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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 OSTI2023

Polyester-based epoxy vitrimer integrating spent coffee ground as a natural filler

Coffee is a widely consumed beverage, but approximately 80% mass of coffee cherry is discarded as waste. Here, in this study, spent coffee grounds (SCG) were recycled and used as a natural filler in a polyester-based epoxy matrix made from reactions of diglycidyl ethers of Bisphenol A and polyethylene glycol with methyl nadic anhydride. The properties of SCG/epoxy composites with various SCG contents up to 40% w/w were evaluated using various techniques such as FT-IR spectroscopy, tensile testing, optical microscopy, differential scanning calorimetry, and rheology. The SCG filled polyester-based epoxy matrix demonstrated excellent dimensional stability and retained a permanently crosslinked network, but re-shaping was possible at ~150 °C through transesterification, which occurred due to a dynamic chain exchange reaction between the ester group of the epoxy matrix and the hydroxyl group of the SCG fillers. The transesterification also improved the interfacial adhesion between the matrix and SCG fillers, resulting in tensile strength of over 20 MPa and a modulus of around 2.5 GPa, even with high SCG contents up to 40% w/w. While neat, cured epoxy shows thermoset behavior, filling the matrix with SCG enables reforming and origami-inspired spontaneous change in shape.

42 ENGINEERING↗
DOE OSTI2026

Biohydrogen Generation from Un-Pretreated Spent Coffee Grounds with Clostridium Thermocellum

Coffee is among the world's most widely consumed beverages, generating 18 million wet tonnes of waste spent coffee grounds annually. Disposal of SCGs is complicated by their high moisture content, their recalcitrant chemical composition, and the presence of caffeine and other bioactive compounds. Dark fermentation is a promising technology for conversion of waste cellulosic biomass into renewable hydrogen, carbon dioxide, and volatile fatty acids. Typical SCGs have high moisture content, are pre-milled to fine particle sizes, and contain 8%-19% cellulose and up to 40% hemicellulose, making them an attractive feedstock for dark fermentation. In this study, we investigate biohydrogen production from unpretreated SCGs using Clostridium thermocellum strain KJC19-9, a cellulolytic bacterium engineered to co-utilize xylose, specifically examining the inhibitory effects of residual caffeine and high solids loadings on microbial growth and hydrogen production efficiency. While SCGs were initially resistant to both cell growth and biohydrogen production, a strategy to co-ferment with low concentrations of cellobiose dramatically enhanced process performance, reducing lag phase duration and enabling cellulosome production for efficient cellulose hydrolysis. This co-substrate approach generated up to 944 mL hydrogen per L reaction from 50 g/L of spent coffee grounds over 120 h (1.34 mol H2/mol carbohydrate), validating SCGs as a promising dark fermentation feedstock and underscoring the value of mixed substrate approaches in consolidated bioprocessing.

08 HYDROGEN↗
DOE OSTI2024

Efficacy of long-lasting insecticide-incorporated nets on 2 scolytinae pests, the coffee berry borer Hypothenemus hampei and tropical nut borer Hypothenemus obscurus under laboratory conditions

Abstract Several pests affect coffee (Coffea spp., Rubiaceae) and macadamia, Macadamia integrifolia Maiden & Betche (Proteaceae) in Hawaii. The coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), is the most damaging to coffee, while the tropical nut borer, Hypothenemus obscurus (Fabricius) (Coleoptera: Curculionidae: Scolytinae), is one of the worst pests of macadamia. This paper investigates the potential efficacy of a long-lasting insecticide-incorporated net (LLIN) under laboratory conditions to manage these pests. The LLIN (40 denier with mesh size 625 knots/in²), incorporated with α-cypermethrin (0.34%), was excised into 100 mm circles and inserted in 100 mm Petri dishes. Nets with the same quality but without insecticides were used as control treatments. Twenty beetles (H. obscurus or H. hampei) each were placed on the treated and non-treated netting at 4 treatment or exposure hours—1, 6, 12, and 24—with 5 replicates. Subsequently, the beetles were ranked alive, affected, or dead. The results showed that the LLIN with α-cypermethrin had significant lethal and sub-lethal effects on both Hypothenemus species, causing over 90% mortality after 24 h of exposure and paralysis after 1, 6, and 12 h of exposure. The highest lethality value was recorded after 24 h of exposure for both H. obscurus and H. hampei. The LT50 of H. obscurus and H. hampei was 18.78 min and 2.15 h, respectively, while the LT90 values were 32.11 and 20.67 h. These results imply the potential effectiveness of LLINs with α-cypermethrin for management of H. obscurus and H. hampei, but field studies are warranted for optimization.

