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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Electrochemical force microscopy

A system and method for electrochemical force microscopy are provided. The system and method are based on a multidimensional detection scheme that is sensitive to forces experienced by a biased electrode in a solution. The multidimensional approach allows separation of fast processes, such as double layer charging, and charge relaxation, and slow processes, such as diffusion and faradaic reactions, as well as capturing the bias dependence of the response. The time-resolved and bias measurements can also allow probing both linear (small bias range) and non-linear (large bias range) electrochemical regimes and potentially the de-convolution of charge dynamics and diffusion processes from steric effects and electrochemical reactivity.

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

Atomic Diffusion, Segregation, and Grain Boundary Migration in Nickel-Based Alloys from Molecular Dynamics Simulations

Grain boundary diffusion and metal mobility in alloys control material performance in many applications and yet remain poorly understood at a mechanistic level. With advances in accessible time and length scales for computational molecular simulations, and recent force field developments, we now possess tools to help unravel those mechanisms. Using large-scale molecular dynamics simulations, here we examined vacancy-mediated diffusion processes in Ni-5Cr alloy with low and high-energy grain boundaries. We show that atomic diffusion inside the grain boundary plane is about four times higher than bulk diffusion, at any temperature, and exhibits a typical Arrhenius behavior with a very small energy barrier (0~.8 eV for Cr and 0.7 eV for Ni within 1300-1600 K). Additionally, the fastest diffusing species inverts; Cr diffusion was faster than Ni in the bulk but slower in the grain boundaries. This is attributed to the creation of high cohesive energy clusters of Cr at the grain boundary. Grain boundary migration was also observed to be temperature dependent and appears to be two times higher in the 5% Cr alloy than in pure Ni, highlighting the important role of the alloying element on grain boundary motion.

Simonnin, Pauline GN↗
DOE OSTI2018

Tritium Diffusion Pathways in y-LiAlO2 Pellets Used in TPBAR: A First-Principles Density Functional Theory Investigation

With superior thermophysical and thermochemical properties, gamma-LiAlO2 has high compatibility with other blanket materials and is used in the form of an annular pellet in tritium-producing burnable absorber rods (TPBARs) to produce tritium by thermal neutron irradiation of Li-6. In radiation damaged gamma-LiAlO2, different types of vacancies, defects of its constituent elements, and other trapping sites hinder the diffusion process of tritium. In this study, the first-principles density functional theory approach is used to study the diffusion mechanisms of tritium defect and its species, such as interstitial and substitutional tritium defects, oxygen-tritium vacancy defects, and interaction of tritium with oxygen vacancies in defective and nondefective gamma-LiAlO2. The obtained results provide an understanding of how such defects hamper the diffusivity and solubility of tritium. By calculating several different diffusion pathways, our results show that the smallest activation energy barrier is 0.63 eV for substitutional tritium diffusion with a diffusion coefficient of 3.25 X 10(-12) m(2)/s. The smallest oxygen-tritium diffusion barrier is found to be 2.17 eV, which is around 3.5 times higher than the tritium diffusion barrier alone.

Paudel, Hari↗
DOE OSTI2016

A simplified boron diffusion for preparing the silicon single crystal p-n junction as an educational device

