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Results for “mechanistic modeling”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multiscale Porous High-temperature Heat Exchanger Using Ceramic Co-extrusion

In this project, our MIT, Purdue, and GE team aims to design, model, fabricate, and test a novel high temperature, compact, and durable ceramic heat exchanger to be operated under high temperature and pressure conditions for aerospace applications. Our approach is grounded in introducing multiscale porosity, i.e., centimeter-scale channels embedded with micrometer-scale channels, into the ceramic heat exchanger to significantly improve its heat transfer performance and mechanical strength while maintaining minimal pressure losses. We first developed high-fidelity thermal-fluid-mechanical model capable of precisely capturing the heat transfer rate, temperature profile, pressure drop, and mechanical stress throughout the entire heat exchanger design. Guided by our model, we identified the optimal design parameters for the SiC heat exchanger body and manifolds. Then, we established a completed fabrication procedure to create multiscale features in the ceramic heat exchanger, including co-extrusion, lamination, burnout, and sintering. We fabricated multiple heat exchanger bodies consisting of 6 × 6 and 3 × 3 centimeter-scale channels where each individual centimeter-scale channel comprises 625 crack-free microchannels with 90 μm × 90 μm opening. Owing to the multiscale features, our fabricated heat exchanger bodies exhibited desirable mechanical strength with 156 MPa flexural strength under 1300 Celsius degree. Despite the demonstrated highly tailorable microscopic features and superior mechanical strength, we identified delamination due to the complex interaction among ceramic, polymer, and gas species can be a critical challenge to create fully defect-free heat exchanger, which requires further fundamental investigations in future works. To test the heat exchanger performance, we constructed a high-temperature and high-pressure experimental apparatus that can be safely operated under 400 Celsius degree and 4 bar. With insights gained from mechanistic modeling, material development, and detailed characterization, a cost model was finally developed to understand the market potential of the developed technology, where a cost of $43,000 Celsius degree/kW was envisioned. This project developed a transformative approach to high-performance heat exchanger design. The thermal-fluid-mechanical design approach developed in this project can serve as a generic tool to guide the design of various heat-exchangers operated under high-temperature and high-pressure conditions. The material fabrication approach established in this project can be a useful guide for ceramic processing at extreme length scales.

42 ENGINEERING↗
DOE OSTI2025

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗
DOE OSTI2022

Atomic-scale mechanism of carbon nucleation from a deep crustal fluid by replica exchange reactive molecular dynamics simulation

Here we present a mechanistic model of carbon nucleation and growth from a fluid at elevated temperature (T) and pressure conditions, typical of those found in the shallow Earth’s lithosphere. Our model uses a replica exchange reactive molecular dynamics framework in which molecular configurations are swapped between adjacent T replica at regular intervals according to underlying statistical mechanics. This framework allows predicting complex molecular structures and thermodynamics while remaining computationally efficient. Here we simulate the reactivity of an unstable mixture of CO 2 and CH 4 at 1000 K and 1 GPa. We find that the path to thermodynamic equilibrium is initially entropy-driven, producing a diversity of short-lived species, including various alcohols with intermediate carbon oxidation states. Cyclic and polycyclic radicals that are sometimes resonance-stabilized form next and set the stage for carbon nucleation. The carbon exsolution process releases abundant water, is exothermic and starts with the nucleation of a large aggregate of hydrogenated graphene flakes from covalently bonded polycyclic units. The carbon backbone of this nucleus subsequently grows into a hydrogen-depleted fullerene-like structure, before evolving toward a partially bilayered graphene layer. Overall, our results show that the mechanism of graphitic C formation is certainly not bimolecular, and that it may involve a combination of key condensation and radical chain reactions. This will help understand the isotopic, and reactive characteristics of carbon-bearing fluids during their upward transit through the Earth’s mantle and crust. Moreover, the mechanistic insights outlined here present intriguing similarities with the process of soot and interstellar dust formation, which suggests that the widespread distribution of abiotic polyaromatic and graphitic material on Earth and beyond may reflect the prevalence of a fundamental chemical pathway.

