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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 OSTI2024

Advances in in situ/operando techniques for catalysis research: enhancing insights and discoveries

Abstract Catalysis research has witnessed remarkable progress with the advent of in situ and operando techniques. These methods enable the study of catalysts under actual operating conditions, providing unprecedented insights into catalytic mechanisms and dynamic catalyst behavior. This review discusses key in situ techniques and their applications in catalysis research. Advances in in situ electron microscopy allow direct visualization of catalysts at the atomic scale under reaction conditions. In situ spectroscopy techniques like X-ray absorption spectroscopy and nuclear magnetic resonance spectroscopy can track chemical states and reveal transient intermediates. Synchrotron-based techniques offer enhanced capabilities for in situ studies. The integration of in situ methods with machine learning and computational modeling provides a powerful approach to accelerate catalyst optimization. However, challenges remain regarding radiation damage, instrumentation limitations, and data interpretation. Overall, continued development of multi-modal in situ techniques is pivotal for addressing emerging challenges and opportunities in catalysis research and technology.

Chen, Linfeng↗
DOE OSTI2024

New insights into the mechanism of ultrasonic atomization for the production of metal powders in additive manufacturing

Ultrasonic atomization is one of the promising technologies for producing metal powders for additive manufacturing, where precise control of particle size and morphology is essential. In this study, we coupled an ultrasonic transducer with a carbon fiber plate and atomized liquid droplets and films under different vibration amplitudes. Water, glycerol, and pure aluminum melt were used to study the atomization mechanism and the resulting droplet/powder characteristics, respectively. High-speed optical and ultrafast synchrotron X-ray imaging were used to study in situ the ultrasonic atomization dynamics, including pulsation and clustering of cavities inside the liquid layer/films, development of capillary waves, and formation of liquid droplets. For the first time, we observed and captured the occurrence of cavitation during the atomization of resting drops, films and impact droplets. The inertial cavitation events interfered with the capillary waves across the interphase boundary, puncturing and breaking the boundary to produce atomized mist. The in situ observation revealed the intricate dynamics of ultrasonic atomization and underscored the pivotal role of cavitation events throughout the entire atomization process. We also conducted experiments on ultrasonic atomization of liquid aluminum, producing particles of perfectly spherical shape. The particle size tended to decrease with reduced vibration amplitude Our work has demonstrated the important processing strategies on how to tailor the particle size while ensuring consistent particle shape and morphology, which is the key processing capability for producing high quality powders for additive manufacturing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Earthworms significantly enhance the temperature sensitivity of soil organic matter decomposition: Insights into future soil carbon budgeting

How and what soil fauna influence the soil organic matter (SOM) decomposition rate (Rs) and its temperature sensitivity (Q 10 ) have been largely ignored, although this is a crucial matter, especially under the scenario of global change. Further, in this study, a novel approach was adopted with a continuous changing-temperature incubation (daytime, from 7 °C to 22 °C; nighttime, from 22 °C to 7 °C) with rapid and continuous measurement, to examine the effect of soil macrofauna (specifically, earthworms) on Rs and Q 10 with three densities (no addition, low density, and high density). According to the results, the earthworms accelerated Rs. Furthermore, Rs with earthworm addition had a symmetrical pattern during daytime and nighttime cycles, which is contrary to traditional soil incubation, with only soil microbe as asymmetrical. More importantly, earthworm addition increased Q 10 markedly, ranging from 48% to 67%. Overall, the findings highlight the pivotal role of earthworms as soil macrofauna that regulating soil carbon release, and their effects should be integrated into process-based ecological models in future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Innovative control mechanism for research and test reactors using mandrel-shaped control rods

Research and test reactors have historically played a pivotal role in supporting the initial development of nuclear reactors. They continue to provide essential data for enhancing fuel designs and material knowledge. However, with many such reactors aging and the growing demand for data to bolster advanced reactor development, it is more necessary to research potential design attributes of the next generation of research and test reactors. For test reactors dedicated to fuel and material testing, the design of control mechanisms significantly influences the stabilization of neutron flux levels in irradiation positions while sustaining criticality. This study presents an innovative control mechanism for potential research and test reactor designs. It employs small absorber rods that move in opposite axial directions to maintain axial symmetry of power and neutron flux during burnup cycles. These rods maximize reactivity worth while also offering flexibility to flatten the radial power distribution. An axial translation of the control mechanisms’ absorbers, as compared to the rotational movement of absorbers in control cylinders, also provides a benefit to available excess reactivity and cycle length. Additionally, this work utilizes a simplified core model of the Advanced Test Reactor to assess the performance of this control mechanism. Compared to the current control system based on rotating control cylinders, the new control mechanism has the potential to enhance, or at least maintain, neutronic performance parameters in this reactor design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

