bacterial Resistance Toward Antimicrobial Ionic Liquids Mediated by Multidrug Efflux Pumps

The effective elimination of foodborne pathogens through cleaning and disinfection measures is of great importance to the food processing industry. As food producers rely heavily on disinfectants to control pathogenic bacteria in their facilities, the increasing spread of tolerant, often even multidrug resistant, strains is of particular concern. In addition to efforts to prevent or at least reduce development and spread of strains resistant to disinfectants and sanitizers, there is an urgent need for new and effective antimicrobials. One new class of promising antimicrobials is ionic liquids (ILs), which have been reported to be effective against resistant strains as they interact with bacterial cells in multiple ways, but investigations of their effectivity against MDR bacteria or specific defense mechanisms are still limited. This study investigates the role of multidrug efflux pumps of the Resistance Nodulation-Division family (RND) on the resistance of bacterial pathogens Escherichia coli and Salmonella enterica serovar Typhimurium toward 10 antimicrobial active ILs. Results reveal that, while known structure–activity relationships (SARs), such as the side-chain effect, were found for all strains, antimicrobial ILs with one elongated alkyl side chain were significantly affected by the RND efflux pump, highlighting the importance of efflux pumps for future IL toxicity studies. In case of antimicrobial ILs with multiple side chains and different cationic head groups, two ILs were identified that were highly active against all investigated strains with little to no effect of the efflux pump. The results obtained in this study for RND efflux pumps can serve as a starting point for identifying and designing antimicrobial ILs as effective biocides against MDR bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of a Solar Heat and Power Co-Generation System. Final Report, CRADA No. TC02152.0

Final Report, CRADA No. TC02152.0. Date Technical Work Ended: October 28, 2013. This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Tassajara Technologies, Inc. (TTI), to develop, fabricate and demonstrate a Solar Heat and Power Co-generation System. The technical objectives of this CRADA were to engineer, design and build a prototype Solar Thermal Process Heat and Power Demonstration System that would be suitable for use at the Arc of Hilo food processing facility. This would be accomplished in two phases. The first phase would entail the building of a prototype at Tassajara facilities. Base design parameters, including the subsystem interactions that would produce reliable performance at the lowest cost per watt of energy generated with the desired balance of power and heat to meet the requirements of the designated food processing applications from Arc of Hilo, would be provided by LLNL. The data and design development would be integrated into the second phase engine prototype and solar thermal system that would be built and delivered, with interface requirements to the Miko Building. This project was originally designated as an eight (8) month project. However, it was ultimately extended by an additional thirty-five (35) months, for total project duration of forty-three (43) months.

14 SOLAR ENERGY↗
DOE OSTI2021

Development of a Solar Heat and Power Co-Generation System. Final CRADA Report

Final Report CRADA No. TC02152.0 Date Technical Work Ended: October 28, 2013. This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Tassajara Technologies, Inc. (TTI), to develop, fabricate and demonstrate a Solar Heat and Power Co-generation System. The technical objectives of this CRADA were to engineer, design and build a prototype Solar Thermal Process Heat and Power Demonstration System that would be suitable for use at the Arc of Hilo food processing facility. This would be accomplished in two phases. The first phase would entail the building of a prototype at Tassajara facilities. Base design parameters, including the subsystem interactions that would produce reliable performance at the lowest cost per watt of energy generated with the desired balance of power and heat to meet the requirements of the designated food processing applications from Arc of Hilo, would be provided by LLNL. The data and design development would be integrated into the second phase engine prototype and solar thermal system that would be built and delivered, with interface requirements to the Miko Building.

14 SOLAR ENERGY↗
DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗
DOE OSTI2020

Developing Materials for Extreme Environments and Their Use in Nuclear Waste Canisters and Reactors - 20559

