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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Rapid Assessment of a Lunar Surface Laboratory Module

Johnson Space Center has piloted an innovation team known as the Forge to perform rapid turnaround, concurrent engineering studies. The Forge is intended to be able to pull together a team of strategically selected domain experts to innovatively solve a specified problem within a short period of time. The Forge’s inaugural project was the development of a Lunar Surface Laboratory Module concept. The lab module is intended as an option for the NASA Lunar Architecture Team and may allow for increased science productivity and return on investment than with only the Surface Habitat. The Forge team developed two concepts, a stationary laboratory and a mobile laboratory. Human factors evaluations have been conducted to determine the acceptability of the resulting design concepts. The human factors evaluations conducted include a card sort evaluation of the laboratories by science discipline and the System Usability Scale (SUS). The card sort is focused subject matter expert expectations for the relative positioning of the laboratory functional areas, determining whether a given lab area should be adjacent to, or separated from, another. The SUS will focus on layout efficiency. Both will use human factors personnel and both life and physical scientists as subject matter experts. Each of these evaluations will focus primarily on objective data with limited subjective comments, reducing the time required for processing responses. The results of the card sort and SUS evaluations and their implications will be discussed. Based on the evaluation data, an overall acceptability of the Lunar Surface Laboratory Module produced by the Forge study can be determined. Lessons learned and recommendations for future use of human factors rapid assessment processes in early design trades will also be provided.

Human Factors↗
DOE OSTI2022

Metal sorter

A material sorting system sorts materials utilizing a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum.

Kumar, Nalin↗
DOE OSTI2020

The application of flow cytometry for kelp meiospore isolation

The goal of this study was to evaluate flow-cytometric techniques for isolating individual kelp meiospores into 96-welled plates. Previously reported low success rates for sorting tens of thousands of meiospores at a time have been improved by technological developments, specifically, the low nozzle pressure of the commercially available, JSAN (Bay Bioscience Co. Ltd) instrument. We monitored growth and gametophyte development post-sorting for 10 months. Our data demonstrate that successful kelp meiospore isolations of up to 76% viability can be achieved with flow-cytometry. This method can save time as compared to traditional, manual isolations using pipettes and improves confidence that self-fertilized individuals will not contaminate specific crosses of resulting gametophytes. Our results highlight a new application for the flow cytometer to produce clonal kelp gametophytes with direct applications for germplasm and culture collection development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A systematic analytical framework for multi-source municipal solid waste characterization for energy recovery

Advancing municipal solid waste (MSW) management from disposal-oriented practices toward circular, value-driven systems requires standardized methodologies capable of identifying material composition and resource recoverable potential at the point of generation. Despite extensive research, MSW characterization remains fragmented due to inconsistences in sampling methodologies, waste sorting categories, and temporal coverage across previous studies which limit cross-site comparability, reproducibility, and constrain the reliable evaluation of potential resource recovery pathways. This lack of consistency has hindered the development of a unified framework for MSW characterization and resource assessment. This study introduces a standardized, field-validated protocol for MSW sampling and composition analysis that ensures consistent, traceable data across diverse waste sources. The protocol integrates randomized spatial sampling, systematic material sorting, and controlled subsampling for multi-site and multi-season field campaigns. Validation included MSW collection from residential, grocery, restaurant, and school MSW streams across five U.S. states, including Maryland, Idaho, Virginia, Ohio, and Mississippi, to demonstrate the protocol’s ability to identify source-based composition patterns relevant to resource recovery applications. Grocery and restaurant streams were dominated by food waste and high-moisture organics, while school waste contained higher paper content and residential waste showed greater heterogeneity. Aggregation into energy-relevant fractions highlighted practical recovery pathways via anaerobic digestion or gasification, supporting data-driven planning, policy, and circular economy strategies for sustainable waste management across waste sources.

09 BIOMASS FUELS↗
DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Shi, Changxia↗
DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Chemistry↗
DOE OSTI2020

Sampling and resolution characteristics in reduced order models of shallow water equations: Intrusive vs nonintrusive

