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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Theoretical Investigation of the Adsorbate and Potential–Induced Stability of Cu Facets During Electrochemical CO 2 and CO Reduction

The activity and product selectivity of electrocatalysts for reactions like the carbon dioxide reduction reaction (CO 2 RR) are intimately dependent on the catalyst's structure and composition. While engineering catalytic surfaces can improve performance, discovering the key sets of rational design principles remains challenging due to limitations in modeling catalyst stability under operating conditions. Herein, we perform first-principles density functional calculations adopting implicit solvation methods with potential control to study the influence of adsorbates and applied potential on the stability of different facets of model Cu electrocatalysts. Using coverage dependencies extracted from microkinetic models, we describe an approach for calculating potential and adsorbate-dependent contributions to surface energies under reaction conditions, where Wulff constructions are used to understand the morphological evolution of Cu electrocatalysts under CO 2 RR conditions. Here we identify that CO*, a key reaction intermediate, exhibits higher kinetically and thermodynamically accessible coverages on (100) relative to (111) facets, which can translate into an increased relative stabilization of the (100) facet during CO 2 RR. Our results support the known tendency for increased (111) faceting of Cu nanoparticles under more reducing conditions and that the relative increase in (100) faceting observed under CO 2 RR conditions is likely attributed to differences in CO* coverage between these facets.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Mechanistic Insights into the Demethylation of Lignin‐Derived Structures Using Protic Ionic Liquids: A Density Functional Theory Study

Lignin valorization is restricted by the stability of its methoxy groups, creating a critical need for efficient demethylation strategies. Here, in this study, density functional theory (DFT) is employed to dissect the mechanistic pathways of demethylation in lignin model compounds, guaiacol and syringol, using protic ionic liquids (PILs) that act as both solvent and catalyst. Conductor‐like Screening Model for Real Solvents (COSMO‐RS) analysis identifies monoethanolammonium acetate ([MEOA][Ace]) as the most promising medium, attributed to its strong hydrogen bonding network and solvation ability. By integrating implicit and explicit solvation models, it is revealed that an acid‐catalyzed hydrolytic mechanism governs demethylation, with PILs stabilizing crucial transition states and intermediates. Complementary electronic structure evaluations, including highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO‐LUMO) gap analysis, charge distribution, and electrostatic potential mapping, demonstrate how PILs lower energetic barriers and enhance reactivity. To simulate realistic environments, this study is extended to lignin dimer complexes with varying water content, uncovering how water‐bridged solvation reverses demethylation preference from guaiacyl to syringyl units. This mechanistic shift aligns with experimental observations showing faster S‐unit reactivity in hydrated systems. Together, these findings provide atomic‐level insight into lignin demethylation dynamics and highlight how tuning acid concentration in PILs can accelerate kinetics, enabling a rational pathway toward next‐generation biomass conversion technologies.

COSMO-RS↗
DOE OSTI2019

Enhancement factor of nuclear reactions in partially ionized plasmas and asymmetric mixtures

When hydrogen is mixed with heavy (high‐ Z ) elements, even as traces, such as iron in the sun, the plasma mixture transits from a weakly coupled state to the intermediate coupling regime of simultaneous weak and strong couplings due to charge asymmetry. In those circumstances, partial ionization is an important aspect to consider. We present a global approach for evaluating enhancement factors for thermonuclear reactions in such mixtures. We grounded our approach on extensive orbital free molecular dynamics (OFMD) simulations of hydrogen‐silver mixtures, chosen as a prototype of hydrogen—high‐ Z mixtures, in a large range of temperature (100 < T < 1600 eV). By comparing a series of OFMD simulations to hyper‐netted chain calculations of effective binary ionic mixtures (eBIM), we set a general procedure for computing enhancement factors. The electron screening contribution is also included implicitly in the definition of the effective ionizations within the average atom framework. The agreement between the pair distribution functions of OFMD and eBIM validates a prescription in which each average atom representing a given species shares the same external electron density with the others (iso‐ n e rule). We checked that an interpolation formula between weak and strong couplings in BIM, due to Chugunov and DeWitt, is accurate enough to address the limit of extreme dilution of a heavy element.