The response field and the saddle points of quantum mechanical path integrals

Highlights: • Moyal quantum mechanics and Marinov’s path integral. • Classical and semiclassical limits of Marinov’s path integral. • Oscillating functional integrals. • Instantons of the Marinov’s path integral. In quantum statistical mechanics, Moyal’s equation governs the time evolution of Wigner functions and of more general Weyl symbols that represent the density matrix of arbitrary mixed states. A formal solution to Moyal’s equation is given by Marinov’s path integral. In this paper we demonstrate that this path integral can be regarded as the natural link between several conceptual, geometric, and dynamical issues in quantum mechanics. A unifying perspective is achieved by highlighting the pivotal role which the response field, one of the integration variables in Marinov’s integral, plays for pure states even. The discussion focuses on how the integral’s semiclassical approximation relates to its strictly classical limit; unlike for Feynman type path integrals, the latter is well defined in the Marinov case. The topics covered include a random force representation of Marinov’s integral based upon the concept of “Airy averaging”, a related discussion of positivity-violating Wigner functions describing tunneling processes, and the role of the response field in maintaining quantum coherence and enabling interference phenomena. The double slit experiment for electrons and the Bohm–Aharonov effect are analyzed as illustrative examples. Furthermore, a surprising relationship between the instantons of the Marinov path integral over an analytically continued (“Wick rotated”) response field, and the complex instantons of Feynman-type integrals is found. The latter play a prominent role in recent work towards a Picard–Lefschetz theory applicable to oscillatory path integrals and the resurgence program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗
DOE OSTI2025

Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning

Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).

Hydrogen storage↗
DOE OSTI2023

Film condensation with high heat fluxes and scaled experiments using pure steam for reactor containment cooling

Condensation tests were performed using a newly developed test facility for scaling the passive containment cooling system (PCCS) to a small modular reactor (SMR). The PCCS of the SMR plays a pivotal role in ensuring greater safety, reliability, and compactness than what is afforded by traditional reactors. Therefore, a well-designed PCCS is essential to SMRs. However, previous studies and test data were unsuitable for scaling, due to high variation in the test geometry and operating conditions. This study intends to close this research gap by using a novel designed scaled test facility consisting of vertical condensing test sections featuring 1-, 2-, and 4-inch-diameter condensing tubes with annular water cooling, and by applying superheated and saturated steam with different steam mass flow ranges of 5–25 g/s. Further, the primary test data, including axial temperatures, mass flow rates, and pressures, were used in conjunction with a standard data reduction method to estimate critical parameters such as heat fluxes, heat transfer coefficients, and condensation rates. These scaled test data would support improving empirical correlations and validating condensation models to identify scaling distortion for SMR PCCSs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

On The Use of Sectional Techniques for the Solution of Depolymerization Population Balances: Results on a Discrete-Continuous Mesh

To study the discrete bond-breaking phenomena of depolymerization, the use of a fully continuous Population Balance Equation (PBE) is inadequate to embody all the inherent characteristics of the process, thus resulting in the need for a discrete-continuous mesh. In this work, the performance of the three most state-of-the-art sectional techniques, i.e. the fixed pivot technique (FPT), cell average technique (CAT) and finite volume scheme (FVS) in approximating discrete depolymerization using discrete-continuous PBEs was extensively compared and evaluated. The solutions from these three methods show different accuracy depending on the breakage mechanisms. For chain-end scission, the FPT and the CAT satisfactorily predict the population densities and moments whereas the FVS fails to predict the population densities but preserves the zeroth and the first moments. In the application of a discrete-continuous model, we identified a previously-not-reported issue of a precipitous drop in the number density at the boundary of discrete and continuous region specifically for chain-end scission. We successfully fixed this problem by employing the alterations proposed in this paper, to the particle allocation functions at the boundary points. For random scission, all three sectional techniques predict the population densities and moments to a high degree of accuracy, even at a very coarse mesh, through the use of our new stoichiometric kernel which is able to closely approximate the inherently discrete bond-breaking depolymerization process. The assessments in this present work intends to provide a clear-cut direction to efficient and economical modelling of depolymerization processes.

