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DOE OSTI2026

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗

DOE OSTI2020

Multiscale formulation of frictional contact mechanics at the pore scale

Direct numerical simulation (DNS) yields the highest fidelity predictions of mechanical deformation at the pore scale, but is prohibitively expensive for analyzing large or many samples. Discrete element methods (DEM) are an efficient alternative, but are limited to granular media and incapable of estimating or controlling prediction errors. We present a pore-level multiscale method (PLMM) that approximates DNS efficiently and with controllable accuracy. We focus on the linear elastic response of a consolidated geologic porous medium with arbitrary microstructure, heterogeneous mineralogy, containing cracks or defects. PLMM decomposes the solid phase into non-overlapping subdomains, on which local basis functions are constructed. The bases are then coupled with a global interface problem that accounts for slip or stick contact conditions between the subdomains. PLMM produces an initial, but accurate, approximation to DNS that can be iteratively improved. It is amenable to parallelism and allows for different mesh, models, and physics in each subdomain. An algebraic interpretation of PLMM as a preconditioner is also presented to allow non-intrusive implementation into existing solvers. Lastly, this work extends previous developments of PLMM in fluid dynamics to solid mechanics and enables future extensions towards modeling coupled flow and mechanics problems.

42 ENGINEERING↗

DOE OSTI2015

Peridynamic Multiscale Finite Element Methods

The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.

42 ENGINEERING↗

DOE OSTI2016

Spatial intratumoral heterogeneity of proliferation in immunohistochemical images of solid tumors

Purpose: The interactions of neoplastic cells with each other and the microenvironment are complex. To understand intratumoral heterogeneity, subtle differences should be quantified. Main factors contributing to heterogeneity include the gradient ischemic level within neoplasms, action of microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins. This may reflect on the expression of biomarkers in the context of prognosis/stratification. Hence, a rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images can be challenging to identify and describe. Methods: A quantitative method that is useful for characterizing complex irregular structures is lacunarity; it is a multiscale technique that exhaustively samples the image, while the decay of its index as a function of window size follows characteristic patterns for different spatial arrangements. In histological images, lacunarity provides a useful measure for the spatial organization of a biomarker when a sampling scheme is employed and relevant features are computed. The proposed approach quantifies the segmented proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumor region. The aim is to investigate in whole sections of primary pancreatic neuroendocrine neoplasms (pNENs), using whole-slide imaging and image analysis, the spatial intratumoral heterogeneity of Ki-67 immunostains. Unsupervised learning is employed to verify that the approach can partition the tissue sections according to distributional heterogeneity. Results: The architectural complexity of histological images has shown that single measurements are often insufficient. Inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. Lacunarity curves demonstrate variations in the sampled image sections. Since the spatial distribution of proliferation in each case is different, the width of the curves changes too. Image sections that have smaller numerical variations in the computed features correspond to neoplasms with spatially homogeneous proliferation, while larger variations correspond to cases where proliferation shows various degrees of clumping. Grade 1 (uniform/nonuniform: 74%/26%) and grade 3 (uniform: 100%) pNENs demonstrate a more homogeneous proliferation with grade 1 neoplasms being more variant, while grade 2 tumor regions render a more diverse landscape (50%/50%). Hence, some cases show an increased degree of spatial heterogeneity comparing to others with similar grade. Whether this is a sign of different tumor biology and an association with a more benign/malignant clinical course needs to be investigated further. The extent and range of spatial heterogeneity has the potential to be evaluated as a prognostic marker. Conclusions: The association with tumor grade as well as the rationale that the methodology reflects true tumor architecture supports the technical soundness of the method. This reflects a general approach which is relevant to other solid tumors and biomarkers. Drawing upon the merits of computational biomedicine, the approach uncovers salient features for use in future studies of clinical relevance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

A Perspective on Multiscale Modeling of Explicit Solvation-Enabled Simulations of Catalysis at Liquid–Solid Interfaces

Catalysis at liquid-solid interfaces is profoundly influenced by the interfacial solvent structure, which affects catalytic activity, selectivity, and reaction pathways. This perspective discusses state-of-the-art multiscale modeling methods that integrate quantum mechanics and molecular mechanics approaches to apply explicit solvent molecules to capture these interfacial phenomena. Specifically, the construction of multiscale models, the importance of capturing the interfacial solvent structure, and the computational strategies used to achieve this are explored, and the challenges in balancing chemical accuracy with computational expense are highlighted. Additionally, this perspective addresses the limitations of current methods. Opportunities for integrating machine learning are proposed. Here, by advancing the efficiency and user friendliness of multiscale modeling, it is argued that deeper insights into heterogeneous catalysis in liquid phases can be provided, which will ultimately contribute to the development of more efficient catalytic processes.