We investigate the sensitivity of reduced order models (ROMs) to training data spatial resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD), coupled with Galerkin projection (POD-GP), as an intrusive reduced order modeling technique. For non-intrusive ROMs, we consider two frameworks. The first is using dynamic mode decomposition (DMD), and the second is based on artificial neural networks (ANNs). For ANN, we utilized a residual deep neural network, and for DMD we have studied two versions of DMD approaches; one with hard thresholding and the other with sorted bases selection. Also, we highlight the differences between mean-subtracting the data (centering) and using the data without mean-subtraction. We tested these ROMs using a system of 2D shallow water equations for four different numerical experiments, adopting combinations of sampling rates and spatial resolutions. For these cases, we found that the DMD basis obtained with hard threshodling is sensitive to sampling rate. The sorted DMD algorithm helps to mitigate this problem and yields more stabilized and converging solution. Furthermore, we demonstrate that both DMD approaches without mean subtraction provide significantly more accurate results than DMD with mean-subtracting the data. On the other hand, POD is relatively insensitive to sampling rate and yields better representation of the flow field. Meanwhile, spatial resolution has little effect on both POD and DMD performances. Here, the numerical results reveal that an ANN on POD subspace (POD-ANN) performs remarkably better than POD-GP and DMD in capturing system dynamics, even with a small number of modes.

42 ENGINEERING↗
DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Techno-economics of hydrocarbon fuel production and recyclables recovery from landfill-destined municipal solid waste: AI-enhanced materials recovery facility design

Sustainable aviation fuels (SAF) production from cellulosic paper fractions of municipal solid waste (MSW) destined for landfills has strong potential to advance environmental, social, and economic sustainability across the aviation and waste sectors. This study proposes an artificial intelligence-enabled material recovery facility (AI-MRF) design to efficiently characterize, separate, process, and convert recovered paper waste from MSW into intermediate chemicals and SAF. The AI-MRF, designed to process 233,091 metric tons of MSW annually, integrates smart manufacturing technologies including AI, visual and hyperspectral imaging, multi-sensor data, and traditional sorting systems. Well-characterized and sorted cellulosic paper waste was utilized for chemical and fuel production scenarios, while clean plastics, metals, and glass were considered for recycling. Conversion of paper waste into intermediate sugars achieved a net present value (NPV) of up to $\$67$ million. For sugar-to-SAF production scenarios, the minimum fuel selling price (MFSP) was calculated at $\$6.11$ per gasoline gallon equivalent (GGE) when excluding recyclable revenue, and $\$4.03$ per GGE when halving recyclable revenue. The MFSP was further reduced to $\$1.96$ per GGE when accounting for SAF sales and recyclables. Nationally, this approach could yield about 2 billion GGE of hydrocarbon fuel annually from available MSW in the United States.

09 BIOMASS FUELS↗
DOE OSTI2025

Impact of mixed grain size sediment input on braided river Morphodynamics: Insights from experimental and numerical modeling

The rate of sediment supply has significant impacts on river morphology, making it crucial to understand the geomorphic changes and grain size distribution dynamics in rivers. However, the effects of varying grain size sediment input on morphological changes in braided channels remain poorly understood. This study is the first to investigate the bar development and sediment sorting processes in braided channels with non-uniform sediment inputs using both numerical and experimental approaches. We applied a two-dimensional numerical model, Nays2DH to confirm and generalize experimental results. The model reproduced key experiment results, including 1) stream elevation changes, and 2) grain size distribution. Using this validated model, we explored the morphological changes and sorting process in a braided river with sediment inputs. The numerical experiments demonstrate that sediment input controls the elevation of the stream bed and the grain size distribution. Notably, both the elevation and grain-size distribution become relatively stable in downstream of the channel. Additionally, the simulation results suggest that an increased sediment supply leads to greater channel complexity, with bed surface armoring decreasing.

Nays2DH↗
DOE OSTI2024

Paths to circularity for plastics in the United States

In 2019, the United States consumed over 57 million metric tons (MMT) of plastic with less than 7% recovered for reuse. This study provides an updated material flow analysis at national and regional scales for all durable and single-use plastics in the United States. From this material flow analysis, we develop a series of alternative future national plastic flow scenarios that envision a scale-up of recycling technologies, incorporating technical limitations and sorting infrastructure constraints. The results suggest that a maximum of 68% (24 MMT) of plastic waste could be diverted from landfills by scaling up existing commercial recycling technologies. Based on the current technological landscape, reaching near-zero waste is only possible if processes that are operating at pilot and laboratory scales can be effectively scaled and coupled with improved sorting infrastructure. Through these scenarios with increased recycling, the availability of postconsumer resin stocks could increase by 22–43 MMT.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chemical recycling of post-consumer polyester wastes using a tertiary amine organocatalyst

