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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.

42 ENGINEERING↗
DOE OSTI2024

Site heterogeneity and broad surface-binding isotherms in modern catalysis: Building intuition beyond the Sabatier principle

Learning the science of heterogeneous catalysis and electrocatalysis always starts with the simple case of a flat, uniform surface with an ideal adsorbate. It has of course been recognized for a century that real catalysts are more complicated. For the increasingly complex catalysts of the 21st century, this Perspective argues that surface heterogeneity and non-ideal binding isotherms are central features, and their implications need to be incorporated in current thinking. A variety of systems are described herein where catalyst complexity leads to broad, non-Langmuirian surface isotherms for the binding of hydrogen atoms – and this occurs even for ideal, flat Pt(111) surfaces. Modern catalysis employs nanoscale materials whose surfaces have substantial step, edge, corner, impurity, and other defect sites, and they increasingly have both metallic and non-metallic elements M n X m , including metal oxides, chalcogenides, pnictides, carbides, doped carbons, etc. The surfaces of such catalysts are often not crystal facets of the bulk phase underneath, and they typically have a variety of potential active sites. Catalytic surfaces in operando are often non-stoichiometric, amorphous, dynamic, and impure, and often vary from one part of the surface to another. Understanding of the issues that arise at such nanoscale, multi-element catalysts is just beginning to emerge. Yet these catalysts are widely discussed using Brønsted/Bell-Evans-Polanyi (BEP) relations, volcano plots, Tafel slopes, the Butler-Volmer equation, and other linear free energy relations (LFERs), which all depend on the implicit assumption that the active sites are “similar” and that surface adsorption is close to ideal. These assumptions underly the ubiquitous intuition based on the Sabatier Principle, that the fastest catalysis will occur when key intermediates have free energies of adsorption that are not too strong nor too weak. Current catalysis research often aims to minimize the complexity of non-ideal isotherms through experimental and computational design (e.g., the use of single crystal surfaces), and these studies are the foundation of the field. In contrast, this Perspective argues that the heterogeneity of binding sites and binding energies is an inherent strength of these catalysts. Here, this diversity makes many nanoscale catalysts inherently a high-throughput screen wrapped in a tiny package. Only by making the heterogeneity part of the foundation of catalysis models, sorting the types of active sites and dissecting non-ideal binding isotherms, will modern catalysis learn to harness the inherent diversity of real catalysts. Controlling and exploiting diversity rather than avoiding it will help to optimize complex modern catalysts and catalytic conditions.

Mayer, James M.↗
DOE OSTI2023

Controlled Self-Assembly of Gold Nanotetrahedra into Quasicrystals and Complex Periodic Supracrystals

The self-assembly of shape-anisotropic nanocrystals into large-scale structures is a versatile and scalable approach to creating multifunctional materials. The tetrahedral geometry is ubiquitous in natural and manmade materials, yet regular tetrahedra present a formidable challenge in understanding their self-assembly behavior as they do not tile space. Here, we report diverse supracrystals from gold nanotetrahedra including the quasicrystal (QC) and the dimer packing predicted more than a decade ago and hitherto unknown phases. We solve the complex three-dimensional (3D) structure of the QC by a combination of electron microscopy, tomography, and synchrotron X-ray scattering. Nanotetrahedron vertex sharpness, surface ligands, and assembly conditions work in concert to regulate supracrystal structure. We also discover that the surface curvature of supracrystals can induce structural changes of the QC tiling and eventually, for small supracrystals with high curvature, stabilize a hexagonal approximant. Finally, our findings bridge the gap between computational design and experimental realization of soft matter assemblies and demonstrate the importance of accurate control over nanocrystal attributes and the assembly conditions to realize increasingly complex nanopolyhedron supracrystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes

Quantification of shape changes in nature-inspired soft material architectures of stimuli-sensitive polymers is critical for controlling their properties but is challenging due to their softness and flexibility. Here, we have computationally designed uniquely shaped bottlebrushes of a thermosensitive polymer, poly(N-isopropylacrylamide) (PNIPAM), by controlling the length of side chains along the backbone. Coarse-grained molecular dynamics simulations of solvated bottlebrushes were performed below and above the lower critical solution temperature of PNIPAM. Conventional analyses (free volume, asphericity, etc.) show that lengths of side chains and their immediate environments dictate the compactness and bending in these architectures. We further developed 100 unique convolutional neural network models that captured molecular-level features and generated a statistically significant quantification of the similarity between different shapes. Thus, our study provides insights into the shapes of complex architectures as well as a general method to analyze them. The shapes presented here may inspire the synthesis of new bottlebrushes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unifying thermochemistry concepts in computational heterogeneous catalysis

Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange–correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Structure prediction of porous organic crystals

In this work, we explore the possibility of applying automated crystal structure prediction to reproduce the experimentally identified metastable porous polymorphs. Using our recently developed High-Throughput Organic Crystal Structure Prediction ( HTOCSP ) framework, we conducted a systematic study on five representative organic crystalline systems including hydrogen-bonded frameworks (HOFs), featured by the presence of significant porosity, in conjunction with different choices of energy models from classical, machine learning force fields, tight binding to density functional theory. Our results suggest that the current structure generation framework, with careful selection of symmetry conditions, is likely to generate rather complex and abundant metastable crystal candidates for porous crystals. In conjunction with the recent advance in universal machine learning force fields, it becomes possible to identify experimental structures as the energetically favorable candidates from a simple energy versus density analysis, thus paving the way for computational design of complex porous materials with the target systems prior to the experimental synthesis and characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Decomposition characteristics of C4F7N-based SF6-alternative gas mixtures

C4F7N [2,3,3,3-tetrafluoro-2-(trifluoromethyl)propanenitrile]/CO2 gas mixtures are being developed as an eco-friendly electrical insulator to replace SF6, the most potent greenhouse industrial gaseous dielectric. However, recent studies have reported complicated and often conflicting decomposition pathways for C4F7N/CO2 gas mixtures, which has raised concerns. In this work, the decomposition characteristics of C4F7N/CO2 gas mixtures were studied comprehensively by both designed computations and experiments. Computations were performed starting from fundamental propositions of C4F7N/CO2 decompositions, which were further experimentally verified by pyrolysis, long-term thermal aging with/without catalytic materials (industrial-grade molecular sieves 4A), and electrical decomposition by spark discharge. The results of both computations and experiments suggest that in an ideal thermal decomposition, C4F7N is likely to decompose into C2F6 and small fluoronitriles first at high temperatures. The generation of C3F6 and C2N2 from C4F7N thermal decomposition at lower temperatures appears because of the catalytic effect of incompatible materials, for example, the industrial-grade molecular sieves 4A that we tested. The electron impact dissociation of C4F7N plays an important role in C4F7N electrical decomposition, leading to additional formation of distinctive small molecules of CF4 and C2N2 of low concentrations. It was pointed out based on a real arcing test in a load disconnector that the decomposition of C4F7N gas mixtures in real applications will be at a much moderate and manageable rate than what was obtained from the highly accelerated laboratory tests presented in this work. The signatures of decomposition products extracted in this study provide invaluable guidance for developing decomposition-based diagnosis and fixation of decomposition byproducts toward SF6-free power grids.

Physics↗
DOE OSTI2023

A prediction of the thermodynamic, thermophysical, and mechanical properties of CrTaO 4 from first principles