58 GEOSCIENCES↗
DOE OSTI2023

Unusual Temperature Dependence of Water Sorption in Semicrystalline Hydrogels

Abstract Water vapor sorption is a ubiquitous phenomenon in nature and plays an important role in various applications, including humidity regulation, energy storage, thermal management, and water harvesting. In particular, capturing moisture at elevated temperatures is highly desirable to prevent dehydration and to enlarge the tunability of water uptake. However, owing to the thermodynamic limit of conventional materials, sorbents inevitably tend to capture less water vapor at higher temperatures, impeding their broad applications. Here, an inverse temperature dependence of water sorption in poly(ethylene glycol) (PEG) hydrogels, where their water uptake can be doubled with increasing temperature from 25 to 50 °C, is reported. With mechanistic modeling of water–polymer interactions, this unusual water sorption is attributed to the first‐order phase transformation of PEG structures, and the key parameters for a more generalized strategy in materials development are identified. This work elucidates a new regime of water sorption with an unusual temperature dependence, enabling a promising engineering space for harnessing moisture and heat.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Photoenzymatic Hydrogenation of Heteroaromatic Olefins Using ‘Ene’‐Reductases with Photoredox Catalysts

Abstract Flavin‐dependent ‘ene’‐reductases (EREDs) are highly selective catalysts for the asymmetric reduction of activated alkenes. This function is, however, limited to enones, enoates, and nitroalkenes using the native hydride transfer mechanism. Here we demonstrate that EREDs can reduce vinyl pyridines when irradiated with visible light in the presence of a photoredox catalyst. Experimental evidence suggests the reaction proceeds via a radical mechanism where the vinyl pyridine is reduced to the corresponding neutral benzylic radical in solution. DFT calculations reveal this radical to be “dynamically stable”, suggesting it is sufficiently long‐lived to diffuse into the enzyme active site for stereoselective hydrogen atom transfer. This reduction mechanism is distinct from the native one, highlighting the opportunity to expand the synthetic capabilities of existing enzyme platforms by exploiting new mechanistic models.

Nakano, Yuji↗
DOE OSTI2024

The complex circuitry of interactions determining coexistence among plants and mycorrhizal fungi

We present a mechanistic model of coexistence among a mycorrhizal fungus and one or two plant species that compete for a single nutrient. Plant–fungal coexistence is more likely if the fungus is better at extracting the environmental nutrient than the plant and the fungus acquires carbon from the plant above a minimum rate. When they coexist, their interaction can shift from mutualistic to parasitic at high nutrient availability. The fungus is a second nutrient source for plants and can promote the coexistence of two plant competitors if one is better at environmental nutrient extraction and the other is better at acquiring the nutrient from the fungus. Because it extracts carbon from both plants, the fungus also serves as a conduit of apparent competition between the plants. Consequently, the plant with the lower environmental nutrient extraction rate can drive the plant with the higher environmental nutrient extraction rate extinct at high carbon supply rates. Furthermore, this model illustrates mechanisms to explain several observed patterns, including shifts in plant–mycorrhizal growth responses and coexistence along nutrient gradients, equivocal results among experiments testing the effect of mycorrhizal fungi on plant diversity, and differences in plant diversity among ecosystems dominated by different mycorrhizal groups.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of protein–ligand binding interactions of enoyl-ACP reductase ( FabI ) by native MS reveals allosteric effects of coenzymes and the inhibitor triclosan

The enzyme enoyl-ACP reductase (also called FabI in bacteria) is an essential member of the fatty acid synthase II pathway in plants and bacteria. This enzyme is the target of the antibacterial drug triclosan and has been the subject of extensive studies for the past 20 years. Despite the large number of reports describing the biochemistry of this enzyme, there have been no studies that provided direct observation of the protein and its various ligands. In this paper we describe the use of native MS to characterize the protein–ligand interactions of FabI with its coenzymes NAD + and NADH and with the inhibitor triclosan. Measurements of the gas-phase affinities of the enzyme for these ligands yielded values that are in close agreement with solution-phase affinity measurements. Additionally, FabI is a homotetramer and we were able to measure the affinity of each subunit for each coenzyme, which revealed that both coenzymes exhibit a positive homotropic allosteric effect. An allosteric effect was also observed in association with the inhibitor triclosan. These observations provide new insights into this well-studied enzyme and suggest that there may still be gaps in the existing mechanistic models that explain FabI inhibition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Measurement of hybrid rocket solid fuel regression rate for a slab burner using deep learning

This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary layer combustion in hybrid rockets by the measurement of fuel regression rates. A DSLR camera with a high intensity flash is used to capture images throughout the burn and the images are then used to find the fuel boundary to calculate the regression rate. A U-net convolutional neural network architecture is explored to segment the fuel from the experimental images. Here, a Monte-Carlo Dropout process is used to quantify the regression rate uncertainty produced from the network. The U-net computed regression rates are compared with values from other techniques from literature and show error less than 10%. An oxidizer flux dependency study is performed and shows the U-net predictions of regression rates are accurate and independent of the oxidizer flux, when the images in the training set are not over-saturated. Training with monochrome images is explored and is not successful at predicting the fuel regression rate from images with high noise. The network is superior at filtering out noise introduced by soot, pitting, and wax deposition on the chamber glass as well as the flame when compared to traditional image processing techniques, such as threshold binary conversion and spatial filtering. U-net consistently provides low error image segmentations to allow accurate computation of the regression rate of the fuel.