Ab initio molecular dynamics↗

NASA NTRSDate not supplied

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

DOE OSTI2017

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

An Analysis Platform for Multiscale Hydrogeologic Modeling with Emphasis on Hybrid Multiscale Methods

One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve, we envision that hybrid multiscale modeling will become more common and may become a viable alternative to conventional single-scale models in the near future.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2015

Additive manufacturing of materials: Opportunities and challenges

Additive manufacturing (also known as 3D printing) is considered a disruptive technology for producing components with topologically optimized complex geometries as well as functionalities that are not achievable by traditional methods. The realization of the full potential of 3D printing is stifled by a lack of computational design tools, generic material feedstocks, techniques for monitoring thermomechanical processes under in situ conditions, and especially methods for minimizing anisotropic static and dynamic properties brought about by microstructural heterogeneity. In this paper, we discuss the role of interdisciplinary research involving robotics and automation, process control, multiscale characterization of microstructure and properties, and high-performance computational tools to address each of these challenges. In addition, emerging pathways to scale up additive manufacturing of structural materials to large sizes (>1 m) and higher productivities (5–20 kg/h) while maintaining mechanical performance and geometrical flexibility are also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Single Atom Catalysts: A Review of Characterization Methods

Abstract Single atom catalysts (SACs) harbor a potential to exceed nanoparticle catalysts in terms of activity, stability and selectivity in a growing number of chemical reactions. Although their investigation is attracting significant attention, important fundamental questions focusing on key physicochemical properties of SACs (e. g., structure – property relationships, structural dynamics, reaction‐driven restructuring) remain unanswered. A main challenge for research in the field is how to reliably characterize the environments of single atoms in the presence of complicating factors such as low weight loadings, strong metal‐support interactions, and atomic and multiscale heterogeneity of bonding in the single atom sites. This review addresses this challenge – identifying catalytically relevant features of physicochemical properties of single atoms (charge state, electronic structure, atomic configuration, bonding interactions with a support) and surveying advanced tools/methods for characterizing them. The review places a strong emphasis on multimodal methods exploiting X‐ray absorption, emission and photoelectron spectroscopies, and provides several examples from the authors’ research that demonstrate their use as powerful tools for SAC characterization.

Kottwitz, Matthew↗

DOE OSTI2017

Phase-field based Multiscale Modeling of Heterogeneous Solid Electrolytes: Applications to Nanoporous Li 3 PS 4

Modeling the effective ion conductivities of heterogeneous solid electrolytes typically involves the use of a computer-generated microstructure consisting of randomly or uniformly oriented fillers in a matrix. But, the structural features of the filler/matrix interface, which critically determine the interface ion conductivity and the microstructure morphology, have not been considered during the microstructure generation. In using nanoporous β-Li 3 PS 4 electrolyte as an example, we develop a phase-field model that enables generating nanoporous microstructures of different porosities and connectivity patterns based on the depth and the energy of the surface (pore/electrolyte interface), both of which are predicted through density functional theory (DFT) calculations. Room-temperature effective ion conductivities of the generated microstructures are then calculated numerically, using DFT-estimated surface Li-ion conductivity (3.14×10 -3 S/cm) and experimentally measured bulk Li-ion conductivity (8.93×10 -7 S/cm) of β-Li 3 PS 4 as the inputs. We also use the generated microstructures to inform effective medium theories to rapidly predict the effective ion conductivity via analytical calculations. Furthemore, when porosity approaches the percolation threshold, both the numerical and analytical methods predict a significantly enhanced Li-ion conductivity (1.74×10 -4 S/cm) that is in good agreement with experimental data (1.64×10 -4 S/cm). The present phase-field based multiscale model is generally applicable to predict both the microstructure patterns and the effective properties of heterogeneous solid electrolytes.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Mimicking Geologic Depositional Fabrics for Multiphase Flow Experiments