Arnault, Philippe↗
DOE OSTI2026

Vacuum Neutral Transport Model in UEDGE for Tokamak Far Scrape‐Off Layer

A model for neutral transport in the far scrape-off layer (SOL) vacuum region (vacuum neutral model) has been developed and implemented in UEDGE. Free-streaming neutral trajectories between the outermost UEDGE boundary and the vessel wall are preprocessed using DEGAS2 to construct a tele-transport matrix that captures non-local neutral relocation through the vacuum. Here, this matrix is then used in UEDGE as a non-local boundary condition for the neutral equations, preserving the robustness and convergence of the implicit solver without introducing statistical noise. Simulations of a DIII-D lower single-null configuration show that the vacuum neutral model relocates neutrals from the divertor to the upstream region, increasing the outer midplane separatrix density required for detachment onset by about 30%. However, the characteristic target temperature at detachment (T e, osp ~ 3 - 4eV) and the radiation front behavior remain unchanged.

DEGAS2↗
DOE OSTI2026

Speedup of UEDGE Parameter Scans Using Machine-Learning Optimized OpenMP Parallelization and a Continuation Solver

This article presents the OpenMP parallelization of the preconditioning Jacobian assembly and right‐hand side residual evaluation in UEDGE. A continuation algorithm, utilizing the internal NKSOL implicit Jacobian‐Free Newton‐Krylov solver to efficiently scan physical parameters, is also presented. The implemented parallelization reduces the computational time for a benchmark scan run on 32 threads by compared to the serial version when using trained random forest regression models to identify the optimal decomposition of the system of equations. Random forest regression models applied to the UEDGE time‐dependent and continuation solver algorithms did not yield meaningful improvement in computational performance. A benchmark DIII‐D gas injection rate scan in the 0.35–0.75 kA interval, performed on a test cluster using the parallelized code and continuation solver, produced 1066 steady‐state solutions with a 22 s average wall‐clock computational time per steady‐state solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Depth‐dependent concentrations of hematopoietic stem cells in the adult skeleton: Implications for active marrow dosimetry

Purpose The hematopoietically active (or red) bone marrow is the target tissue assigned in skeletal dosimetry models for assessment of stochastic effects (leukemia induction) as well as tissue reactions (marrow toxicity). Active marrow, however, is in reality a surrogate tissue region for specific cell populations, namely the hematopoietic stem and progenitor cells. Present models of active marrow dosimetry implicitly assume that these cells are uniformly localized throughout the marrow spaces of trabecular spongiosa. Data from Watchman et al. and Bourke et al., however, clearly indicate that there is a substantial spatial concentration gradient of these cells with the highest concentrations localized near the bone trabeculae surfaces. The purpose of the present study was thus to explore the dosimetric implications of these spatial gradients on active marrow dosimetry. Methods Images of several bone sites from a 45‐yr female were retagged to group active marrow voxels into 50 μm increments of marrow depth, after which electron and alpha‐particle depth‐dependent specific absorbed fractions were computed for four source tissues — active marrow, inactive marrow, bone trabeculae volumes, and bone trabeculae surfaces. Corresponding depth‐dependent S values (dose to a target tissue per decay in a source tissue) were computed and further weighted by the relative target cell concentration. These depth‐weighted radionuclide S values were systematically compared to the more traditional volume‐averaged radionuclide S values of the MIRD schema for both individual bones of the skeleton and their skeletal‐averaged quantities. Results For both beta‐emitters and alpha‐emitters localized in the active and inactive marrow, depth‐weighted S values were shown to differ from volume‐averaged S values by only a few percent, as dose gradients across the marrow tissues are nonexistent. For bone volume and bone surface sources of alpha‐emitters and lower energy beta‐emitters, when marrow dose gradients are expected, explicit consideration of target cell spatial concentration gradients are shown to significantly impact marrow dosimetry. Conclusions For medical isotopes currently utilized for treatment of skeletal metastases, namely 153 Sm and 223 Ra, accounting for hematopoietic stem and progenitor cell concentration gradients resulted in maximum percent differences to reference skeletal‐averaged S values of ~21% and 55%, respectively.

Geyer, Amy M.↗
DOE OSTI2018

A Generalized Backward Euler algorithm for the numerical integration of a viscous breakage model

This paper discusses the formulation and the numerical performance of a fully implicit algorithm used to integrate a rate-dependent model defined within a breakage mechanics framework. For this purpose, a Generalized Backward Euler (GBE) algorithm has been implemented according to two different linearization strategies: The former is derived by a direct linearization of the constitutive equations, while the latter introduces rate effects through a consistency parameter. Additionally, the accuracy and efficiency of the GBE algorithm have been investigated by (1) performing material point analyses and (2) solving initial boundary value problems. In both cases, the overall performance of the underlying algorithm is inspected for a range of loading rates, thus simulating comminution from slow to fast dynamic problems. As the viscous response of the breakage model can be recast through a viscous nucleus function, the presented algorithm can be considered as a general framework to integrate constitutive equations relying on the overstress approach typical of Perzyna-like viscoplastic models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A hybrid calibration approach to Hertz-type contact parameters for discrete element models