Ahamed, Firnaaz↗
DOE OSTI2022

Reinforcement Learning for feedback-enabled cyber resilience

The rapid growth in the number of devices and their connectivity has enlarged the attack surface and made cyber systems more vulnerable. As attackers become increasingly sophisticated and resourceful, mere reliance on traditional cyber protection, such as intrusion detection, firewalls, and encryption, is insufficient to secure the cyber systems. Cyber resilience provides a new security paradigm that complements inadequate protection with resilience mechanisms. A Cyber-Resilient Mechanism (CRM) adapts to the known or zero-day threats and uncertainties in real-time and strategically responds to them to maintain the critical functions of the cyber systems in the event of successful attacks. Feedback architectures play a pivotal role in enabling the online sensing, reasoning, and actuation process of the CRM. Reinforcement Learning (RL) is an important gathering of algorithms that epitomize the feedback architectures for cyber resilience. It allows the CRM to provide dynamic and sequential responses to attacks with limited or without prior knowledge of the environment and the attacker. In this work, we review the literature on RL for cyber resilience and discuss the cyber-resilient defenses against three major types of vulnerabilities, i.e., posture-related, information-related, and human-related vulnerabilities. Here we introduce moving target defense, defensive cyber deception, and assistive human security technologies as three application domains of CRMs to elaborate on their designs. The RL algorithms also have vulnerabilities themselves. We explain the major vulnerabilities of RL and present develop several attack models where the attacker target the information exchanged between the environment and the agent: the rewards, the state observations, and the action commands. We show that the attacker can trick the RL agent into learning a nefarious policy with minimum attacking effort. The paper introduces several defense methods to secure the RL-enabled systems from these attacks. However, there is still a lack of works that focuses on the defensive mechanisms for RL-enabled systems. Last but not least, we discuss the future challenges of RL for cyber security and resilience and emerging applications of RL-based CRMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Biological Valorization of Natural Gas for the Production of Lactic Acid: Techno-Economic Analysis and Life Cycle Assessment

Due to the availability of natural gas, shale gas, and flared gas, there is increased interest in converting methane in these gases into commodity chemicals via cost-effective and sustainable processes. Recently, we have demonstrated an efficient process concept converting methane to lactic acid (LA) by methanotrophic bacteria with high carbon flux, pivoting potentials for commercialization. Herein, we present a first-of-kind conceptual design and a techno-economic analysis (TEA) of a biorefinery process with calculated minimum selling prices. This study includes both sensitivity analysis and scenario analysis for key cost drivers and for projecting path forwards in research and development. The analyses reveal that the conversion efficiency, LA product titer, LA productivity, and gas flow rate have the most significant impacts on cost. The MSP varies from $5.83-$2.17/kg LA depending on these key process attributes. Further, a life cycle assessment of this process concept is evaluated and compared to understand the sustainable aspects. In this TEA study, the bio-upgrading process from natural gas to LA presents a potentially promising approach in terms of the feedstock versatility, economic viability, and environmental impact.

BIOMASS FUELS,NATURAL GAS↗
DOE OSTI2025

A chemical-recovery-free ammonium sulfite-based alkali pretreatment of corn stover for low-cost sugar production via fertilizer use of waste liquor

The production of cellulosic sugars is a pivotal strategy for advancing biomass bioconversion. This study evaluated the pretreatment of corn stover using ammonium sulfite and potassium hydroxide to develop comprehensive data on sugar, lignin, chemicals, and overall mass recovery profiles in a batch reactor at 80 °C. The results indicated significant improvements in delignification, deacetylation, enzymatic digestibility, and overall sugar yield. Specifically, pretreating corn stover with a solution of 40 wt% potassium hydroxide and 15 wt% ammonium sulfite at 80 °C for 2 h achieved 78.9 % lignin removal and 82.1 % acetyl removal, resulting in a total sugar yield exceeding 87.5 % with an enzyme loading of 12.5 mg protein/g-glucan plus xylan. The pretreated spent liquor, containing ammonium, potassium, sulfur, biomass-derived organics, and inorganics, demonstrated substantial potential as a fertilizer. The techno-economic analysis projected a minimum sugar selling price of $0.285 per pound, supporting the ongoing development and implementation of chemical-recovery-free pretreatment technology.

