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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A semi-continuous process for co-production of CO 2 -free hydrogen and carbon nanotubes via methane pyrolysis

Heterogeneous catalytic pyrolysis of hydrocarbons to produce CO 2 -free hydrogen and high-quality solid carbon have historically been stymied by issues related to catalyst deactivation by carbon formed during pyrolysis on the catalyst surface. In addition, a system that demonstrates sustained performance in terms of high conversion, high H 2 yield, and high quality of produced carbon has remained elusive. Here, we propose and demonstrate a semi-continuous methane pyrolysis process to H 2 and carbon nanotubes (CNTs) consisting of repeated pyrolysis and in situ (i.e., within the reactor) CNT dislodging by vigorous steam/argon fluidization. With this process, we demonstrate 10 process cycles with high H 2 yield from CH 4 and CNT dislodging in a fluidized-bed reactor with an Fe/q-Al 2 O 3 catalyst synthesized by an easily scalable incipient wetness impregnation process. We also identify and present opportunities for future catalyst and process development.

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

Dl-3-n-butylphthalide promotes neurite outgrowth of primary cortical neurons by Sonic Hedgehog signaling via upregulating Gap43

Highlights: • NBP promoted neurite outgrowth in immature primary cortical neurons. • NBP increased axon and dendrite extension in mature primary cortical neurons. • NBP promoted neuritogenesis and neuronal plasticity via Shh signaling pathway. • The Shh signaling pathway increased Gap43 expression in primary cortical neuron. • NBP promoted neurite outgrowth by Shh signaling via upregulating Gap43 expression. Neurite outgrowth is the basis for wiring during the development of the nervous system. Dl-3-n-butylphthalide (NBP) has been recognized as a promising treatment to improve behavioral, neurological and cognitive outcomes in ischemic stroke. However, little is known about the effect and mechanism of NBP on the neurite outgrowth. In this study, we used different methods to investigate the potential effects of NBP on the neurite extension and plasticity of immature and mature primary cortical neurons and explored the underlying mechanisms. Our results demonstrated that in immature and mature cortical neurons, NBP promoted the neurite length and intersections, increased neuritic arborization, elevated numbers of neurite branch and terminal points and improved neurite complexity and plasticity of neuronal development processes. Besides, our data revealed that NBP promoted neurite extension and branching partly by activating Shh signaling pathway via increasing Gap43 expression both in immature and mature primary cortical neurons. The present study provided new insights into the contribution of NBP in neuronal plasticity and unveiled a novel pathway to induce Gap43 expression in primary cortical neurons.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Measurement of Spray Chamber Ignition Delay and Cetane Numbers for Aviation Turbine Fuels

Experiments using pure compounds, National Jet Fuels Combustion Program (NJFCP) test fuels, and commercial jet fuels were conducted to demonstrate the equivalence of the indicated cetane number (ICN) and derived cetane number (DCN) for jet fuels. The calibrated range for ICN was also extended to lower cetane number (CN) values (5 to 35) to allow CN quantification for jet fuel synthetic blending components (SBCs) with low CN. ICN and DCN were shown to be highly correlated for values above about 30. This study presents the most comprehensive comparison of these two methods published to date. Because of the importance of low-volume test methods for early-stage SBC production process development, we demonstrated that ICN and DCN can be accurately measured with 15 mL of fuel, well below 40 to 100 mL required by standard methods. ICN or DCN is important for jet fuels because fuels with lower CN are more prone to lean blowout (LBO), an undesirable operational failure in a jet engine. Comparing data on a fuel-to-air ratio (Φ) at LBO for the NJFCP fuels shows similar linear correlations for ICN and DCN. Ignition delay measurements at lower-pressure and higher-temperature conditions may be more directly relevant to LBO. At 675 °C, 0.5 MPa, and a global Φ of roughly 0.68, ignition delay time correlations to LBO were similar to those produced from DCN and ICN. A much weaker correlation was obtained with a global Φ value of 0.34.