The paper focuses on the development of materials which can be utilized in extreme industrial environments. The paper discusses the advancement of materials and their application in components which are utilized in extreme industrial environments as such that of the nuclear field and especially in the nuclear waste field. Nuclear power plants have become an indispensable part of the electricity generation, medical, food processing and many other industries. Though burning small amount of fuel as compared to conventional power plants, they also create waste which is not easy to handle as other types of wastes. The nuclear waste sitting at the bottom of spent fuel tanks around the globe has raised public concerns on how it will be dealt with. Europe has started to give an answer by working on geological repositories. Though till yet, waste has been cooled in spent fuel tanks and after processing, is precisely placed in nuclear waste canisters and casks and transported to sites across the country for further cooling and storage. Though in all this process there had been a great deal of advancement on the type of casks and canisters used and the processes for transporting nuclear material and waste. Often reports about radioactive material leakage, moisture content inside barrels etc. has surfaced. Be it official or unofficial report, there seems a technical failure on how the nuclear waste has been stored and placed at facilities around the globe. The other aspect of this material development is to be beneficial for nuclear reactors. As the technology gets advanced, nuclear reactors change their titles from Gen II to Gen III and so on. The new fleet of upcoming reactors will be exceptionally safer, reliable and more efficient. But these benefits will also bring drawbacks with them. As these reactors will operate at high temperature (above 800 degree Celsius) they also ask for advancement in materials used in the reactor core, fuel used, reactor control etc. The paper tries to answer such concerning questions. The work shows the study done on different material that can be better candidates for extreme environments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Luminescent Enhancement for Combined Solar and Commercial Agriculture. Final Report

This proposal will develop a new racking / mounting system combined with a new agriculture-tuned luminescent solar panel for low cost high tunnel implementation to produce both crops and electricity for small local farms. Crop trials performed under this specialized panel/racking system can be extended to open field agriculture with standard utility scale racking system in phase II. The US agricultural industry uses about 300 billion KW-hr of energy / year. Of this energy consumption, roughly 20% goes towards food production and 20% goes towards food processing. This proposal will allow farm land to simultaneously generate electricity, food AND provide jobs. Employment is one of the largest hurdles for the introduction of solar into rural areas. The ability to provide agricultural jobs in addition to solar energy from a plot of land will pave the way for greater adoption of photovoltaics in rural areas. A cost effective and highly durable hybrid power generating high tunnel greenhouse will be developed that generates electricity at less than $2.50/watt INSTALLED cost and can be used for crop production of high values crops. The high tunnel will use a new design of Soliculture greenhouse integrated luminescent solar panels to selectively absorb the green portion of the solar spectrum that is not used by plants and convert the light to red light with higher photosynthetic efficiency and to enhance power output of solar cells. Green light is selectively downshifted to red light using luminescent materials that match the photosythetically active region for plants and the efficiency maximum of Si photovoltaic cells. The color tuning associated with converting green light to red light has been shown to facilitate fruit production in commercial greenhouses growing cucumbers, lettuce and herbs.

14 SOLAR ENERGY↗
DOE OSTI2024

Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. Through the integration of Internet of Things (IoT), remote sensing, and blockchain technologies, these models facilitate the real-time monitoring of crop growth, resource allocation, and market dynamics, enhancing decision making and sustainability. The study adopts a mixed-methods approach, including systematic literature analysis and regional case studies. Highlights include AI-driven yield forecasting in European hydroponic systems and resource optimization in southeast Asian aquaponics, showcasing localized efficiency gains. Furthermore, AI applications in food processing, such as plasma, ozone and Pulsed Electric Field (PEF) treatments, are shown to improve food preservation and reduce spoilage. Key challenges—such as data quality, model scalability, and prediction accuracy—are discussed, particularly in the context of data-poor environments, limiting broader model applicability. The paper concludes by outlining future directions, emphasizing context-specific AI implementations, the need for public–private collaboration, and policy interventions to enhance scalability and adoption in food security contexts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Coupling Circularity With Carbon Negativity in Food and Agriculture Systems

Achieving a circular economy is critical for a sustainable future, particularly in sectors that currently produce resource-intensive products in a linear fashion, such as food and agriculture. At the same time, technologies that remove atmospheric CO 2 , often referred to as carbon dioxide removal (CDR) or carbon negativity, must be developed and deployed rapidly if we are to avoid the worst effects of climate change. Circularity and CDR are often assessed and discussed independently, even though they are highly intertwined. Innovations to food and agriculture systems are essential to achieving a circular economy and enabling rapid deployment of CDR technologies. We explore critical areas of technology that must undergo rapid innovation (upstream and downstream) to food processing and consumption, namely precision and regenerative agriculture and biorefining, respectively. If implemented at scale, these two areas of technology have the potential to couple circularity with carbon negativity in food production systems.