09 BIOMASS FUELS↗
DOE OSTI2025

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗
DOE OSTI2025

Prediction of α $IIb$ $β$ 3 integrin structures along its minimum free energy activation pathway

The adhesion protein integrin is a transmembrane heterodimer that plays a pivotal role in cellular processes such as cell signaling and cell migration. To execute its function, integrin undergoes extensive conformational changes from a bent-closed to an extended-open state. Resolving the structures across these changes remains a challenge with both experimental and computational methods, but it is crucial for understanding the activation mechanism of integrin. We address this challenge for the platelet integrin α IIb β 3 by employing finite temperature string method with structures of the images along the initial guess path generated by a multiscale data-driven framework. The full-length all-atom structures along the resulting minimum free energy path between the inactive bent-closed and active extended-open states of α IIb β 3 integrin are consistent with a variety of experimentally resolved structures. Changes in these predicted structures along the path show that the extension and separation of the α and β subunits from the bent-closed to the extended-open state require correlated movements between the subdomain pairs in α IIb β 3 . Furthermore, these results provide new insights into integrin activation mechanism, and the predicted structures have potential applications in guiding the design of integrin-targeting therapeutics.

Dasetty, Siva [University of Chicago, IL (United S↗
DOE OSTI2024

Analysis of the turbostratic structures in PAN-based carbon fibers with wide-angle x-ray diffraction

Carbon fiber (CF) is a versatile material renowned for its excellent mechanical, thermal, and electrical properties. Polyacrylonitrile (PAN)-based CFs dominate the market due to their high tensile strength, rendering them suitable for structural applications in a wide variety of applications ranging from sporting goods to aerospace. Over five decades of commercial development of PAN-based CF has resulted in a range of varieties with different tensile moduli and tensile strengths. The microstructures, nanostructures, and crystal structures of PAN-based CF play pivotal roles in the macroscale properties of this material. In particular, the crystal structure and crystallite orientation in CF is closely related to the mechanical properties. The crystal structure of PAN-based CF generally consists of turbostratic carbon, which is a disordered form of graphite, the characteristics of which can be effectively characterized in a bulk format through wide-angle x-ray diffraction (WAXD). In this work, we employed a three-part approach to the analysis of WAXD patterns collected from four intermediate modulus PAN-based CFs. The approach incorporates a Scherrer analysis, a Debye analysis, and an orientational analysis to provide precise estimates of crystallite sizes, crystallite distributions, and crystallite orientations with the fiber axis. Furthermore, the results presented here suggest that intermediate modulus PAN-based CF mostly consists of small turbostratic crystallites (<4 nm), with larger crystallites having increased orientation with the fiber axis. The results here imply the presence of curvature and/or wrinkling of the turbostratic layers within the CF structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A historical perspective on the regulation of cellulose biosynthesis

Cellulose is a β-1,4 linked glucose polymer that is synthesized by higher plants, algae and even by some bacteria and animals, making it the most abundant polymer on earth. As the major load bearing structure of the plant cell wall, it is hugely important in terms of plant growth and development, and in recent years it has gained interest for its biotechnological applications. Naturally, there has been a large concerted research effort to uncover the regulatory mechanisms underpinning cellulose synthesis. During the last century, several major breakthroughs in our understanding of cellulose synthesis in algae, bacteria, and plants have been pivotal in advancing the field of cellulose research, improving the likelihood that cellulose synthesis could be feasibly adapted for sustainable purposes. In this work, we will summarize the major hypotheses and advancements made during the last century on the regulation of cellulose biosynthesis, focusing on Arabidopsis thaliana.

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

A review of in situ/operando studies of heterogeneous catalytic hydrogenation of CO 2 to methanol

Repurposing CO 2 into chemicals, one of the Carbon Dioxide Removal (CDR) strategies, still faces significant challenges in conversion and energy efficiency due to the lack of effective catalysts and processes. Fundamental understanding through in situ/operando investigations of the reaction mechanisms and catalyst structures is pivotal for developing the efficient catalysts. This paper reviews the past and recent in situ/operando studies of methanol synthesis from heterogeneous CO 2 hydrogenation over a few typical catalysts including Cu-based, oxide-based, and noble-metal-based catalysts. With the development of high-pressure reactors, in situ/operando IR, X-ray absorption spectroscopy (XAS), X-ray diffraction (XRD), neutron diffraction and imaging have been used to reveal the surface intermediates and structures of working catalysts under CO 2 hydrogenation conditions. On the one hand, the combined operando techniques shed light on working mechanisms for some catalytic systems. On the other hand, due to the complexity of selective CO 2 hydrogenation reaction and limited sensitivity of current accessible operando techniques to the surface structure of catalysts, it is still murky about the exact nature of the active sites at the surface/interface and how different sites promote different reaction paths. Furthermore, it is concluded that new methodologies for differentiating signals from different sites, and the development of surface-sensitive techniques for high pressure reactions are needed for providing structural descriptors of highly active and selective CO 2 conversion catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