09 BIOMASS FUELS↗
DOE OSTI2025

Predicting Multicomponent Aqueous Phase Adsorption Equilibria of Organic Acids Using the Generalized Brunauer–Emmett–Teller Isotherm Model

Here, to support process development of adsorptive separation of organic acids, this work presents a thermodynamic modeling methodology to predict multicomponent aqueous phase organic acid adsorption equilibria from single-component adsorption isotherms using the generalized Brunauer–Emmett–Teller isotherm model (gBET). With the organic acid fugacities rigorously accounting for the aqueous phase organic acid solution chemistry and solution nonideality, gBET precisely represents the single-component adsorption isotherms and accurately predicts the binary and ternary mixed-acid adsorption equilibria for the ranges of initial pH (∼3–7), acid concentration (100–400 mmol/L), and temperature (298.15–328.15 K) with less than 10% average absolute relative deviation. In addition, gBET with pH-independent parameters provides insights into the underlying adsorption phenomena, including the adsorbate loadings and compositions in the monolayer and subsequent layers under varying initial pH, temperature, concentration, and composition. The gBET model predictions outperform the predictions from the overloading model and the Ideal Dilute Solution Theory.

09 BIOMASS FUELS↗
DOE OSTI2025

Unveiling Feedstock Variability: Insights into Corn Stover Conversion - Part I: Physicochemical Properties and Self-Degradation

Transforming agricultural waste into biofuels and bioproducts is crucial to advancing a low-carbon bioeconomy. However, the inherent variability in the composition and quality introduces uncertainties in the conversion efficiency and poses challenges in process development. Through integrating a high-throughput conversion system, material characterization techniques, and advanced data analysis tools, this study investigates the variability of corn stover and its subsequent impacts on carbohydrate conversion. The findings reveal that indoor storage substantially reduces the moisture and ash content and soil contamination, while other properties remain largely unchanged. Self-degradation due to microbial activity during storage decreases the carbohydrate content of corn stover but enhances glucose and xylose yields. A negative correlation is observed between sugar yields and lignin content across samples with varying ash and moisture content. The inhibitory effect of lignin diminishes in self-degraded samples likely due to the disrupted cell wall structure. Although self-degradation slightly increases cellulose crystallinity, no strong correlation was observed between the crystallinity and sugar yield. Hot water pretreatment under mild conditions effectively mitigates inherent variability, consistently improving the sugar yield from corn stover by up to 50%. By elucidating the feedstock variability and its impact on convertibility, these findings offer valuable insights into appropriate feedstock handling and management, highlighting potential strategies to address variability challenges.

09 BIOMASS FUELS↗
DOE OSTI2020

Characterizing Variability in Lignocellulosic Biomass: A Review

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Recently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We further examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

09 BIOMASS FUELS↗
DOE OSTI2024

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH 4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH 4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH 4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH 4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH 4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

Environmental Sciences & Ecology↗
DOE OSTI2023

Fragment-based drug nanoaggregation reveals drivers of self-assembly

Drug nanoaggregates are particles that can deleteriously cause false positive results during drug screening efforts, but alternatively, they may be used to improve pharmacokinetics when developed for drug delivery purposes. The structural features of molecules that drive nanoaggregate formation remain elusive, however, and the prediction of intracellular aggregation and rational design of nanoaggregate-based carriers are still challenging. We investigate nanoaggregate self-assembly mechanisms using small molecule fragments to identify the critical molecular forces that contribute to self-assembly. We find that aromatic groups and hydrogen bond acceptors/donors are essential for nanoaggregate formation, suggesting that both π-π stacking and hydrogen bonding are drivers of nanoaggregation. We apply structure-assembly-relationship analysis to the drug sorafenib and discover that nanoaggregate formation can be predicted entirely using drug fragment substructures. We also find that drug nanoaggregates are stabilized in an amorphous core-shell structure. These findings demonstrate that rational design can address intracellular aggregation and pharmacologic/delivery challenges in conventional and fragment-based drug development processes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Engineering microbial consortia for mixed plastic upcycling

Recent studies in developing processes using ‘single’ plastic waste for microbial conversion have demonstrated great promise in advancing a circular economy. However, chemical complexity and compositional variability of post-consumer ‘mixed’ plastic waste pose huge challenges to using it as a feedstock for biomanufacturing. Here, we present a process leveraging a synthetic microbial consortium, comprising Rhodococcus jostii strain PET and Acinetobacter baylyi ADP1, enabled by engineering the division of labor. The robust consortium synergistically and stably consumes diverse mixtures of oxygenated compounds, derived from the depolymerization of post-consumer, mixed plastic waste, regardless of the fluctuating plastic waste compositions. We evaluate the upcycling potential of the stable consortium by applying rational metabolic engineering to both specialists, enabling the funneling of these oxygenates into lycopene and lipids. This work highlights the potential of stable microbial consortia to valorize untapped, mixed plastic waste for sustainable biomanufacturing, offering a promising solution to global plastic pollution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Two-dimensional diamonds from sp 2 -to- sp 3 phase transitions