It is reported that the self-forming CrTaO 4 oxide scale can protect refractory high-entropy alloys from oxidation, superior to Cr 2 O 3 . In this paper, the phase stability, mechanical, and thermal properties of three polymorphous phases of CrTaO 4 are systematically investigated from first-principles density functional theory calculations. The mechanical properties predicted using the strain–energy methods indicated that all three phases are mechanically stable. The temperature dependence of elastic constants and polycrystalline moduli of three phases demonstrated the thermal softening as temperature increase. The Helmholtz-free energies as a function of volume and temperature are derived from phonon dispersions within the quasi-harmonic approximation at six strained volumes. The calculated apparent bulk coefficients of thermal expansion of these three phases are evaluated, the highest value approximately 13.4× 10 –6 K –1 within a temperature range of 500–2000 K for the rutile I4 1 md phase. The lattice thermal conductivity calculated by the Debye–Callaway model suggested that the rutile type I4 1 md phase has the lowest value of approximately 2.1 W/m/K at 1800 K. The other two phases, C2/m and P2/c, exhibit higher values due to relatively lower Grüneisen parameters and larger phonon velocities. The melting point of CrTaO 4 is predicted to be between 1975 and 2449 K using ab initio molecular dynamics simulations. Finally, this work provides a comprehensive theoretical understanding of the thermodynamic, mechanical, and thermal properties for the new material CrTaO 4 and serves as an example of a viable computational design strategy for improved oxidation resistance of refractory alloys at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Equivalent Properties of Interfacial Void Defects at the CFRTP-adhesive Interface and Their Detrimental Effects on the Bonding Performance of Metal-CFRTP Dissimilar Joints

This paper revealed the detrimental effects of micro-scale air interfacial voids on the debonding at the interface of carbon-fiber-reinforced polyphthalamide (CFRPPA) and thermoset adhesive, representing a weak adherend-adhesive interface, within a dissimilar joint made of an aluminum alloy and a CFRPPA. The reduced lap shear strength of the joint, due to different void area fractions at the CFRPPA-adhesive interface, can be computationally described by using equivalent interfacial properties in the modeling to avoid the explicit modeling of the micro-scale interfacial voids. Such equivalent interfacial properties (e.g., interfacial normal strength, etc.) was found to have a non-linear relationship with respect to interfacial void area fraction as well as lap shear strength. This work has practical applications by utilizing equivalent interfacial properties for the analytical and/or computational design(s) of adhesively bonded joints.

Qiao, Yao↗
DOE OSTI2022

Lattice Optimization for Porous Electrode

This code performs an optimization over the structure of a porous electrode formed from a lattice of unit cells. This is a steepest descent version of the code used in: V. A. Beck, J. J. Wong, C. F. Jekel, D. A. Tortorelli, S. E. Baker, E. B. Duoss and M. A. Worsley, Computational design of microarchitected porous electrodes for redox flow batteries, J. Power Sources, 2021, 512, 230453.

Wong, JonathanJ↗
DOE OSTI2023

Gene Tuples ArraNGed in overLapping Elements

GENTANGLE is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome that can be used to design and test gene entanglements for new microbial engineering projects using arbitrary sets of user specified gene pairs.

Leonard, SeanP↗
DOE OSTI2020

(U) PRAD0697 & PRAD0698: Complex Loading of CeO₂ Powder

Cerium(IV) oxide (CeO₂) powder is shock compressed using the Precision High Energy-density Liner Implosion eXperiment (PHELIX) platform. Experimental results are compared against several modeling approaches. Compaction behavior is best captured with a P-∝ model, which calculates CeO₂ powder bulk densities within 80-99% of experimental values but overpredicts densi cation at the cylindrical target's outer radius and center by up to 20%. Preliminary calculations suggest that accuracy could be increased with the inclusion of a coupled strength model. Several common computational modeling approaches for the shock compression response of granular materials and the magnetohydrodynamic (MHD) force upon the impactor/liner in pulsed power compression experiments are investigated and analyzed for their validity. The Bi-linear Ramp, P-∝ PACXP, and P-∝ Menikoff-Kober continuum compaction models are calibrated to planar impact Hugoniot data for CeO₂ powder and used to predict the powder's shock compaction response under non-planar shock wave compression. MHD calculations of the PHELIX pulsed power driver are performed using an idealized resistor-inductor-capacitor (RLC) circuit calibrated to previous experiments. All simulations are performed using the LANL code FLAG. Two validation experiments are computationally designed using the calibrated compaction and circuit models, executed using the PHELIX platform on CeO₂ targets with initial porous densities of 3.95 and 4.03 g/cm³, measured with proton radiography, and analyzed against the model predictions. The two P-∝ models more accurately describe CeO₂ powder densi cation than the Bi-linear Ramp model. However, the two P-∝ models overpredict bulk density of the shock compressed CeO₂ powder by up to 20% when the appropriate impact velocities are applied. MHD calculations for both validation experiments underpredict liner impact velocities by 4-11% when using the idealized RLC circuit model calibrated to previous experiments. Compensating underpredictions of impact velocity and overpredictions of powder densication lead to a false accuracy in pre-shot calculations compared to experimental data. To improve correlation between simulations and experiments, the following improvements are suggested: 1. A coupled strength model for CeO₂ powder that updates strength as a function of porosity and applied stress. 2. An improved MHD circuit model that more accurately captures the PHELIX machine.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic, Adaptive, Systems and Materials: Complex, Simple and Emergent Behaviors

