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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of the Microcalorimeter Array for the Line Emission Mapper (LEM) X-Ray Probe

The Line Emission Mapper (LEM) is a proposed NASA probe-class mission designed to study the formation of structure in the Universe. LEM will have a 14k pixel array of transition-edge sensor (TES) microcalorimeters that provide a spectral resolution of < 2.5 eV and a bandpass of 0.2-2 keV. In this paper, we report on the status and plan for continued development of the LMS microcalorimeter. This includes details of the TES and x-ray absorber design, and the measured performance in prototype arrays. We present a detailed budget for the energy resolution and show how the properties of the LEM pixels are well optimized for the baseline time-division-multiplexing (TDM) that will be used read out the array. Finally, we describe the design and performance of the first full scale LMS arrays which include the necessary mechanical and electrical interfaces needed for LEM and are a precursor to an engineering model detector.

Stephen J Smith↗
NASA NTRS2002

Synthesis and Characterization of the First Liquid Single Source Precursors for the Deposition of Ternary Chalcopyrite (CuInS2) Thin Film Materials

Molecular engineering of ternary single source precursors based on the [{PBu3}2Cu(SR')2In(SR')2] architecture have afforded the first liquid CIS ternary single source precursors (when R = Et, n-Pr), which are suitable for low temperature deposition (< 350 C). Thermogravimetric analyses (TGA) and modulated-differential scanning calorimetry (DSC) confirm their liquid phase and reduced stability. X-ray diffraction studies, energy dispersive analyzer (EDS), and scanning electron microscopy (SEM) support the formation of the single-phase chalcopyrite CuInS2 at low temperatures.

Banger, Kulbinder K.↗
NASA NTRS2007

The Nation's Vision for Exploration: An Update

I.Current key activities: a) Constellation Level2-System Engineering. b) Lunar Architecture Team (LAT)2-technology assessment and architectural option for the lander. c) Mars Architecture Team-system engineering support, Science integration, precursor program planning. d) Lunar Lander Project Core Team-GN&C and Flight system engineering. e) Technology program-supporting multiple projects in robotics, power systems, aero entry technology. f) Mission Operation Project-Mission operations system engineering. g) Advanced Environmental Monitoring Instruments. H. Lunar Reconnaissance Orbiter instrument (Diviner). II. Mission Proposals a) Lunar Sample return. b) Lunar Gravity field mapper.

space exploration↗
DOE OSTI2026

A Chemoselective and Stereodivergent Platform of Heme‐Nitrene Transferases to Access Chiral Aryl‐β‐Amino Esters and An Investigation of the Sequence‐Activity Landscape

Engineered biocatalysts can utilize nitrene precursors to access enantioenriched amination products, yet they have not been applied to produce valuable, enantiomerically enriched noncanonical β-amino esters. Current approaches to synthesizing β-amino acids rely on pre-oxidized precursors and multistep synthetic approaches involving various protecting groups. We engineered a platform of heme enzymes for stereoselective C–H bond amination of readily available carboxylic ester derivatives to install primary amines. A directed evolution campaign coupled with sequencing of over 1000 variants enabled us to develop engineered variants that use either O-pivaloylhydroxylamine triflic acid (PONT) or hydroxylamine hydrochloride (H 2 NOH∙HCl) as aminating reagents. An analysis of the resulting sequence–activity dataset revealed additional improvements that could be made to the final variant, highlighting the utility of sequencing data to guide future steps in directed evolution campaigns. Furthermore, the evolved nitrene transferases expand the scope of accessible chiral β-amino acid building blocks for peptidomimetic applications and provide new starting points for the design and synthesis of enantioenriched β-amino acid motifs.

amino ester building blocks↗
DOE OSTI2024

Synthesis and characterization of photo-cross-linkable quince seed-based hydrogels for soft tissue engineering applications