Entomology↗
DOE OSTI2023

Tropical Tree Crop Simulation with a Process-Based, Daily Timestep Simulation Model (ALMANAC): Description of Model Adaptation and Examples with Coffee and Cocoa Simulations

Coffee (Coffea species) and Cocoa (Theobroma cacao) are important cash crops grown in the tropics but traded globally. This study was conducted to apply the ALMANAC model to these crops for the first time, and to test its ability to simulate them under agroforestry management schemes and varying precipitation amounts. To create this simulation, coffee was grown on a site in Kaua’i, Hawai’i, USA, and cocoa was grown on a site in Sefwi Bekwai, Ghana. A stand-in for a tropical overstory tree was created for agroforestry simulations using altered parameters for carob, a common taller tropical tree for these regions. For both crops, ALMANAC was able to realistically simulate yields when compared to the collected total yield data. On Kaua’i, the mean simulated yield was 2% different from the mean measured yield, and in all three years, the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When precipitation patterns were altered, in Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawai’i. When agroforestry-style management was simulated, a low Leaf Area Index (LAI) of the overstory showed positive or no effect on yields, but when LAI climbed too high, the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and demonstrated its simulation of different management and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Deep Learning Model Segmentations on Computed Tomography 3D Reconstructions of Coffee Beans to Determine Void Ratio (U-Net) and Roast Level (LinkNet)

This project will evaluate the functionality of Object Research Dragonfly software’s user produced deep learning (DL) models on Computed Tomography (CT) scanned coffee beans from green (unroasted) through a dark roast. DL models will be expected to identify voids within the coffee beans, and identify the level of roast of the bean from the CT reconstruction. The scope of this project is intended to meet the Capstone Project requirements of University of California San Diego (UCSD) Structural Engineering master’s degree and offer useful insight on Dragonfly’s DL capability for LANL’s Non-Destructive Evaluation (NDE) CT team. The results of this project will be presented to the E-6 NDE group within LANL. Data acquisition was completed with a North Star Imaging (NSI) X-25 CT Cabinet.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Water production for coffee brewing by electrodeionization

A resin-wafer electrodeionization (RW-EDI) apparatus for purifying water for coffee brewing comprises a cathode; an anode; and multiple porous solid resin wafer exchange units arranged in a stack between the cathode and the anode, and an air distributor adapted and arranged to aerate the water to be purified. Each unit comprises a monovalent cation exchange membrane (CEM), an anion exchange membrane (AEM), and an ion exchange resin wafer between the CEM and the AEM, which is in contact with, and in fluid flow connection with the CEM and AEM. Each resin wafer comprises a cation exchange resin and an anion exchange resin. The units are oriented with the CEM facing the cathode and the AEM facing the anode, with space between the units defining ion concentrate chambers. Bipolar ion exchange membranes separate the anode and cathode from their nearest resin wafer exchange units.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Fully Inkjet‐Printed, 2D Materials‐Based Field‐Effect Transistor for Water Sensing