This program has been funded by DoE/BES for twenty years. It has moved into and out of various subjects as it has developed, but it has retained its focus on complexity and complex systems. The project has evolved in the following way: Self-Assembly and Biomimetic Self-Assembly: All self-assembling systems depend upon a minimum of two types of interaction: a repulsion and an attraction. For the familiar molecular systems, attractive interactions are typically hydrogen bonds and electrostatic interactions. Repulsive interactions include steric effects, hydrophobic effects (in biological systems), and charge-charge repulsion. We have expanded this repertoire to include surface interactions, magnetic interactions, and others. I list these systems in the order in which we have explored them: i) A key emphasis in current work is in understanding how the movement of ions in a magnetic field (the Lorentz effect) interacts with catalytic systems. We have demonstrated that an acceleration in rate of reduction of CO 2 to CO can be accomplished by applying an external magnetic field. This acceleration is largely due to the application of the Lorentz effect on mass transport at the catalyst’s surface. ii) We have also extensively explored the influence of electrostatics, as exhibited in self-assembling systems, by tribocharging. iii) Another key system involves surface tension effects; examples include interactions between heavy particles floating at a liquid-air interface, and interacting by changes in surface area; interactions of bubbles and bubble rafts, behaviors of bubble trains in microfluidic networks, and behaviors of microorganisms in constraining environments. iv) This work has intentionally de-emphasized biological systems; but it does include some work on protein-ligand interactions and interactions among microorganisms. v) We have also explored applications of some of these effects, these explorations include bubble rafts as diffraction gratings, exploration of the structures that can be obtained by tribocharging and uses of these structures in exploring nucleation and melting of crystals. vi) Although not a major focus of this work, several other topics have emerged and offer opportunities for future work. These include the behavior of bubble trains and bubble rafts in microfluidic systems. A particularly interesting example is the formation of bubble trains that repeat in the alteration of large and small bubbles according to rules we do not presently understand, but are uniquely large-period oscillating systems. These systems offer a new route into understanding the instabilities of the type represented by oscillations. vii) We have also begun exploratory projects on magnetic levitation (especially to determine molecular density), and information storage (in molecules). Magnetic Levitation: Self-assembling and biomimetic systems require both attraction and repulsion. We have used electrostatics (tribocharging), interfacial free-energies (surface tension and related forces) and others. Potential uses include reconfigurable diffraction gratings and liquid lenses; exploration of mechanisms in tribocharging; tunneling in EGaIn junctions; and bubble trains (especially in micro-fluidic systems). Examples of systems representing these topics is included in the following papers: Complexity: Disks rotating at a water-air interface; Benard-Marangoni effects; Vortex-Crystals from spinning magnetic disks (Marangoni effects); EGaIn Electrode to study quantum tunneling; Self-Assembly of electrostatically-charged metallic spheres (electrets); Dynamically reconfigurable lens; Using computational designs of ligands for enzymes; Electrostatic self-assembly by tribocharging; Monodisperse bubble trains in microchannel systems; Inverted dripping faucet; Flames; Printing of micro-organisms to regenerate the “ink” of printing device; Using micro-organisms to move loads (“microoxen”); Motion of bacterial swarms near surfaces; Making monodisperse particles in microfluidic systems; Coding/decoding of information stored in droplet trains in microfluidic networks; Magnetic levitation; and Information storage. i) Tribocharging. The change in focus of this work on electrets from the fundamentals of charging to applications of these materials in studying self-assembly using electrostatic interactions. ii) Bubbles in Microchannels. The realization that systems of bubbles in microchannels represented a major opportunity to study complexity in a very tractable system, and the development of a semi-quantitative theory of this subject. iii) Flames. The growth of “flames” remains an exploratory subject for the research, although their currently relatively little active work involving it ongoing. iv) Systems with Microorganisms. The removal of work in biological systems from this project. Based on work supported in this program, we now have a significant project on the development of microfluidic tools for studying C. elegans (a nematode), but this work was not appropriate for a program focused on complexity, and we developed separate support for it. (It is, however, an example of successful seeding of a new area by BES.) The work on electrets has gone through a period in which a part of the program was the subject of a MURI; the focus of this work was to develop materials that did not charge electrostatically on friction or contact. The MURI is now over, and the work on dynamic self-assembly (supported by BES) is the major focus. “Flames” has also enjoyed synergistic support, in terms of a project supported by DARPA on flame suppression (in the absence of extinguishing agents, using acoustic and electrostatic interactions). This work was helpful in understanding some of the basics of flames, but is entirely distinct from the BES focus in complexity. A growing interest is in the Lorentz effect. The Lorentz effect is the force exerted on charged particles (electrons, ions, charged molecules) when they move through a perpendicular magnetic field. The Lorentz effect is almost ubiquitous in modern technology: examples of applications include electric motors, dynamos, cathode ray tubes, many batteries, and most systems that control electrical currents with magnetic forces. We have begun to explore the Lorentz effect in electrochemical systems and heterogeneous catalytic systems involving charged organic species and inorganic ions. This work is still at an early stage, but initial studies that Lorentz effects can be large when ions move through magnetic fields, or magnetic fields move in the presence of ions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling Hydrodynamic Instabilities, Shocks, and Radiation Waves in High Energy Density Experiments [Dissertation]