A novel laboratory technique is presented for generating two-dimensional beadpacks with reproducible natural geologic sedimentary bedforms. The heterogeneous beadpacks are deposited in a 0.6 m × 0.6 m × 0.02 m glass slab chamber using a programmable two-axis linear actuator. The method takes advantage of natural mechanical sorting processes, along with the ability to program the motion of the arm, to efficiently build cross-beds and ripple laminae similar to those seen in natural water-lain clastic deposits. By using a mixture of grain sizes (200 to 800 μm diameter), depositional fabrics with multiscale heterogeneity (mm to dm) are generated. Reproducibility tests show very high correlation among multiple fabric realizations produced with similar inputs. After introducing this first-of-a-kind capability to produce depositionally realistic fabrics at scales larger than that of rock cores, a demonstrative study is presented that illustrates gravity unstable multiphase flow which is relevant in the context of CO 2 sequestration. Preliminary results highlight the dramatic impact small scale capillary heterogeneities have on multiphase immiscible displacement and can help bridge understanding between core scale experiments and reservoir scale observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Bayesian and variational Bayesian approaches for flows in heterogeneous random media

In this paper, we study porous media flows in heterogeneous stochastic media. We propose an efficient forward simulation technique that is tailored for variational Bayesian inversion. As a starting point, the proposed forward simulation technique decomposes the solution into the sum of separable functions (with respect to randomness and the space), where each term is calculated based on a variational approach. This is similar to Proper Generalized Decomposition (PGD). Next, we apply a multiscale technique to solve for each term (as in ) and, further, decompose the random function into 1D fields. As a result, our proposed method provides an approximation hierarchy for the solution as we increase the number of terms in the expansion and, also, increase the spatial resolution of each term. We use the hierarchical solution distributions in a variational Bayesian approximation to perform uncertainty quantification in the inverse problem. We conduct a detailed numerical study to explore the performance of the proposed uncertainty quantification technique and show the theoretical posterior concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Water Imbibition and Oil Recovery in Shale: Dynamics and Mechanisms Using Integrated Centimeter-to-Nanometer-Scale Imaging

Water imbibition, and the associated oil displacement, is an important process in shale oil reservoirs after hydraulic fracturing and in water-based enhanced oil recovery (EOR). Current techniques for water imbibition measurement are mostly “black-box”-type methods. A more explicit understanding of the water imbibition/oil recovery dynamics and geological controls is in demand. In this paper, a multiscale imaging technique that covers centimeter to nanometer scale (i.e., core to pore scale), integrating neutron radiography, microcomputed tomography (micro-CT), and scanning electron microscope (SEM) is applied to investigate the water imbibition depth and rate and the cause of heterogeneity of imbibition in shale samples. The dynamic processes of water imbibition in the 1-in. (25.4-mm) core sample were explicitly demonstrated, and the imbibition along the matrix and imbibition through microfractures are distinguished through neutron radiography image analysis. The causes of observed imbibition heterogeneity were further investigated through micro-CT and SEM image analysis for 1.5-mm diameter miniplug samples from different laminas of the 1-in. core samples. Imbibition depth and rate were calculated on the basis of image analysis as well. Estimation of oil recovery through water imbibition in shale matrix was performed for an example shale field. Here this innovative and integrated multiscale imaging technique provides a “white/gray-box” method to understand water imbibition and water-oil displacement in shale. The wide span of the length scale (from centimeter to nanometer) of this technique enables a more comprehensive, accurate, and specific understanding of both the core-scale dynamics and pore-scale mechanisms of water imbibition, oil recovery, and matrix-fracture interaction.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2018

Finite-element analysis of top-casing electric source method for imaging hydraulically active fracture zones

