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Results for “Computational thermodynamics”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A mathematical framework for thermodynamic computing with applications to chemical reaction networks

The widespread adoption of energy-intensive computing applications has led to a growing need for energy-efficient computing approaches. Thermodynamic computing offers a promising approach for low-energy computation by leveraging the intrinsic computational capabilities of physical, chemical, or biological systems. However, the mathematical foundations of thermodynamic computing require further development to fully realize the potential energy efficiencies, as well as to assess factors like noise and operational speed. In this paper, we establish a mathematical framework for utilizing thermodynamic processes to perform fundamental operations, including addition, subtraction, multiplication, and division. We highlight the use of chemical reactions as potential computational units and explore synthetic chemical and biochemical systems as practical implementations. Additionally, we demonstrate how these principles can be applied to solving complex mathematical problems, such as ordinary differential equations (ODEs) and suggest the necessary components to implement the thermodynamic computing framework using chemical reactions based in a microfluidic device. This work enhances our understanding of thermodynamic processes for natural computing as a basis for scalable, energy-efficient computation in paradigm disruptive next-generation systems.

Cannon, William R. [Pacific Northwest National Lab↗
DOE OSTI2020

Computational thermodynamics and its applications

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonlinear thermodynamic computing out of equilibrium

We present the design for a thermodynamic computer that can perform arbitrary nonlinear calculations in or out of equilibrium. Simple thermodynamic circuits, fluctuating degrees of freedom in contact with a thermal bath and confined by a quartic potential, display an activity that is a nonlinear function of their input. Such circuits can therefore be regarded as thermodynamic neurons, and can serve as the building blocks of networked structures that act as thermodynamic neural networks, universal function approximators whose operation is powered by thermal fluctuations. We simulate a digital model of a thermodynamic neural network, and show that its parameters can be adjusted by genetic algorithm to perform nonlinear calculations at specified observation times, regardless of whether the system has attained thermal equilibrium. This work expands the field of thermodynamic computing beyond the regime of thermal equilibrium, enabling fully nonlinear computations, analogous to those performed by classical neural networks, at specified observation times.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
DOE OSTI2026

Generative Thermodynamic Computing

Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.

Whitelam, Stephen [Lawrence Berkeley National Labo↗
NASA NTRS1994

Computing Thermodynamic And Transport Properties Of Air

EQAIRS computer program is set of FORTRAN 77 routines for computing thermodynamic and transport properties of equilibrium air for temperatures from 100 to 30,000 K. Computes properties from 11-species, curve-fit mathematical model. Successfully implemented on DEC VAX-series computer running VMS, Sun4-series computer running SunOS, and IBM PC-compatible computer running MS-DOS.

Thompson, Richard A.↗
DOE OSTI2020

Coupling computational thermodynamics with density-function-theory based calculations to design L12 precipitates in Fe Ni based alloys

Achieving a high-volume fraction of thermodynamically stable L12-type precipitates that are resistant to coarsening is of great importance for the development of low-cost FeNi based austenitic steels. With the aid of computational thermodynamics, this work designed two model alloys: Fe-37.4Ni-6.1Al-2.9Ti (FNAT) and Fe-45.2Ni-5.9Al-8.5Si (FNAS). Both alloys were designed to contain a similar amount of L1 2 precipitate in Fe-Ni matrix without forming other precipitates. Density-Function-Theory (DFT) calculation was coupled with computational thermodynamics to predict the critical radius at which the precipitates change shape from spherical to cuboidal. The calculation results suggest that critical radius for the FNAT alloy is about two orders of magnitude larger than that for the FeNiAlSi alloy. Phase stability and morphology of the L1 2 precipitates in these two alloys were experimentally investigated through X-ray diffraction, atom probe tomography, and scanning and transmission electron microscopy. The L1 2 precipitates in the FeNiAlSi system were found to be cuboidal and rod shaped, with much larger size than the spherical ones in the FeNiAlTi system, agreeing with the calculation results. This work suggested that coupling computational thermodynamics with DFT calculations can be reliably used to design L1 2 precipitates in FeNi based alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational thermodynamic study of SiC chemical vapor deposition from MTS-H 2