This thesis presents the computational design, modeling, and analysis of three experiments in high-energy density physics (HEDP), all of them concerning fundamental radiation flows. The first experiment is a laboratory astrophysics experiment to investigate the role of the Kelvin-Helmholtz instability (KHI) in the process of galactic filaments supplying gas to galactic halos. The achieved goal was to provide a first study in which the role of the instability is maximal and predict behavior in future iterations of an experiment accessing a more radiative regime where the role of the instability is stifled. This experiment would help answer how certain galaxies are able to grow so rapidly and produce many stars as the KHI limits this process. The second experiment, COAX, is a radiation flow experiment with a novel spectroscopy diagnostic configuration, designed to spatially measure the temperature of a radiation wave as it travels down a doped foam. A key result of this work was the development of a synthetic spectroscopy application and application of modern spectroscopy comparison techniques to provide our first temperature reconstructions from the experimental data. This experimental platform serves as the launching ground for a number of new experiments that vary the basic premise and thus is foundational to our ongoing research. The final experiment is a full integration of modeling, design, and theoretical development for the Radishock experiment. This experimental platform studies the head-on collision of a radiation wave with a counter-propagating shock, and like COAX, uses spectroscopy to diagnose and detect the interaction. My research analyzes the successful shots, indicating aspects of successful detections and suggests improvements to future iterations of the design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Annual report for DOE VTO