The ability to change material properties through phase engineering has long been sought, with the goal of ad hoc tunability of the physical and chemical properties of the transformed phases. The synthesis and study of graphene have made it possible to explore the mechanisms of 2D phase transformations, opening up paths towards the formation of 2D diamond and diamond thin films. This Review examines the state-of-the-art phase transformations in 2D graphitic systems and beyond. The theoretical models formulated to describe the sp2-to-sp3 transitions from graphene to 2D diamond and the experimental processes developed to induce the transition to 2D diamond are discussed, focusing on the transformations induced by chemical functionalization and pressure. The effects of different structural and environmental factors on the evolution of the phase transformations and on the properties of the transformed diamond phases are explored. Without comprehensively reviewing phase transitions in all 2D materials, we briefly mention hexagonal boron nitride, phosphorene, transition metal dichalcogenides and MXenes systems. Lastly, the Review delves into the technologies and applications of phase transformations in 2D materials and the opportunities for this field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications

Abstract An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H 2 S, HCl, HCN, K 2 O, KCl, NH 3 ) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al 2 O 3 , MgO, anatase-TiO 2 , rutile-TiO 2 , ZnO, ZrO 2 ) catalysts and supports. Approximately 3,000 unique adsorption geometries and corresponding adsorption energies were obtained.

09 BIOMASS FUELS↗
DOE OSTI2020

Frequency domain measurements of melt pool recoil force using modal analysis

Recoil pressure is a critical factor affecting the melt pool dynamics during Laser Powder Bed Fusion (LPBF) processes. Recoil pressure depresses the melt pool. When the recoil pressure is low, thermal conduction and capillary forces may be inadequate to provide proper fusion between layers. However, excessive recoil pressure can produce a keyhole inside the melt pool, which is associated with gas porosity. Direct recoil pressure measurements are challenging because it is localized over an area proportionate to the laser spot size producing a force in the mN range. This paper reports a vibrationbased approach to quantify the recoil force exerted on a part in a commercial LPBF machine. The measured recoil force is consistent with estimates from high speed synchrotron imaging of entrained particles, and the results show that the recoil force scales with applied laser power and is inversely related to the laser scan speed. These results facilitate further studies of melt pool dynamics and have the potential to aid process development for new materials.

42 ENGINEERING↗
DOE OSTI2025

Insights into the mechanism of electrochemical chloride oxidation in ethanol from X-ray photoelectron spectroscopy, quiescent solution voltammetry, and rotating ring-disk electrodes

The wide availability of bio-derived alcohols provides the impetus to develop processes that convert them to valuable chemicals. The chloride ion is a redox mediator for electrocatalytic ethanol oxidation to 1,1-diethoxyethane (1,1-DEE) through an ethyl hypochlorite (EtOCl) intermediate, and this paper describes the chloride oxidation reaction (COR) to EtOCl on a glassy carbon (GC) electrode. Voltammetry measurements on a GC electrode in inert acetonitrile solvent combined with ex situ X-ray photoelectron spectroscopy (XPS) establish a Volmer step, where chloride ion from solution chemisorbs and is oxidized. In reactive ethanol solvent, ethanol adsorbs, and analyzing the current response in an LSV experiment supports a two-electron-transfer to form EtOCl, with chemisorption of the regenerated chloride. Koutecký–Levich (K–L) analysis on a rotating ring disk electrode (RRDE) shows that the kinetic rate constant of the COR in ethanol is on the order of 10 −8 cm s −1 , which is five orders of magnitude faster than the direct alcohol oxidation reaction in a kinetically limited regime. This hydrodynamic approach in understanding the electrochemistry of this non-aqueous system extends the possibilities for mediated electrocatalysis in neat alcohol solvents.

Van Daele, Ryan D. [University of Michigan, Ann Ar↗
DOE OSTI2020

Air-transfer production method for large-area picosecond photodetectors

We have designed and prototyped the process steps for the batch production of large-area micro-channel-plate photomultipliers (MCPPMT) using the “air-transfer” assembly process developed with single LAPPD TM modules. Results are presented addressing the challenges of designing a robust package that can transmit large numbers of electrical signals for pad or strip readout from inside the vacuum tube and of hermetically sealing the large-perimeter window–body interface. We have also synthesized a photocathode in a large-area low-aspect-ratio volume and have shown that the micro-channel plates recover their functionality after cathode synthesis. These steps inform a design for a multi-module batch facility employing dual nested low-vacuum and ultra-high-vacuum systems in a small-footprint. The facility design provides full access to multiple MCP-PMT modules prior to hermetic pinch-off for leak-checking and real-time photocathode optimization.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Renormalization of excitonic properties by polar phonons