42 ENGINEERING↗
DOE OSTI2021

Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

Phenological transitions determine the timing of changes in land surface properties and the seasonality of exchanges of biosphere-atmosphere energy, water, and carbon. Accurate mechanistic modeling of phenological processes is therefore critical to understand and correctly predict terrestrial ecosystem feedbacks with changing atmospheric and climate conditions. However, the phenological components in the land model of the US Department of Energy's (DOE) Energy Exascale Earth System Model (ELM of E3SM) were previously unable to accurately capture the observed phenological responses to environmental conditions in a well-studied boreal peatland forest. In this research, we introduced new seasonal-deciduous phenology schemes into version 1.0 of ELM and evaluated their performance against the PhenoCam observations at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in northern Minnesota from 2015 to 2018. We found that phenology simulated by the revised ELM (i.e., earlier spring onsets and stronger warming responses of spring onsets and autumn senescence) was closer to observations than simulations from the original algorithms for both the deciduous conifer (Larix laricina) and mixed shrub layers. Moreover, the revised ELM generally produced higher carbon and water fluxes (e.g., photosynthesis and evapotranspiration) during the growing season and stronger flux responses to warming than the default ELM. A parameter sensitivity analysis further indicated the significant contribution of phenology parameters to uncertainty in key carbon and water cycle variables, underscoring the importance of precise phenology parameterization. Furthermore, this phenological modeling effort demonstrates the potential to enhance the E3SM representation of land-climate interactions at broader spatiotemporal scales, especially under anticipated elevated CO 2 and warming conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A macro-scale ruck and tuck mechanism for deformation in ion-irradiated polycrystalline graphite

A vein structure, which becomes more pronounced with increasing ion dose, was found on the surface of polycrystalline HOPG (highly oriented pyrolytic graphite) implanted by ex situ C + (up to 1.8 × 10 17 ions/cm 2 ), and in situ Ar + in a transmission electron microscope (TEM). These veins are found to be independent of the crystallographic orientations and are associated with the formation of pores. Underneath the veins, a triangular-shaped core was formed with the graphite platelet inside the core displaced up towards the surface. A macro-scale ‘ruck&tuck’ geometry was thus generated at these triangle structure boundaries. Progressive movement of dislocations along basal planes during irradiation was observed, and a mechanistic model was proposed on this basis to explain the vein formation. A small increase of c-spacing was observed with irradiation but it is believed that macro-scale vein formation plays a more vital role in the dimensional and property changes in polycrystalline graphite, especially when a stress gradient is present. Here, the model proposed also explains the change of thermal expansion in HOPG with irradiation. Together with Heggie’s ‘ruck&tuck’ and Barsoum’s ‘ripplocations’ models, the present model is considered to have provided an additional experimentally proven mechanism responsible for irradiation behaviour in graphite materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗
DOE OSTI2021

Water vapor oxidation of SiC layer in surrogate TRISO fuel particles

Under accidental conditions for high temperature gas-cooled reactors (HTGR), the SiC layer in tri-structural-isotropic (TRISO) fuel particles can be exposed to water vapor. In this study, oxidation behaviors of surrogate TRISO fuel particles were investigated in a He-20 vol% water vapor mixed atmosphere at temperatures up to 1600 °C. The growth of the crystalline oxide passivation layer with cracks and pores followed a parabolic law with time, where the maximum was 2.3 μm at 1600 °C. The oxide layer and the SiC surface under the oxide became flattened with increasing temperature, as a function of the silica viscosity and the diffusion path of water vapor. Volatilization of the oxide layer was analyzed using a mechanistic model that an inert gas in oxidizing atmospheres could influence the magnitude of volatilization. The fracture load and strength of the oxidized and thinned SiC layer were numerically estimated to decrease from 2.27 to 1.69 N and from 317 to 299 MPa, respectively, with the SiC thickness decrease from 35 to 32 μm. This prediction indicates that the oxidized SiC layer should retain fission products. Additionally, the mechanical integrity of each layer in the TRISO fuel particle after oxidation was evaluated. The results in this work provide important data for the safety analysis of accidental scenarios in HTGRs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Standards, dissemination, and best practices in systems biology