Abstract Despite significant progress in solution‐processing of 2D materials, it remains challenging to reliably print high‐performance semiconducting channels that can be efficiently modulated in a field‐effect transistor (FET). Herein, electrochemically exfoliated MoS 2 nanosheets are inkjet‐printed into ultrathin semiconducting channels, resulting in high on/off current ratios up to 10 3 . The reported printing strategy is reliable and general for thin film channel fabrication even in the presence of the ubiquitous coffee‐ring effect. Statistical modeling analysis on the printed pattern profiles suggests that a spaced parallel printing approach can overcome the coffee‐ring effect during inkjet printing, resulting in uniform 2D flake percolation networks. The uniformity of the printed features allows the MoS 2 channel to be hundreds of micrometers long, which easily accommodates the typical inkjet printing resolution of tens of micrometers, thereby enabling fully printed FETs. As a proof of concept, FET water sensors are demonstrated using printed MoS 2 as the FET channel, and printed graphene as the electrodes and the sensing area. After functionalization of the sensing area, the printed water sensor shows a selective response to Pb 2+ in water down to 2 ppb. This work paves the way for additive nanomanufacturing of FET‐based sensors and related devices using 2D nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hyperspectral imaging for real-time waste materials characterization and recovery using endmember extraction and abundance detection

Hyperspectral imaging, combined with advanced spectral unmixing techniques and artificial intelligence, offers a powerful solution for improving material identification and classification. Here, this study evaluates the effectiveness of the pixel purity index and the sequential maximum angle convex cone algorithms in extracting and validating spectral signatures from pure samples of paper components (cellulose and lignin) and plastic (polypropylene). Principal-component analysis showed that both algorithms captured nearly all relevant variance for the tested materials. Spectral signatures were compared using the spectral angle mapper, revealing high similarity in the short-wave infrared region and greater variability in the visible near-infrared range. The methodology was then applied to a disposable coffee cup to detect and quantify mixed materials, accurately estimating material abundance and object area with less than 1% error. This approach enhances material classification, supporting product verification, quality control, and automated sorting for sustainable waste management and resource recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaporation of a Reactive Nanofluid Sessile Drop: Capturing Rapid Emergence of Surface Crystals with In Situ Synchrotron X-ray Diffraction

Mechanisms for surface pattern formation from evaporation of a reactive nanofluid sessile drop are not well understood. In contrast to the coffee-ring effect from inert particles, rapid chemical and morphological transformation of reactive nanoparticles upon rapid evaporative drying are challenging to probe experimentally. Here, using grazing-incidence X-ray surface scattering, the nanostructure of nascent surface patterns has been probed as a ZnO nanofluid sessile drop rapidly dries. The high temporal resolution enabled by the high flux of synchrotron X-rays allows the observation of the emergence of Zn(OH) 2 surface crystals from the onset of evaporation and their rapid evolution into the final residual surface pattern, via transient layered complexes evident from the temporary appearance of X-ray diffraction peaks preceding Zn(OH) 2 formation. The results offer mechanistic insights of morphogenesis of surface patterns from evaporation-induced self-assembly and self-organization of reactive nanofluids, previously untenable using other experimental methods.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multigenic resistance to Xylella fastidiosa in wild grapes ( Vitis sps.) and its implications within a changing climate

Xylella fastidiosa is a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives. There is little understanding of the genes that contribute to plant resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (Vitis vinifera) are not resistant to the bacterium. Here we study a wild grapevine species, V. arizonica, that segregates for resistance. Using genome-wide association, we identify candidate resistance genes. Resistance-associated kmers are shared with a sister species of V. arizonica but not with more distant species, suggesting that resistance evolved more than once. Finally, resistance is climate dependent, because individuals from low (< 10 °C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in colder climates. In fact, climate is as effective a predictor of resistance phenotypes as some genetic markers. We extend our climate observations to additional crops, predicting that increased pathogen pressure is more likely for grapevines and almonds than some other susceptible crops.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Longitudinal Effects on Plant Species Involved in Agriculture and Pandemic Emergence Undergoing Changes in Abiotic Stress

In this work we identify changes in high-resolution zones across the globe linked by environmental similarity that have implications for agriculture, bioenergy, and zoonosis. We refine exhaustive vector comparison methods with improved similarity metrics as well as provide multiple methods of amalgamation across 744 months of climatic data. The results of the vector comparison are captured as networks which are analyzed using static and longitudinal comparison methods to reveal locations around the globe experiencing dramatic changes in abiotic stress. Specifically we (i) incorporate updated similarity scores and provide a comparison between similarity metrics, (ii) implement a new feature for resource optimization, (iii) compare an agglomerative view to a longitudinal view, (iv) compare across 2-way and 3-way vector comparisons, (v) implement a new form of analysis, and (vi) demonstrate biological applications and discuss implications across a diverse set of species distributions by detecting changes that affect their habitats. Species of interest are related to agriculture (e.g., coffee, wine, chocolate), bioenergy (e.g., poplar, switchgrass, pennycress), as well as those living in zones of concern for zoonotic spillover that may lead to pandemics (e.g., eucalyptus, flying foxes).