The educational method which is including designing, making, and evaluating actual semiconductor devices with learning the theory is one of the best way to obtain the fundamental understanding of the device physics and to cultivate the ability to make unique ideas using the knowledge in the semiconductor device. In this paper, the simplified Boron thermal diffusion process using Sol-Gel material under normal air environment was proposed based on simple hypothesis and the feasibility of the reproducibility and reliability were investigated to simplify the diffusion process for making the educational devices, such as p-n junction, bipolar and pMOS devices. As the result, this method was successfully achieved making p+ region on the surface of the n-type silicon substrates with good reproducibility. And good rectification property of the p-n junctions was obtained successfully. This result indicates that there is a possibility to apply on the process making pMOS or bipolar transistors. It suggests that there is a variety of the possibility of the applications in the educational field to foster an imagination of new devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. In this work, we address two central challenges: clarifying the connections between different deep generative models and deepening our understanding of their learning mechanisms. We focus on Restricted Boltzmann Machines (RBMs), a class of generative models known for their universal approximation capabilities for discrete distributions. By introducing a reciprocal space formulation for RBMs, we reveal a connection between these models, diffusion processes, and systems of coupled bosons. Our analysis shows that at initialization, the RBM operates at a saddle point, where the local curvature is determined by the singular values of the weight matrix, whose distribution follows the Marc̆enko-Pastur law and exhibits rotational symmetry. During training, this rotational symmetry is broken due to hierarchical learning, where different degrees of freedom progressively capture features at multiple levels of abstraction. This leads to a symmetry breaking in the energy landscape, reminiscent of Landau’s theory. This symmetry breaking in the energy landscape is characterized by the singular values and the weight matrix eigenvector matrix. We derive the corresponding free energy in a mean-field approximation. We show that in the limit of infinite size RBM, the reciprocal variables are Gaussian distributed. Our findings indicate that in this regime, there will be some modes for which the diffusion process will not converge to the Boltzmann distribution. To illustrate our results, we trained replicas of RBMs with different hidden layer sizes using the MNIST dataset. Our findings not only bridge the gap between disparate generative frameworks but also shed light on the fundamental processes underpinning learning in deep generative models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Determination of oxygen diffusion kinetics during thin film ruthenium oxidation

In situ X-ray reflectivity was used to reveal oxygen diffusion kinetics for thermal oxidation of polycrystalline ruthenium thin films and accurate determination of activation energies for this process. Diffusion rates in nanometer thin RuO{sub 2} films were found to show Arrhenius behaviour. However, a gradual decrease in diffusion rates was observed with oxide growth, with the activation energy increasing from about 2.1 to 2.4 eV. Further exploration of the Arrhenius pre-exponential factor for diffusion process revealed that oxidation of polycrystalline ruthenium joins the class of materials that obey the Meyer-Neldel rule.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Mutual diffusion of binary liquid mixtures containing methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride

Mutual diffusion coefficients of all 20 binary liquid mixtures that can be formed out of methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride without a miscibility gap are studied at ambient conditions of temperature and pressure in the entire composition range. The considered mixtures show a varying mixing behavior from almost ideal to strongly non-ideal. Predictive molecular dynamics simulations employing the Green-Kubo formalism are carried out. Radial distribution functions are analyzed to gain an understanding of the liquid structure influencing the diffusion processes. It is shown that cluster formation in mixtures containing one alcoholic component has a significant impact on the diffusion process. The estimation of the thermodynamic factor from experimental vapor-liquid equilibrium data is investigated, considering three excess Gibbs energy models, i.e., Wilson, NRTL, and UNIQUAC. It is found that the Wilson model yields the thermodynamic factor that best suits the simulation results for the prediction of the Fick diffusion coefficient. Four semi-empirical methods for the prediction of the self-diffusion coefficients and nine predictive equations for the Fick diffusion coefficient are assessed and it is found that methods based on local composition models are more reliable. Finally, the shear viscosity and thermal conductivity are predicted and in most cases favorably compared with experimental literature values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

The large deviation principle and steady-state fluctuation theorem for the entropy production rate of a stochastic process in magnetic fields

Fluctuation theorem is one of the major achievements in the field of nonequilibrium statistical mechanics during the past two decades. There exist very few results for steady-state fluctuation theorem of sample entropy production rate in terms of large deviation principle for diffusion processes due to the technical difficulties. Here we give a proof for the steady-state fluctuation theorem of a diffusion process in magnetic fields, with explicit expressions of the free energy function and rate function. The proof is based on the Karhunen-Loève expansion of complex-valued Ornstein-Uhlenbeck process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Dynamic scaling for the growth of non-equilibrium fluctuations during thermophoretic diffusion in microgravity