Recycling diverse waste plastics poses challenges due to complex sorting and processing, resulting in high costs and inefficiency. To tackle this, we present a metal-free catalytic sorting method for targeted deconstruction of polyester from post-consumer plastic waste, encompassing textiles, plastic mixtures, and multilayer packaging materials. This method employs N-methylpiperidine, a tertiary amine catalyst in methanol, to depolymerize polyethylene terephthalate (PET). Operating under these conditions (160°C, 1 h), we achieve 100% yields of dimethyl terephthalate and ethylene glycol. This technique also effectively breaks down other polyesters, including polylactic acid, polycarbonate, and polybutylene terephthalate, yielding high-yield monomers at relatively low temperatures. Through comprehensive nuclear magnetic resonance (NMR) analysis, we propose that N-methylpiperidine’s role is in enhancing methanol nucleophilicity and activating PET’s ester bond. Our insights advance the chemical recycling of post-consumer plastic waste, offering a potentially simple and efficient path to closing the polyester production loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modern Approaches to Exact Diagonalization and Selected Configuration Interaction with the Adaptive Sampling CI Method

Recent advances in selected configuration interaction methods have made them competitive with the most accurate techniques available and, hence, creating an increasingly powerful tool for solving quantum Hamiltonians. In this work, we build on recent advances from the adaptive sampling configuration interaction (ASCI) algorithm. We show that a useful paradigm for generating efficient selected CI/exact diagonalization algorithms is driven by fast sorting algorithms, much in the same way iterative diagonalization is based on the paradigm of matrix vector multiplication. We present several new algorithms for all parts of performing a selected CI, which includes new ASCI search, dynamic bit masking, fast orbital rotations, fast diagonal matrix elements, and residue arrays. The ASCI search algorithm can be used in several different modes, which includes an integral driven search and a coefficient driven search. The algorithms presented here are fast and scalable, and we find that because they are built on fast sorting algorithms they are more efficient than all other approaches we considered. After introducing these techniques, we present ASCI results applied to a large range of systems and basis sets to demonstrate the types of simulations that can be practically treated at the full-CI level with modern methods and hardware, presenting double- and triple-ζ benchmark data for the G1 data set. The largest of these calculations is Si$_2$H$_6$ which is a simulation of 34 electrons in 152 orbitals. We also present some preliminary results for fast deterministic perturbation theory simulations that use hash functions to maintain high efficiency for treating large basis sets.

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

Click-Chemistry-Based Free Azide versus Azido Sugar Detection Enables Rapid In Vivo Screening of Glycosynthase Activity

Engineering of carbohydrate-active enzymes such as glycosynthases to enable chemoenzymatic synthesis of bespoke oligosaccharides has been limited by the lack of suitable ultrahigh-throughput screening methods capable of robustly detecting either starting substrates or end-products of the glycosidic bond formation reaction. Currently, there are limited screening methods available for rapid and highly sensitive single-cell-based screening of glycosynthase enzymes employing azido sugars as activated donor glycosyl substrates. Here, we report a fluorescence-based approach employing click-chemistry for the selective detection of glycosyl azides as substrates versus free inorganic azides as reaction products that facilitated an ultrahigh-throughput in vivo single-cell-based assay of glycosynthase activity. This assay was developed based on the distinct differences observed in relative fluorescence intensity of the triazole-containing fluorophore product formed during the click-chemistry reaction of organic glycosyl azides versus inorganic azides. This discovery formed the basis for proof of concept validation of a directed evolution methodology for screening and sorting glycosynthase mutants capable of synthesis of targeted fucosylated oligosaccharides. Our screening approach facilitated fluorescence-activated cell sorting of an error-prone polymerase chain reaction-based mutant library of fucosynthases expressed in Escherichia coli to identify several novel mutants that showed increased activity for ß-fucosyl azide-activated donor sugars toward desired acceptor sugars (e.g., pNP-xylose and lactose). Finally, we discuss avenues for improving this proof of concept in vivo assay method to identify better glycosynthase mutants and further demonstrate the broader applicability of this screening methodology for synthesis of bespoke glycans.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

L -Value and Energy Dependence of 0.1–50 keV O + , He + , and H + Ions for CME and CIR Storms Over the Entire Van Allen Probes Era