The convenience, versatility, and biocompatibility of photocrosslinkable hydrogel precursors make them promising candidates for developing tissue engineering scaffolds. However, the current library of photosensitive materials is limited. This study reports, for the first time, the modification of quince seed mucilage (QS) with glycidyl methacrylate (GM), resulting in the synthesis of methacrylated QS (QSGM). The chemical composition and structure of QS were analyzed. The effects of reaction time, temperature, QS concentration, and GM/QS ratio on the degree of methacrylation, as well as the physicochemical, rheological, mechanical, and biological properties of the synthesized materials were explored. Chemical characterization using 1H NMR and FTIR confirmed the successful methacrylation of QS. Hydrogels fabricated from QSGMs at a 0.5 wt% concentration exhibited high swelling ratios of 320 to 580 g/g, and compressive strengths between 0.6 ± 0.1 and 1.2 ± 0.3 kPa. No significant changes in the rheological properties of hydrogel precursors were observed. Moreover, QSGM-based hydrogels supported cell encapsulation for 14 days with minimal cytotoxicity and immune cell activation. Finally, as a proof of concept, the potential use of QSGM for 3D printing was demonstrated. Overall, the results highlight the significant potential of QSGMs as a biomaterial of choice for soft tissue engineering applications.

3D printing↗
DOE OSTI2023

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗
DOE OSTI2023

Engineering custom morpho- and chemotypes of Populus for sustainable production of biofuels, bioproducts, and biomaterials

Humans have been modifying plant traits for thousands of years, first through selection (i.e., domestication) then modern breeding, and in the last 30 years, through biotechnology. These modifications have resulted in increased yield, more efficient agronomic practices, and enhanced quality traits. Precision knowledge of gene regulation and function through high-resolution single-cell omics technologies, coupled with the ability to engineer plant genomes at the DNA sequence, chromatin accessibility, and gene expression levels, can enable engineering of complex and complementary traits at the biosystem level. Populus spp., the primary genetic model system for woody perennials, are among the fastest growing trees in temperate zones and are important for both carbon sequestration and global carbon cycling. Ample genomic and transcriptomic resources for poplar are available including emerging single-cell omics datasets. To expand use of poplar outside of valorization of woody biomass, chassis with novel morphotypes in which stem branching and tree height are modified can be fabricated thereby leading to trees with altered leaf to wood ratios. These morphotypes can then be engineered into customized chemotypes that produce high value biofuels, bioproducts, and biomaterials not only in specific organs but also in a cell-type-specific manner. For example, the recent discovery of triterpene production in poplar leaf trichomes can be exploited using cell-type specific regulatory sequences to synthesize high value terpenes such as the jet fuel precursor bisabolene specifically in the trichomes. By spatially and temporally controlling expression, not only can pools of abundant precursors be exploited but engineered molecules can be sequestered in discrete cell structures in the leaf. The structural diversity of the hemicellulose xylan is a barrier to fully utilizing lignocellulose in biomaterial production and by leveraging cell-type-specific omics data, cell wall composition can be modified in a tailored and targeted specific manner to generate poplar wood with novel chemical features that are amenable for processing or advanced manufacturing. Precision engineering poplar as a multi-purpose sustainable feedstock highlights how genome engineering can be used to re-imagine a crop species.

09 BIOMASS FUELS↗
NASA NTRS1978

The engineering analysis of solar radiation

A necessary precursor to construction of well-designed, efficient, and economically viable solar energy systems is the engineering analysis not only of the systems themselves but also of the solar radiation that will drive them. This paper presents the first steps in such an analysis to support the design of solar thermal power systems. A rationale for development of an integrated approach to this analysis is outlined, and elements of the approach are described. A dynamic computer simulation of a conceptual system was employed in an initial sensitivity analysis to explore how performance estimates might be affected by the precision and amount of detail in solar radiation data used as model input. A measurement program, including instrumentation, used to characterize precisely and in detail the solar resource at one location is described as is a probabilistic model derived from it, for predicting insolation as a function of time.

Reid, M. S.↗
NASA NTRS1999

Engine Test and Measurements

Although the importance of aerosols and their precursors are now well recognized, the characterization of current subsonic engines for these emissions is far from complete. Furthermore, since the relationship of engine operating parameters to aerosol emissions is not known, extrapolation to untested and unbuilt engines necessarily remains highly uncertain. 1997 NASA LaRC engine test, as well as the parallel 1997 NASA LaRC flight measurement, attempts to address both issues by expanding measurements of aerosols and aerosol precursors with fuels containing different levels of fuel sulfur content. The specific objective of the 1997 engine test is to obtain a database of sulfur oxides emissions as well as the non-volatile particulate emission properties as a function of fuel sulfur and engine operating conditions. Four diagnostic systems, extractive and non-intrusive (optical), will be assembled for the gaseous and particulate emissions characterization measurements study. NASA is responsible for the extractive gaseous emissions measurement system which contains an array of analyzers dedicated to examining the concentrations of specific gases (NO, NO(x), CO, CO2, O2, THC, SO2) and the smoke number. University of Missouri-Rolla uses the Mobile Aerosol Sampling System to measure aerosol/particulate total concentration, size distribution, volatility and hydration property. Air Force Research Laboratory uses the Chemical Ionization Mass Spectrometer to measure SO2, SO3/H2SO4, and HN03 Aerodyne Research, Inc. uses Infrared Tunable Diode Laser system to measure SO2, SO3, NO, H2O, and CO2.