This study focuses on the computational thermodynamic analysis of the chemical vapor deposition (CVD) of SiC from the methyltrichlorosilane-hydrogen (MTS-H 2 ) using up-to-date thermodynamic databases. High-resolution computation has been performed with the fine intervals of temperature and pressure at the various H 2 /MTS ratios of interest to systematically investigate the deposition condition range (800 to 1600°C, 0 to 26 664 Pa, and H 2 /MTS ratios of 0.1 to 100) to guide experimental exploration. The influence of deposition parameters on the compositions and phase stabilities of the deposit and gas phase pertinent to vapor processing is elucidated. Low pressure and medium temperatures (1000 to 1400°C) are beneficial to reaching a higher SiC deposition efficiency and provide an optimal window for preparing a high-purity (>99 wt.% SiC) deposit. This optimal processing window expands significantly with an increasing H 2 /MTS ratio (<20). These results are supported by a number of previous theoretical and experimental observations. The mass fraction of SiC in deposit is proposed as an additional perspective to understand the discrepancy between thermodynamic calculation and experimental observation of pure CVD SiC at low H 2 /MTS ratios.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Chapter 4 - Research Tools: Microstructure, Mechanical Properties, and Computational Thermodynamics

The purpose of this Chapter is to provide an overview of the research tools that are available to evaluate the response of materials that are subject to atomic displacements caused by fast particle irradiation. The major focus is on metals employed in structural components in operating or planned nuclear fission and fusion reactors. Understanding, predicting and characterising the changes in material properties under irradiation requires the ability to characterise the irradiation-induced microstructure at and above the atomic scale, and the ability to relate such changes to the observed degradation in performance sustaining properties. Thus, any discussion of research tools necessarily involves microstructural characterization techniques and mechanical property characterization techniques. In addition, computational thermodynamics (and related multiscale, multiphysics modeling) can also be considered characterization tools since they enable the study of the thermodynamically and kinetically mediated mechanisms (influenced by the irradiation environment) that affect microstructural evolution. Hence, this chapter also contains a brief review of computational thermodynamics.

English, Colin A.↗
NASA NTRS2001

Computational Thermodynamic Study to Predict Complex Phase Equilibria in the Nickel-Base Superalloy Rene N6

A previous study by Ritzert et al. on the formation and prediction of topologically closed packed (TCP) phases in the nickel-base superalloy Rene' N6 is re-examined with computational thermodynamics. The experimental data on phase distribution in forty-four alloys with a composition within the patent limits of the nickel-base superalloy Rene' N6 provide a good basis for comparison to and validation of a commercial nickel superalloy database used with ThermoCalc. Volume fraction of the phases and partitioning of the elements are determined for the forty-four alloys in this dataset. The baseline heat treatment of 400 h at 1366 K was used. This composition set is particularly interesting since small composition differences lead to dramatic changes in phase composition. In general the calculated values follow the experimental trends. However, the calculations indicated no TCP phase formation when the experimental measurements gave a volume percent of TCP phase less than 2 percent. When TCP phases were predicted, the calculations under-predict the volume percent of TCP phases by a factor of 2 to 8. The calculated compositions of the gamma and gamma' phases show fair agreement with the measurements. However, the calculated compositions of the P Phase do not agree with those measured. This may be due to inaccuracies in the model parameters for P phase and/or issues with the microprobe analyses of these phases. In addition, phase fraction diagrams and sigma and P phase solvus temperatures are calculated for each of the alloys. These calculations indicate that P phase is the primary TCP phase formed for the alloys considered here at 1366 K. Finally, a series of isopleths are calculated for each of the seven alloying elements. These show the effect of each alloying element on creating TCP phases.

Copland, Evan H.↗
DOE OSTI2018

Development of novel Cu-Cr-Nb-Zr alloys with the aid of computational thermodynamics

Multi-modal precipitate distribution in the microstructure, with coarse precipitates pinning the grain boundaries and finer precipitates strengthening the matrix, is beneficial to suppress grain boundary sliding and dislocation creep, respectively, of structural materials. However, achievement of a multi-modal precipitate distribution remains a challenge in developing creep-resistant advanced Cu alloys while retaining high strength and high conductivity at elevated temperature. This work overcame this challenge with the aid of computational thermodynamics. Thermodynamic models for Gibbs energy functions of phases in the Cu-Cr-Nb-Zr system have been developed in this study. These models were then used to calculate solidification paths and phase equilibria at different temperatures, guiding the design of chemical composition and heat treatment parameters of novel copper alloys with a target multi-modal distribution of precipitates. The new alloy, fabricated through traditional ingot metallurgy method, has achieved the desired microstructure as validated by optical and transmission electron microscopy. Electrical conductivity and mechanical properties were screened and compared with the existing commercial Cu alloys.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Computing Thermodynamics Of Cryostorage Tanks In Orbit

No-vent filling, boiloff, and other phenomena predicted. Cryogenic On-Orbit Liquid Analytical Tool (COOLANT) computer program developed to analyze thermodynamic processes required in maintaining and utilizing cryogen depot tank in microgravity environment. Code contains four major analysis modules, tank-geometry module, and data base of properties of fluids and other materials. COOLANT is modular, so algorithms and data bases upgraded and expanded as required. Written in FORTRAN 77.

Brown, N.↗