Diffusion processes are widespread in biological and chemical systems, where they play a fundamental role in the exchange of substances at the cellular level and in determining the rate of chemical reactions. Recently, the classical picture that portrays diffusion as random uncorrelated motion of molecules has been revised, when it was shown that giant non-equilibrium fluctuations develop during diffusion processes. Under microgravity conditions and at steady-state, non-equilibrium fluctuations exhibit scale invariance and their size is only limited by the boundaries of the system. Here in this work, we investigate the onset of non-equilibrium concentration fluctuations induced by thermophoretic diffusion in microgravity, a regime not accessible to analytical calculations but of great relevance for the understanding of several natural and technological processes. A combination of state of the art simulations and experiments allows us to attain a fully quantitative description of the development of fluctuations during transient diffusion in microgravity. Both experiments and simulations show that during the onset the fluctuations exhibit scale invariance at large wave vectors. In a broader range of wave vectors simulations predict a spinodal-like growth of fluctuations, where the amplitude and length-scale of the dominant mode are determined by the thickness of the diffuse layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Exits in order: How crowding affects particle lifetimes

Diffusive processes are often represented using stochastic random walk frameworks. The amount of time taken for an individual in a random walk to intersect with an absorbing boundary is a fundamental property that is often referred to as the particle lifetime, or the first passage time. The mean lifetime of particles in a random walk model of diffusion is related to the amount of time required for the diffusive process to reach a steady state. Mathematical analysis describing the mean lifetime of particles in a standard model of diffusion without crowding is well known. However, the lifetime of agents in a random walk with crowding has received much less attention. Since many applications of diffusion in biology and biophysics include crowding effects, here we study a discrete model of diffusion that incorporates crowding. Using simulations, we show that crowding has a dramatic effect on agent lifetimes, and we derive an approximate expression for the mean agent lifetime that includes crowding effects. Our expression matches simulation results very well, and highlights the importance of crowding effects that are sometimes overlooked.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Integrated three-dimensional characterization of reactive phase formation and coarsening during isothermal annealing of metastable Zn–3Mg–4Al eutectic

Microstructural instabilities associated with a metastable lamellar eutectic when exposed to an elevated temperature were analyzed in a Zn-3Mg-4Al alloy as a model system. X-ray diffraction and scanning electron microscopy showed that annealing at a temperature 43 K below the equilibrium eutectic temperature converted the metastable ternary MgZn 2 /η-Zn/β-ZnAl eutectic to a stable mixture of Mg 2 Zn 11 /η-Zn/α-Al. 3D EBSD suggested that supersaturation of η-Zn with Mg and Al eased difficulties in nucleation of Mg 2 Zn 11 and α-Al at the MgZn 2 /η-Zn phase interfaces. Quasi-in-situ X-ray nanotomography revealed that a reactive diffusion process prevailed in an early stage of annealing leading to rapid consumption of MgZn 2 for growth of Mg 2 Zn 11 and concomitant thinning and pinch-off of η-Zn lamellae. The reactive diffusion process also brought about significant and quantifiable changes in the topological characteristics of the η-Zn phase at remarkably shorter time scales compared to Rayleigh instability and Ostwald ripening mechanisms. Overall, the present results provide fresh insights on the short-term annealing effects on metastable eutectics, with relevance to structural evolution in additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Li-Ion Diffusion Correlations in LiAlGeO 4 : Quasielastic Neutron Scattering and Ab Initio Simulation

Here, we investigated the impact of Li stoichiometry and host flexibility on Li + diffusion processes in LiAlGeO 4 at the microscopic level using quasielastic neutron scattering (QENS) and ab initio molecular dynamics (AIMD) simulations. Using sufficiently long AIMD trajectories, we could simulate the observed QENS signal and identify the localized dynamics of Li in crystalline LiAlGeO 4 . Such information is vital to identify the bottleneck of diffusion processes and design materials for battery application. Our AIMD simulations in LiAlGeO 4 reveal that the Li + conductivity can be significantly improved by manipulating the Li stoichiometry and/or host flexibility via amorphization. We determined that excess Li stoichiometry enhances the Coulomb repulsion of neighboring Li sites and softens the host structure to enable faster Li + diffusion along the hexagonal c-axis. In the amorphous structure, random orientations of AlO 4 and GeO 4 polyhedral units create a wide distribution of intersite distances and significantly soften the host structure, greatly enhancing the Li + diffusion. The simulations are used to understand the nature of diffusion, especially the role of the host structure, the possible hopping pathways, and the diffusion behavior in various structures of LiAlGeO 4 .