This study aims at providing a hybrid calibration framework to estimate Hertz-type contact parameters (particle-scale shear modulus and Poisson ratio) for both two-dimensional and three-dimensional discrete element modelling (DEM). On the basis of statistically isotropic granular packings, a set of analytical formulae between macroscopic material parameters (Young modulus and Poisson ratio) and particle-scale Hertz-type contact parameters for granular systems are derived under small-strain isotropic stress conditions. However, the derived analytical solutions are only estimated values for general models. By viewing each DEM modelling as an implicit mathematical function taking the particle-level parameters as independent variables and employing the derived analytical solutions as the initial input parameters, an automatic iterative scheme is proposed to obtain the calibrated parameters with higher accuracies. Considering highly nonlinear features and discontinuities of the macro-micro relationship in Hertz-based discrete element models, the adaptive moment estimation algorithm is adopted in this study because of its capacity of dealing with noise gradients of cost functions. Here, the proposed method is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. Noticeable improvements in terms of calibration efficiency and accuracy have been made.

Constitutive law↗
DOE OSTI2016

A rank-exploiting infinite Arnoldi algorithm for nonlinear eigenvalue problems

We consider the nonlinear eigenvalue problem M ( λ ) x = 0, where M ( λ ) is a large parameter-dependent matrix. In several applications, M ( λ ) has a structure where the higher-order terms of its Taylor expansion have a particular low-rank structure. We propose a new Arnoldi-based algorithm that can exploit this structure. More precisely, the proposed algorithm is equivalent to Arnoldi's method applied to an operator whose reciprocal eigenvalues are solutions to the nonlinear eigenvalue problem. The iterates in the algorithm are functions represented in a particular structured vector-valued polynomial basis similar to the construction in the infinite Arnoldi method [Jarlebring, Michiels, and Meerbergen, Numer. Math., 122 (2012), pp. 169–195]. In this paper, the low-rank structure is exploited by applying an additional operator and by using a more compact representation of the functions. This reduces the computational cost associated with orthogonalization, as well as the required memory resources. The structure exploitation also provides a natural way in carrying out implicit restarting and locking without the need to impose structure in every restart. In conclusion, the efficiency and properties of the algorithm are illustrated with two large-scale problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A fully coupled two-level Schwarz preconditioner based on smoothed aggregation for the transient multigroup neutron diffusion equations

The neutron multigroup diffusion equations is an important approximation of the neutron transport equation, and has been widely used for studying the motion of neutrons and their interactions with the stationary background materials. Solving the multigroup diffusion equations faces challenging because many variables are coupled together and a lot of computing resources are required. In this paper, we focus on the development of a scalable parallel algorithm framework for the system of equations arising from the discretization of the multigroup diffusion equations using a finite element method in space and using an implicit scheme in time. The parallel agorithm framweork consists of an inexact Jacobian-free Newton for the nonlinear equations, a Krylov subspace method for the Jacobian system and a parallel Schwarz preconditioner for the acceleration of the algorithm convergence. A coarse space based on smoothed aggregation is introduced to construct a two-level method to improve the parallel performance of the Schwarz preconditioner. We numerically shown that compared with the one-level method, the proposed two-level method works significantly better in terms of the number of linear iterations and the compute time for a system of equations with millions of unknowns and a supercomputer with thousands of processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Recursive integral method with Cayley transformation

Summary The recently developed RIM (recursive integral method) finds eigenvalues in a region of the complex plane. It computes an indicator to test if the region contains eigenvalues using an approximate spectral projection. If the indicator shows that the region contains eigenvalues, it is subdivided into smaller regions, which are then recursively tested and subdivided until any eigenvalues are isolated to a specified precision. We propose an enhancement to RIM that uses Cayley transformations and Arnoldi's method to greatly decrease the number of factorizations required to solve the linear systems that arise from a discretized contour integral to compute the indicator, which substantially reduces the computational cost. We demonstrate the efficacy of our method with numerical examples and compare with the implicitly restarted Arnoldi method, as implemented in eigs in MATLAB.