Our studies report the first observation of L -value and energy sorted correlation of differential fluxes of 0.1–50 keV O + , He + , and H + ions with different geophysical parameters for 29 Coronal Mass Ejected (CME) and 40 Corotating Interaction Region (CIR)-driven geomagnetic storms during the entire Van Allen Probes era. For both solar wind drivers, ions with ≥1 keV energies show more variability in response to the solar wind changes, while the lower energy (<1 keV) ions are relatively stable. During the in-storm interval, O + ions show maximum flux enhancement and become further prominent during CME storms. O + ion (≥10 keV) fluxes show good correlation with – $V_{sw}B_z$, and Sym-H index during CME-driven storms in the L ~2.5–5.5. Apart from this, the average duration of persistence ($\langleΔt\rangle$) for enhanced fluxes is higher for CIR-driven storms with $\langleΔt\rangle_{O^+}>\langleΔt\rangle_{He^+}>\langleΔt\rangle_{H^+}$ at E ≤ 50 keV in the L ~2.5–5.5. Moreover, the observed value of $\langleΔt\rangle_i$ (where $\textit{i}$ is O + , H + or He + ) increases with the increasing L . Further, we discuss the plausible mechanisms to provide a comprehensive overview of L -values and energy sorted O + , He + and H + ion dynamics for two different categories of solar wind drivers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Transcriptomic and proteomic signatures of stemness and differentiation in the colon crypt

The intestinal epithelium is replaced weekly by non-quiescent stem cells with kinetics that rely on a rapid loss of stemness and choice for secretory or absorptive lineage differentiation. To determine how the cellular transcriptome and proteome changes during these transitions, we developed a new cell sorting method to purify stem cells, secretory and absorptive progenitor cells, and mature, differentiated cells. Transcriptome analyses revealed that as stem cells transition to the progenitor stage, alternative mRNA splicing and polyadenylation dominate changes in the transcriptome. In contrast, as progenitors differentiate into mature cell types, alterations in gene expression and mRNA levels drive the changes. RNA processing targets mRNAs encoding regulators of cell cycle, RNA regulators, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, global proteome profiling of sorted cell populations detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Economic evaluation of infrastructures for thermochemical upcycling of post-consumer plastic waste

Thermochemical technologies, such as pyrolysis, offer a potentially scalable pathway for upcycling diverse types of plastic waste (PW) into value-added chemicals. However, deploying these technologies in waste management infrastructures is not straightforward because such systems involve a wide range of interdependent stakeholders, processing facilities, and products. In this work, we present a holistic optimization framework that integrates value-chain analysis, techno-economic analysis, and life-cycle analysis for investigating the economic viability and environmental benefits of upcycling infrastructures that collect, sort, clean, and process post-consumer PW for producing virgin polymer resins. The framework is applied to a case study in the upper Midwest region of the US. Our analysis reveals that the infrastructures are economically viable and could activate a regional circular economy that generates over 1 billion USD in annual profit. Moreover, our analysis reveals that this economy can reduce the carbon footprint of PW incineration by half. Our framework also determines the inherent values of post-consumer PW and of derived products such as plastic bales and pyrolysis oil; we find that, in these infrastructures, PW becomes a highly valuable feedstock with a market value of 500 USD per tonne. Here, we discuss how this market value can generate incentives that foster more effective waste pre-sorting practices by consumers that can help bypass material recycling facilities and increase total system profit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Spatial proteomics reveals signal sequence characteristics correlated with localization in cyanobacteria

Abstract Cyanobacteria have an inner and outer cell membrane enclosing the periplasm and cell wall and an additional set of internal membranes (called the thylakoid membranes) enclosing the thylakoid lumen. The periplasm and thylakoid lumen have unique proteomes, but the mechanisms regulating protein sorting to these locations have remained elusive. Here, proximity-based proteomics using the engineered peroxidase APEX2 was performed in the cyanobacteria Synechococcus sp. PCC 7002 to profile the proteomes of the cytoplasm, thylakoid lumen, and the periplasm and outer membrane (P-OM). Our analyses revealed specific roles for the thylakoid lumen in photosynthesis and energy generation, as well as roles for the periplasm in metabolite transport and binding, cell motility, and cell wall maintenance. Forty proteins localized to both the thylakoid lumen and the P-OM; however, their biological functions remain unclear. We also analyzed the correlation between signal sequence characteristics and differential protein localization to either the thylakoid lumen or the P-OM. In PCC 7002, as well as Synechocystis sp. PCC 6803 and Nostoc sp. PCC 7120, thylakoid lumen proteins translocated across membranes via the Secretory (Sec) system possessed more hydrophobic and alpha-helical signal sequence H-regions than P-OM proteins. The signal sequences of homologous proteins in Gloeobacter violaceus PCC 7421, a cyanobacterial species with a combined thylakoid lumen and periplasmic space, did not exhibit such differences. Therefore, the pattern of increased H-region hydrophobicity and alpha helix content is specific to cyanobacteria with a separate thylakoid lumen space and likely contributes to proper protein sorting between the thylakoid lumen and periplasm.

Plant Sciences↗