Cashman, Mikaela↗
DOE OSTI2023

Novel viruses of the family Partitiviridae discovered in Saccharomyces cerevisiae

It has been 49 years since the last discovery of a new virus family in the model yeast Saccharomyces cerevisiae . A large-scale screen to determine the diversity of double-stranded RNA (dsRNA) viruses in S . cerevisiae has identified multiple novel viruses from the family Partitiviridae that have been previously shown to infect plants, fungi, protozoans, and insects. Most S . cerevisiae partitiviruses (ScPVs) are associated with strains of yeasts isolated from coffee and cacao beans. The presence of partitiviruses was confirmed by sequencing the viral dsRNAs and purifying and visualizing isometric, non-enveloped viral particles. ScPVs have a typical bipartite genome encoding an RNA-dependent RNA polymerase (RdRP) and a coat protein (CP). Phylogenetic analysis of ScPVs identified three species of ScPV, which are most closely related to viruses of the genus Cryspovirus from the mammalian pathogenic protozoan Cryptosporidium parvum . Molecular modeling of the ScPV RdRP revealed a conserved tertiary structure and catalytic site organization when compared to the RdRPs of the Picornaviridae . The ScPV CP is the smallest so far identified in the Partitiviridae and has structural homology with the CP of other partitiviruses but likely lacks a protrusion domain that is a conspicuous feature of other partitivirus particles. ScPVs were stably maintained during laboratory growth and were successfully transferred to haploid progeny after sporulation, which provides future opportunities to study partitivirus-host interactions using the powerful genetic tools available for the model organism S . cerevisiae .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hydra: Computer Vision for Data Quality Monitoring

Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.

Roy, Ayan↗
DOE OSTI2024

Optimal Design of Food Packaging Considering Waste Management Technologies to Achieve Circular Economy

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider the minimum increase in price (MIP) when adding recycling to the cost of each packaging solution, while for the environmental analysis, the greenhouse gas emissions impact was considered. A case study on ground coffee packaging is used to illustrate the proposed framework. The results demonstrate that the multilayer bag option is the most convenient when considering both the chosen economic and environmental impacts.

Life Cycle Analysis↗
DOE OSTI2025

SITCOMTN-148: LSST Camera Electro-Optical Test (Run 7) Results

This note collects results from the LSST Camera electro-optical testing prior to installation on the TMA. We describe the focal plane characterization, optimization, and the resulting default settings. Results from eo-pipe are shown for standard runs such as B-protocols, Dense and SuperDense PTCs, gain stability, OpSim runs of Darks, and Darks with variable delays. We also describe features such as e2v Persistence, ITL phosphorescence in coffee stains, remnant charge near Serial register following saturated images, vampire pixels, ITL dips, and other sensor features.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Agrivoltaics: Solar Farming for a Greener Future

Resilient, secure, diversified, and disaster-hardened energy systems are critical to Puerto Rico's clear energy future. This presentation builds on NREL's PR100 One Year Progress Summary Report, discussing the intersection of land availability, PV capacity growth, and the potential role of agrivoltaics in contributing to Puerto Rico's 100% renewable energy goal and agricultural sector resilience. An overview of the state-of-the-science in agrivoltaics is provided, including the NREL InSPIRE Puerto Rican pilot project on hurricane-resistant, shade-grown agrivoltaic coffee. Agrivoltaics is discussed in the context of food-energy resilience for island nations, and future research & development needs are highlighted.

agrivoltaics↗