Huang, R.↗
DOE OSTI2021

Optimizing multigrid reduction-in-time and Parareal coarse-grid operators for linear advection

Parallel-in-time methods, such as multigrid reduction-in-time (MGRIT) and Parareal, provide an attractive option for increasing concurrency when simulating time-dependent partial differential equations (PDEs) in modern high-performance computing environments. While these techniques have been very successful for parabolic equations, it has often been observed that their performance suffers dramatically when applied to advection-dominated problems or purely hyperbolic PDEs using standard rediscretization approaches on coarse grids. In this paper, we apply MGRIT or Parareal to the constant-coefficient linear advection equation, appealing to existing convergence theory to provide insight into the typically nonscalable or even divergent behavior of these solvers for this problem. To overcome these failings, we replace rediscretization on coarse grids with improved coarse-grid operators that are computed by applying optimization techniques to approximately minimize error estimates from the convergence theory. Therefore, one of our main findings is that, in order to obtain fast convergence as for parabolic problems, coarse-grid operators should take into account the behavior of the hyperbolic problem by tracking the characteristic curves. Our approach is tested for schemes of various orders using explicit or implicit Runge–Kutta methods combined with upwind-finite-difference spatial discretizations. In all cases, we obtain scalable convergence in just a handful of iterations, with parallel tests also showing significant speed-ups over sequential time-stepping.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

High‐order methods for low Reynolds number flows around moving obstacles based on universal meshes

Summary We propose a family of methods for simulating two‐dimensional incompressible, low Reynolds number flow around a moving obstacle whose motion is prescribed. The methods make use of a universal mesh: a fixed background mesh that adapts to the geometry of the immersed obstacle at all times by adjusting a few elements in the neighborhood of the obstacle's boundary. The resulting mesh provides a conforming triangulation of the fluid domain over which discretizations of any desired order of accuracy in space and time can be constructed using standard finite element spaces together with off‐the‐shelf time integrators. We demonstrate the approach by using Taylor‐Hood elements to approximate the fluid velocity and pressure. To integrate in time, we consider implicit Runge‐Kutta schemes as well as a fractional step scheme. We illustrate the methods and study their convergence numerically via examples that involve flow around obstacles that undergo prescribed deformations. Copyright © 2015 John Wiley & Sons, Ltd.

Gawlik, Evan S.↗
DOE OSTI2016

Microscale modeling of effective mechanical and electrical properties of textiles

Here, a computational framework for assisting in the development of novel textiles is presented. Electronic textiles are key in the rapidly growing field of wearable electronics for both consumer and military uses. There are two main challenges to the modeling of electronic textiles: the discretization of the textile microstructure and the interaction between electromagnetic and mechanical fields. A director-based beam formulation with an assumed electrical current is used to discretize the fabric at the level of individual fibrils. The open-source package FEniCS was used to implement the finite element model. Contact integrals were added into the FEniCS framework so that multiphysics contact laws can be incorporated in the same framework, leveraging the code generation and automated differentiation capabilities of FEniCS to produce the tangents needed by the implicit solution method. The computational model is used to construct and determine the mechanical, thermal, and electrical properties of a representative volume elements of a plain woven textile. Dynamic relaxation to solve the mechanical fields and the electrical and thermal fields is solved statically for a given mechanical state. The simulated electrical responses are fit to a simplified Kirchhoff network model to determine effective resistances of the textile.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Variational projection methods for gradient crystal plasticity using Lie algebras

Summary A computational method is developed for evaluating the plastic strain gradient hardening term within a crystal plasticity formulation. While such gradient terms reproduce the size effects exhibited in experiments, incorporating derivatives of the plastic strain yields a nonlocal constitutive model. Rather than applying mixed methods, we propose an alternative method whereby the plastic deformation gradient is variationally projected from the elemental integration points onto a smoothed nodal field. Crucially, the projection utilizes the mapping between Lie groups and algebras in order to preserve essential physical properties, such as orthogonality of the plastic rotation tensor. Following the projection, the plastic strain field is directly differentiated to yield the Nye tensor. Additionally, an augmentation scheme is introduced within the global Newton iteration loop such that the computed Nye tensor field is fed back into the stress update procedure. Effectively, this method results in a fully implicit evolution of the constitutive model within a traditional displacement‐based formulation. An elemental projection method with explicit time integration of the plastic rotation tensor is compared as a reference. A series of numerical tests are performed for several element types in order to assess the robustness of the method, with emphasis placed upon polycrystalline domains and multi‐axis loading. Copyright © 2016 John Wiley & Sons, Ltd.

Truster, Timothy J.↗
DOE OSTI2018

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity]

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capability of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.

42 ENGINEERING↗