Biorefining↗
DOE OSTI2025

Analysis of Extracted Ingredients from Dairy Byproduct Using Dimethyl Ether

Whey permeate is a byproduct created in large quantities from the dairy industry with limited applications due to transportation and stability. Whey permeate is primarily comprised of water, carbohydrates, and minerals with minimal contribution of proteins. Various biomasses in food processing have utilized liquid dimethyl ether (DME) as a form of extraction for high-value ingredients and dewatering. DME is a growing interest in wastewater and biomass treatment due to it being a green solvent, ability to dissolve organic solvents, and miscibility with water. The current study is to determine if DME can effectively dewater whey permeate as well as recover components that can be further used in the food industry as a value-added ingredient. Analysis of the liquid extract and solid extract was evaluated with inductively coupled plasma-mass spectrometry (ICP-MS) and solid extracts were further characterized with the application of a scanning electron microscope (SEM).

09 - BIOMASS FUELS↗
DOE OSTI2022

Biofilm formation and genomic features of Listeria monocytogenes strains isolated from meat and dairy industries located in Piedmont (Italy)

Listeria monocytogenes is considered a major challenge for the food industry as it can persist for long periods in food processing plants by forming biofilms. The aims of this study were: i) to assess the biofilm producing ability of 57 Listeria monocytogenes isolates previously subjected to whole-genome sequencing (WGS); ii) to compare the levels of biofilm formation with the presence or absence of biofilm associated genes. To determine the presence or absence of a known set of biofilm associated genes, a comparative genomic analysis was performed on each strain. Among Listeria monocytogenes isolates, 58 %, 38.5 % and 3.5 % exhibited weak, moderate or strong biofilm production, respectively. No difference in biofilm production was observed between food and environmental isolates. The percentage of Listeria monocytogenes strains isolated from meat products (57 %) classified as moderate or strong biofilm producers was higher than the percentage obtained for strains isolated from dairy products (28 %). Here, the presence of the Stress Survival Islet 1, the arsD stress gene and the truncated inlA protein was significantly associated with increased levels of biofilm. Combining biofilm phenotype with molecular and genotyping data may provide the opportunity to better understand the relationship between genes linked to biofilm formation in Listeria monocytogenes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mesoscale fractal whey protein particles derived from microscale linear-shaped protein assemblies (Part 1): Manufacturing method and particle characteristics

Whey protein isolates (WPI) are widely used in processed foods for their versatile functional properties. Modifying the structural properties of proteins by assembling them into mesoscale or microscale particles may improve their functionality and broaden their applications. This study aims to manufacture and characterize mesoscale whey protein particles (WPP) derived from WPI. Two types of WPP, WPP1 (0.05 mL/min) and WPP2 (0.25 mL/min), were prepared through a multistep approach involving liquid antisolvent (LAS) precipitation, heat treatment, and microfluidization. Liquid antisolvent precipitation was performed by injecting a 20% (wt/vol) WPI dispersion (pH 7) into an ethanol-glycerol mixture (75:25, vol/vol) under laminar flow, followed by heat treatment at 80°C for 20 min as a particle hardening step. This process produced stable fiber- and ribbon-shaped whey protein assemblies (WPA), which served as precursors to WPP. Subsequent microfluidization (150 MPa, 6 passages) reduced the size of WPA, yielding mesoscale WPP with irregular morphologies and a more uniform size distribution, as revealed by microscopy and dynamic light scattering. ζ-Potential and fluorescence labeling indicated higher surface charge and surface hydrophobicity of WPP compared with untreated WPI. The WPP showed internal mass fractal and surface fractal structures at larger length scales, analyzed using small-angle X-ray scattering. Fourier transform infrared spectroscopy demonstrated an increased fraction of intermolecular β-sheets in WPP, suggesting that hydrogen bonding contributed to their formation. Gel electrophoresis confirmed that disulfide bonds served as the primary cross-links stabilizing the WPP structure. Furthermore, turbidity measurements showed that WPP exhibited superior colloidal phase stability compared with untreated WPI and maintained high colloidal stability under both acidic and neutral pH conditions.

Antisolvent precipitation↗