In this study, the reproducibility of scientific research is crucial to the success of the scientific method. Here, we review the current best practices when publishing mechanistic models in systems biology. We recommend, where possible, to use software engineering strategies such as testing, verification, validation, documentation, versioning, iterative development, and continuous integration. In addition, adhering to the Findable, Accessible, Interoperable, and Reusable modeling principles allows other scientists to collaborate and build off of each other’s work. Existing standards such as Systems Biology Markup Language, CellML, or Simulation Experiment Description Markup Language can greatly improve the likelihood that a published model is reproducible, especially if such models are deposited in well-established model repositories. Where models are published in executable programming languages, the source code and their data should be published as open-source in public code repositories together with any documentation and testing code. For complex models, we recommend container-based solutions where any software dependencies and the run-time context can be easily replicated.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing

Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.

Petzold, Christopher J↗
DOE OSTI2026

Analysis of synergies in converting underground storage sites: Natural gas to hydrogen with co-located CO2 storage

This study examines the untapped potential of synergistically converting underground natural gas storage (UGS) into underground hydrogen storage (UHS) with co-located CO2 storage. Current approaches to subsurface storage technology (SST) development often prioritise single-use scenarios, overlooking the benefits of integrating multiple technologies. We investigate converting UGS assets into UHS through gradual cushion-gas injection over multiple years, rather than injecting all cushion gas in the first year, and include on-site CO2 storage to offset site emissions. Mechanistic modelling shows this gradual transition reduces the Levelised Cost of Storage (LCOS) of H2 by 1.2-13.1% while retaining energy output within 3% of the current status quo. We also show that combined UHS and CO2 storage hubs can reduce the LCOS of CO2 by 45-77% for only a 3-10% increase in hydrogen LCOS relative to the status quo. This analysis framework may help future-proof SST sites and support a resilient, economically beneficial energy transition.

Mouli-Castillo, Julien↗
DOE OSTI2025

Surface intermediates identified using IR spectroscopy during the catalytic oxidation of C 2 H 6 on IrO 2 (1 1 0) at near-ambient pressures

Characterizing surface intermediates during catalysis is essential for developing mechanistic models of catalytic reactions and for identifying rate-controlling steps. Here, in this work, we used polarization-dependent reflection absorption infrared spectroscopy (PD-RAIRS) to investigate surface intermediates that form on IrO 2 (1 1 0) during the catalytic oxidation of C 2 H 6 at pressures near 0.5 Torr. Our results show that adsorbed CO and HCO 2 are the only intermediates detectable with PD-RAIRS across a wide range of temperatures and reactant compositions during complete C 2 H 6 oxidation, giving rise to dominant peaks at about 2093 and 1310 cm −1 , respectively. These assignments were corroborated by RAIRS measurements following CO and HCOOH adsorption in ultrahigh vacuum, RAIRS with C 2 H 6 – 18 O 2 mixtures during catalysis and vibrational frequencies and IR intensities computed using density functional theory. We find that increasing the C 2 H 6 mole fraction in the reaction mixture raises the CO surface coverage relative to HCO 2 , correlating with increasing catalytic oxidation rates. The formation of CO and HCO 2 surface species at temperatures well below catalytic ignition indicates that the overall rate of C 2 H 6 oxidation on IrO 2 (1 1 0) is governed by steps late in the reaction sequence, such as H 2 O formation, CO oxidation and HCO 2 dehydrogenation. These findings provide key insight into the mechanism of alkane oxidation on IrO 2 (1 1 0) and valuable input for first-principles microkinetic modeling.

Pope, Connor [Univ. of Florida, Gainesville, FL (U↗
DOE OSTI2022

Irradiation-induced chemical disordering in ceramics: The case of SiC

Chemical disordering is one feature of damage that occurs in irradiation environments and is common in ceramic compounds. This paper reviews irradiation-induced chemical disordering in SiC-based materials at elevated temperatures. Here the results were obtained using advanced analytical tools to characterize atomistic defects and to evaluate the chemistry of defect clusters and homonuclear bond structures. Finally, this paper demonstrates that chemical disordering is crucial to understanding microstructural stability and establishing a mechanistic modeling of microstructural evolution of irradiated SiC.

36 MATERIALS SCIENCE↗