Wey, Chown Chou↗
DOE OSTI2024

Colloidal AInSe 2 (A = K, Rb, Cs) Nanocrystals with Tunable Crystal and Band Structures

Wide band gap AInSe 2 (A = K, Rb, Cs) is an important interlayer material for improving the efficiency of Cu(In,Ga)(S,Se) 2 (CIGS) solar cells. Compared to high-vacuum deposition and solid-state synthesis, a less energyintensive method is of interest for its fabrication. Herein, we present the rapid, low-temperature colloidal synthesis of AInSe 2 nanocrystals that opens a pathway for convenient solution processing. The crystal structures and electronic band structures of the nanocrystals were studied, and their particle morphology was found to be dependent on the choice of alkali metal and selenium precursors. Homogeneous solid solution (K,Rb,Cs)InSe 2 nanocrystals were synthesized using a mixture of alkali metal precursors. Their compositions, lattice parameters, and band gaps were easily tuned based on the K:Rb:Cs precursor ratio, providing potential for interface engineering of CIGS nanocrystal-based solar cells.

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

Can Multiple Ions in an Ionic Liquid Improve the Biomass Pretreatment Efficacy?

we report over the last few decades, efforts to transition the global production of fuels and chemicals toward renewable carbon feedstocks have accelerated. A large portion of these efforts have focused on valorization of one of the most abundant renewable carbon sources, lignocellulose. Pretreatment of lignocellulose is the first critical step in this process. In this study, novel ionic liquid (IL) systems consisting of multiple ions known to be effective at biomass pretreatment were tested on woody and grassy biomass. Molecular simulations and experimental results established the synergistic advantages of combining specific individual components in these systems. For pine (woody) biomass, pretreatment with the combination of imidazolium, cholinium, acetate, and lysinate ions achieved 80% glucose and 70% xylose yields at high biomass loading. For sorghum biomass, an IL system comprising cholinium, lysinate, and palmitate ions not only enabled a 98% glucose yield but was also found to be biocompatible in a one-pot configuration, producing the biofuel precursor bisabolene using an engineered strain of the yeast Rhodosporidium toruloides.

09 BIOMASS FUELS↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Superconducting gravity gradiometer mission. Volume 2: Study team technical report

Scientific and engineering studies and developments performed or directed by a Study Team composed of various Federal and University activities involved with the development of a three-axis superconducting gravity gradiometer integrated with a six-axis superconducting accelerometer are examined. This instrument is being developed for a future orbital mission to make precise global gravity measurements. The scientific justification and requirements for such a mission are discussed. This includes geophysics, the primary mission objective, as well as secondary objective, such as navigation and feats of fundamental laws of physics, i.e., a null test of the inverse square law of gravitation and tests of general relativity. The instrument design and status along with mission analysis, engineering assessments, and preliminary spacecraft concepts are discussed. In addition, critical spacecraft systems and required technology advancements are examined. The mission requirements and an engineering assessment of a precursor flight test of the instrument are discussed.

Morgan, Samuel H.↗
NASA NTRS1989

Superconducting gravity gradiometer mission. Volume 1: Study team executive summary

An executive summary is presented based upon the scientific and engineering studies and developments performed or directed by a Study Team composed of various Federal and University activities involved with the development of a three-axis Superconducting Gravity Gradiometer integrated with a six-axis superconducting accelerometer. This instrument is being developed for a future orbital mission to make precise global gravity measurements. The scientific justification and requirements for such a mission are discussed. This includes geophysics, the primary mission objective, as well as secondary objectives, such as navigation and tests of fundamental laws of physics, i.e., a null test of the inverse square law of gravitation and tests of general relativity. The instrument design and status along with mission analysis, engineering assessments, and preliminary spacecraft concepts are discussed. In addition, critical spacecraft systems and required technology advancements are examined. The mission requirements and an engineering assessment of a precursor flight test of the instrument are discussed.

Morgan, Samuel H.↗
DOE OSTI2025

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