Imaging hydraulically active fracture zones (HAFZ) is of paramount importance to subsurface resource extraction, geologic storage, and hazardous waste disposal. We have developed advanced 3D finite-element (FE) electrical imaging algorithms for HAFZ in the presence of a steel-cased well. The algorithms use tetrahedral FE meshes in the simulation domain and coarse rectangular finite-difference meshes in the imaging domain. This heterogeneous dual-mesh approach is well suited to modeling the multiscale earth model due to steel-cased wells. We find that the algorithms accurately and efficiently simulate surface electric field measurements over a 3D HAFZ at depth when one end point of a surface electric source is connected to a wellhead. For brevity, this configuration is called the top-casing electric source method. By replacing a hollow cased well with a solid prism, we improve our computational efficiency without affecting the solution accuracy. The sensitivity of the top-casing source method to HAFZ highly depends on the continuity of a steel-cased well because it makes currents preferentially flow to HAFZ. The sensitivity also depends on conductivity structures around the well because they control current leaking from the steel-cased well. We find that the method can image a localized HAFZ and detect changes in its width and height. Here, the imaging results are improved when a volume of the imaging domain is constrained from geomechanical perspectives. A primary advantage of the method is the fact that the sources and receivers are placed on the surface, thus not interrupting the well operation.

3D↗

DOE OSTI2023

Mixed imbibition controls the advance of wetting fluid in multiscale geological media

Imbibition plays a central role during multiphase flows in geological media; yet, our understanding of imbibition dynamics across the multiscale features of rocks, including fractures, microcracks, and heterogeneous matrices is limited. Here, we deployed a unique combination of micro- and clinical X-ray CT imaging to probe directly the spatiotemporal evolution of imbibition in a natural, multiscale shale sample. The method enabled unraveling of mixed imbibition behavior, with spontaneous imbibition rates in the matrix pores and microcracks driven by capillarity proceeding as $\propto t^{-1/2}$, whereas pressure-driven flows in the macroscopic fractures yield apparent imbibition rates with $\propto t^{-1}$ scaling. Regardless of the aperture, we showed that spontaneous imbibition proceeds uniformly away from the fractures. The effects of microcracks are further investigated by comparing the dynamics of the imbibition fronts with and without microcracks. Finally, these results highlight the paramount role of microcracks on anomalous front roughening and the need to account for microcracks appropriately in the development of predictive theoretical models.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Benchmarking and Performance of the NASA Multiscale Analysis Tool

The NASA Multiscale Analysis Tool (NASMAT) is as a “plug and play,” software package which utilizes multiscale recursive micromechanics as a platform for massively multiscale modeling of hierarchical materials and structures subjected to thermomechanical. This paper is intended to give an overview of the design of NASMAT and how the design supports modularity, upgradability and maintainability, interoperability, and utility. First, the software architecture and hierarchy will be explored. Details on each of the 11 NASMAT procedures and the arrangement of NASMAT data will be presented. Application program interfaces (APIs) that were developed to facilitate the communication of NASMAT with other programs will be described. The intended application for NASMAT is massively multiscale modeling on high performance computing systems. As such, results benchmarking the performance of the integration of NASMAT with the Abaqus commercial finite element method software are also presented.

Multiscale Modeling↗

DOE OSTI2020

A numerical-homogenization based phase-field fracture modeling of linear elastic heterogeneous porous media

Most porous media, such as geomaterials and biomaterials are highly heterogeneous in nature, and they contain large variations of microscopic pore structures, such as pore sizes, pore distribution, and pore shapes. The oscillation of microscopic structures is a substantial challenge in theoretical characterization and is usually ignored in continuous modeling. However, mechanical behavior of porous media such as deformation and failure, are essentially impacted by the microscopic heterogeneity which needs to be considered in modeling a porous media. Here, this research proposes a numerical modeling framework with a capability to investigate the effect of microscopic heterogeneity on the macroscopic fracture behavior in porous media by using a numerical homogenization technique, combined with the phase-field fracture modeling method. This numerical modeling strategy computes a homogenized elasticity tensor based on microscopic heterogeneous pore structures heterogenous porous domain by solving boundary value problems at microscopic domain. The strain energy and subsequent propagation of macroscopic fractures will be updated using homogenized stiffness information. Using this numerical scheme, the microscopic pore structure’s impact on the fracture behavior through the homogenized elastic tensor will be taken into account. This multiscale technique is benchmarked against classical problems. Finally, the results highlight the importance of the underlying pore structure and reveal that both fracture strength and propagation path can be influenced by the microscopic heterogeneity.

36 MATERIALS SCIENCE↗