localized dynamics↗
DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
DOE OSTI2022

Dynamic response of photorespiration in fluctuating light environments

Abstract Photorespiration is a dynamic process that is intimately linked to photosynthetic carbon assimilation. There is a growing interest in understanding carbon assimilation during dynamic conditions, but the role of photorespiration under such conditions is unclear. In this review, we discuss recent work relevant to the function of photorespiration under dynamic conditions, with a special focus on light transients. This work reveals that photorespiration is a fundamental component of the light induction of assimilation where variable diffusive processes limit CO2 exchange with the atmosphere. Additionally, metabolic interactions between photorespiration and the C3 cycle may help balance fluxes under dynamic light conditions. We further discuss how the energy demands of photorespiration present special challenges to energy balancing during dynamic conditions. We finish the review with an overview of why regulation of photorespiration may be important under dynamic conditions to maintain appropriate fluxes through metabolic pathways related to photorespiration such as nitrogen and one-carbon metabolism.

Plant Sciences↗
DOE OSTI2014

Development of three-dimensional site-site Smoluchowski-Vlasov equation and application to electrolyte solutions

Site-site Smoluchowski-Vlasov (SSSV) equation enables us to directly calculate van Hove time correlation function, which describes diffusion process in molecular liquids. Recently, the theory had been extended to treat solute-solvent system by Iida and Sato [J. Chem. Phys. 137, 034506 (2012)]. Because the original framework of SSSV equation is based on conventional pair correlation function, time evolution of system is expressed in terms of one-dimensional solvation structure. Here, we propose a new SSSV equation to calculate time evolution of solvation structure in three-dimensional space. The proposed theory was applied to analyze diffusion processes in 1M NaCl aqueous solution and in lithium ion battery electrolyte solution. The results demonstrate that these processes are properly described with the theory, and the computed van Hove functions are in good agreement with those in previous works.

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

Atomic-scale in situ observation of electron beam and heat induced crystallization of Ge nanoparticles and transformation of Ag@Ge core-shell nanocrystals

Crystallization of amorphous materials by thermal annealing has been investigated for numerous applications in the fields of nanotechnology, such as thin-film transistors and thermoelectric devices. The phase transition and shape evolution of amorphous germanium (Ge) and Ag@Ge core–shell nanoparticles with average diameters of 10 and 12 nm, respectively, were investigated by high-energy electron beam irradiation and in situ heating within a transmission electron microscope. The transition of a single Ge amorphous nanoparticle to the crystalline diamond cubic structure at the atomic scale was clearly demonstrated. Depending on the heating temperature, a hollow Ge structure can be maintained or transformed into a solid Ge nanocrystal through a diffusive process during the amorphous to crystalline phase transition. Selected area diffraction patterns were obtained to confirm the crystallization process. In addition, the thermal stability of Ag@Ge core–shell nanoparticles with an average core of 7.4 and a 2.1 nm Ge shell was studied by applying the same beam conditions and temperatures. The results show that at a moderate temperature (e.g., 385 °C), the amorphous Ge shell can completely crystallize while maintaining the well-defined core–shell structure, while at a high temperature (e.g., 545 °C), the high thermal energy enables a freely diffusive process of both Ag and Ge atoms on the carbon support film and leads to transformation into a phase segregated Ag–Ge Janus nanoparticle with a clear interface between the Ag and Ge domains. In conclusion, this study provides a protocol as well as insight into the thermal stability and strain relief mechanism of complex nanostructures at the single nanoparticle level with atomic resolution.

36 MATERIALS SCIENCE↗