Carbon fiber (CF)/polymer composites are a transformative class of high-performance, lightweight material, where high aspect-ratio CFs reinforce a polymer matrix and exceed the strength of steel alloys at a fraction of the density. Despite the advantages of such a class of material, the broader implementation of CF composites in a range of automotive, aerospace, and energy applications is hindered by limitations of current manufacturing methods. These current techniques (e.g., hand lay-up, wet filament winding) are costly and impose severe limitations on fiber placement, orientation, and angle, and thus a composite’s ultimate properties. Today’s CF composites are expensive to manufacture, limited in form factor, and utilize costly and sub-optimal continuous filament CF. Advanced additive manufacturing (AM) processes, combined with computational design optimization and new approaches to resin development, offer alternative design and manufacturing paradigms that have the realistic potential to lift these constraints. Such integrated AM approaches could thus help to realize the full potential of CF composite materials. One relevant application of CF composite materials where manufacturing constraints limit the cost-benefit ratio is in the manufacture of high-performance composite pressure vessels for onboard compressed natural gas (CNG) storage. Current CNG storage vessels (Types 3–5) are made from load-bearing filament-wound carbon-fiber composite and are ~3.5 times as expensive as an all-metallic Type-1 vessel. This cost is invariably tied to the complex and labor-intensive nature of conventional filament winding processes and the large volumes of expensive high tensile-strength CF tow feedstock required in manufacture. Our proposed approach to CNG storage vessel manufacture is based on a combination of AM technologies for CF composite printing and design optimization tools that were pioneered at Lawrence Livermore National Laboratory (LLNL), with advances in resin/composite formulation enabled by chemical and nano-material modification. Through the successful development of this technology, LLNL seeks to demonstrate the capability for advanced CNG storage vessel manufacture at reduced cost with no reduction in performance versus the most advanced, extant Type-5 designs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Highly Permeable Rubbery Thin Film Composite Membranes for CO2 Capture from Steel Mills

For presentation at the 2024 AIChE Annual Meeting, San Diego, CA, October 27-31, 2024. High-permeance and CO2-selective membranes are needed to make membrane technology economically viable for large-scale deployment of carbon capture from various industrial point sources such as steel mills. Thin film composite (TFC) membranes are necessary for this practical implementation because they can provide high permeance by forming a thin selective layer on top of a porous support layer. This presentation reports the rational design and fabrication of National Energy Technology Laboratory’s highly permeable non-aging TFC membranes achieved by: (1) synthesizing a high-performance rubbery selective material; (2) developing a high-porosity membrane support; (3) optimizing coating methods to assemble the two materials into scalable membranes; and (4) scaling up membrane supports and TFCs via a roll-to-roll process. This talk will also cover the design, computational fluid dynamic simulation, 3D printing, construction, and permeation testing of plate-and-frame membrane modules for an upcoming field demonstration at U. S. Steel’s Edgar Thomson Plant in Braddock, PA.

Zhu, Lingxiang↗
DOE OSTI2023

A fast Monte Carlo cell-by-cell simulation for radiobiological effects in targeted radionuclide therapy using pre-calculated single-particle track standard DNA damage data

Introduction: We developed a new method that drastically speeds up radiobiological Monte Carlo radiation-track-structure (MC-RTS) calculations on a cell-by-cell basis. Methods: The technique is based on random sampling and superposition of single-particle track (SPT) standard DNA damage (SDD) files from a “pre-calculated” data library, constructed using the RTS code TOPAS-nBio, with “time stamps” manually added to incorporate dose-rate effects. This time-stamped SDD file can then be input into MEDRAS, a mechanistic kinetic model that calculates various radiation-induced biological endpoints, such as DNA double-strand breaks (DSBs), misrepairs and chromosomal aberrations, and cell death. As a benchmark validation of the approach, we calculated the predicted energy-dependent DSB yield and the ratio of direct-to-total DNA damage, both of which agreed with published in vitro experimental data. We subsequently applied the method to perform a superfast cell-by-cell simulation of an experimental in vitro system consisting of neuroendocrine tumor cells uniformly incubated with 177 Lu. Results and discussion: The results for residual DSBs, both at 24 and 48 h post-irradiation, are in line with the published literature values. Our work serves as a proof-of-concept demonstration of the feasibility of a cost-effective “in silico clonogenic cell survival assay” for the computational design and development of radiopharmaceuticals and novel radiotherapy treatments more generally.

62 RADIOLOGY AND NUCLEAR MEDICINE↗