Here we employ quasiparticle path integral molecular dynamics to study how the excitonic properties of model semiconductors are altered by electron–phonon coupling. We describe ways within a path integral representation of the system to evaluate the renormalized mass, binding energy, and radiative recombination rate of excitons in the presence of a fluctuating lattice. To illustrate this approach, we consider Fröhlich-type electron–phonon interactions and employ an imaginary time influence functional to incorporate phonon-induced effects nonperturbatively. The effective mass and binding energies are compared with perturbative and variational approaches, which provide qualitatively consistent trends. We evaluate electron-hole recombination rates as mediated through both trap-assisted and bimolecular processes, developing a consistent statistical mechanical approach valid in the reaction limited regime. These calculations demonstrate how phonons screen electron–hole interactions, generically reducing exciton binding energies and increasing their radiative lifetimes.

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

Chemically sensitive fluorescence imaging of colliding microdroplets

Here, we present a simple optical capability for generating spatially resolved chemical concentration maps of mixing fluids using a chemically sensitive dye, 1-hydroxy-3,6,8-pyrenetrisulfonic acid, detected by planar laser induced fluorescence. To demonstrate an application of this capability, we investigate the collision and mixing of a pair of microdroplets in air. The two microdroplets are composed of different fluids, methanol and water, with the dye initially in the methanol droplet. When the droplets collide and mixing process develops, the fluorescence of the dye shifts from blue to green as the solvent environment changes. A series of spectral-temporal images of the collision and subsequent mixing are recorded, from which we extract the distribution of the two intermixing droplet species reflected in the spatially resolved dye spectra. Images reveal material transfer between droplets in both coalescing and non-coalescing droplet collisions.

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

Spatially resolved charge-transfer kinetics at the quantum dot–microbe interface using fluorescence lifetime imaging microscopy

Integrating the optoelectronic properties of quantum dots (QDs) with biological enzymatic systems to form microbe-semiconductor biohybrids offers promising prospects for both solar-to-chemical conversion and light-modulated biochemical processes. Developing these nano–bio hybrid systems necessitates a deep understanding of charge-transfer dynamics at the nano–bio interface. Photoexcited carrier transfer from QDs to microbes is driven by complex interactions, with emerging insights into the relevant thermodynamic and kinetic factors. The heterogeneities of both microbes and QD ensembles pose significant challenges in mechanistic understanding, which is critical for designing advanced nano–bio hybrids. We used fluorescence lifetime imaging microscopy to analyze charge transfer between a CdSe QD film andShewanella oneidensismicrobes. We correlated the spatiotemporal fluorescence data with an analytical model. Our analysis revealed two distinct distributions of QD de-excitation pathways. The characteristics of these distributions: 1) a faster transfer rate ( k ¯ E T 1 = 1.5 10 9 s - 1 ), with a lower acceptor number ( N ¯ a 1 = 0.03 ) and 2) a slower transfer rate ( k ¯ E T 2 = 4.1 10 8 s - 1 ) with a higher acceptor number ( N ¯ a 2 = 0.18 ). We assign these distributions to the indirect and direct electron transfer mechanisms, respectively. Our findings demonstrate how spectroscopic imaging can uncover fundamental electron transfer mechanisms at complex interfaces, offering valuable design principles for future nano–bio hybrids.

Science & Technology - Other Topics↗
DOE OSTI2022

AbBERT: Learning Antibody Humanness via Masked Language Modeling

Understanding the degree of humanness of antibody sequences is critical to the therapeutic antibody development process to reduce the risk of failure modes like immunogenicity or poor manufacturability. We introduce AbBERT, a transformer-based language model trained on up to 20 million unpaired heavy/light chain sequences from the Observed Antibody Space database. We first validate AbBERT using a novel “multi-mask” scoring procedure to demonstrate high accuracy in predicting complementary determining regions—including the challenging hypervariable H3 region. We then demonstrate several uses of AbBERT at various points along the antibody design process. AbBERT enhances in silico antibody optimization via deep reinforcement learning by utilizing its learned embeddings as additional observations during optimization. Within a larger computational antibody design platform, AbBERT has been successfully applied as an additional design objective, where it displays strong correlations with computational tools predicting antibody structural stability. Finally, mutant antibody sequences that have been scored as unfavorable by AbBERT have shown corresponding low yields when expressed in cells. These use cases demonstrate the power of language modeling within computational antibody design.

Bioinformatics↗