Atomistic level simulation of the nanostructure properties
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Atomistic-level simulation of the vibration spectrum of quantum dot crystals
Quantum dot crystal structures (QDCs) have been recently proposed as the building blocks of novel thermoelectric devices.
phonons↗
The effect of the strain relaxation in InAs/GaAs stacked quantum dots and multiple quantum wells on the Raman spectrum
Atomistic-level simulations of the Raman shift in InAs/GaAs multiple quantum well (MQW) and stacked quantum dot (SQD) structures as a function of interlayer separation are reporter.
phonons↗
Computer simulation of surface and film processes
All the investigations which were performed employed in one way or another a computer simulation technique based on atomistic level considerations. In general, three types of simulation methods were used for modeling systems with discrete particles that interact via well defined potential functions: molecular dynamics (a general method for solving the classical equations of motion of a model system); Monte Carlo (the use of Markov chain ensemble averaging technique to model equilibrium properties of a system); and molecular statics (provides properties of a system at T = 0 K). The effects of three-body forces on the vibrational frequencies of triatomic cluster were investigated. The multilayer relaxation phenomena for low index planes of an fcc crystal was analyzed also as a function of the three-body interactions. Various surface properties for Si and SiC system were calculated. Results obtained from static simulation calculations for slip formation were presented. The more elaborate molecular dynamics calculations on the propagation of cracks in two-dimensional systems were outlined.
Tiller, W. A.↗
Coordinated Multiscale Modeling and Synthesis of Novel Nanostructured Composite Membranes for Solar Fuels Generation (Final Report)
Generation of carbon-based liquid fuels from reduction of CO 2 using solar energy requires the development of improved membranes that provide good ionic conductivity and mechanical properties while minimizing the crossover of gases and reduction products. Using closely coordinated multiscale modeling, synthesis and characterization studies we propose to investigate and develop novel nanostructured composite membranes with applications to conversion of carbon dioxide to storable chemical fuels. The envisioned proton exchange membranes (PEMs) will be based on a support of self- assembling polymer-modified nanoparticles with controllable porosity and tortuosity. The use of a nanoparticle support will provide control of transport and mechanical properties of the membranes. Tuning the copolymer modification of nanoparticles (polymer architectures, brush grafting density) will allow to optimize the ion (proton) transport via the Grotthuss mechanism through narrow hydrated channels while minimizing crossover of gases and reaction products due to the high density of the grafted brush and use of a non-ionic conducting glassy polymers to fill spaces between polymer-grafted nanoparticles. In Phase I synthesis of the copolymers and their attachment to the nanoparticle support will be guided by multiscale simulations that include atomistic molecular dynamics and continuum-level transport simulations. The former will include reactive and non-reactive atomistic simulations that will provide key insight into nanoscale polymer morphology and ion/molecular transport mechanisms need to optimize the copolymer structure. The latter will provide insight into the role of nanoparticle self-assembly on the global transport of ionic and molecular species. The proton conduction and CO 2 /methanol permeability of the membranes will be experimentally characterized as well as simulated and will be correlated with morphology and polymer structure. Prototypes of optimal membranes will be fabricated and characterized at the end of the project. Successful development of improved nanostructured composite PEMs and demonstration of the simulation-guided materials-by-design paradigm will result in our ability to design and synthesize membranes for a wide variety of solar fuels generation and related electrochemical applications.
14 SOLAR ENERGY↗
Ubiquitous short-range order in multi-principal element alloys
Recent research in multi-principal element alloys (MPEAs) has increasingly focused on the role of short-range order (SRO) on material performance. However, the mechanisms of SRO formation and its precise control remain elusive, limiting the progress of SRO engineering. Here, leveraging advanced additive manufacturing techniques that produce samples with a wide range of cooling rates (up to 10 7 K s –1 ) and an enhanced semi-quantitative electron microscopy method, we characterize SRO in three CoCrNi-based face-centered-cubic (FCC) MPEAs. Surprisingly, irrespective of the processing and thermal treatment history, all samples exhibit similar levels of SRO. Atomistic simulations reveal that during solidification, prevalent local chemical order arises in the liquid-solid interface (solidification front) even under the extreme cooling rate of 10 11 K s –1 . This phenomenon stems from the swift atomic diffusion in the supercooled liquid, which matches or even surpasses the rate of solidification. Therefore, SRO is an inherent characteristic of most FCC MPEAs, insensitive to variations in cooling rates and even annealing treatments typically available in experiments.
36 MATERIALS SCIENCE↗
Data-centric framework for crystal structure identification in atomistic simulations using machine learning
Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.
36 MATERIALS SCIENCE↗
Reshaping of Truncated Pd Nanocubes: Energetic and Kinetic Analysis Integrating Transmission Electron Microscopy with Atomistic-Level and Coarse-Grained Modeling
Stability against reshaping of metallic fcc nanocrystals synthesized with tailored far-from-equilibrium shapes is key to maintaining optimal properties for applications such as catalysis. Yet Arrhenius analysis of experimental reshaping kinetics, and appropriate theory and simulation, is lacking. As such, we use TEM to monitor the reshaping of Pd nanocubes of ~25 nm side length between 410 °C (over ~4.5 h) and 440 °C (over ~0.25 h), extracting a high effective energy barrier of E eff ≈ 4.6 eV. We also provide an analytic determination of the energy variation along the optimal pathway for reshaping that involves transfer of atoms across the nanocube surface from edges or corners to form new layers on side {100} facets. The effective barrier from this analysis is shown to increase strongly with the degree of truncation of edges and corners in the synthesized nanocube. Theory matches experiment for the appropriate degree of truncation. In addition, we perform simulations of a stochastic atomistic-level model incorporating a realistic description of diffusive hopping for undercoordinated surface atoms, thereby providing a visualization of the initial reshaping process.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multiphysics and Multiscale Simulation Methods for Electromagnetic Energy Assisted Fossil Fuel to Hydrogen Conversion (Final Scientific/Technical Report)
This report summarizes the technical accomplishments of the four-year research project “Multiphysics and Multiscale Simulation Methods for Electromagnetic Energy Assisted Fossil Fuel to Hydrogen Conversion” (Award No. DE-FE0032092), conducted at Howard University and the University of Houston (subawardee) from September 2021 to August 2025. The project successfully achieved all four major objectives: 1. 3D Structural Characterization – Developed 3D optical imaging and mechanical sectioning methods to characterize catalyst distribution and support morphology in nickel foam substrates. Successfully reconstructed 3D geometries and imported them into COMSOL Multiphysics for electromagnetic simulations. 2. EM Hotspot Simulation – Created all-frequency stable electromagnetic formulations and 3D nodal discontinuous Galerkin (NDG) methods for coupled electromagnetic-thermal-fluid problems in multiscale catalytic media. Demonstrated stable solutions from DC to microwave frequencies. 3. Multiphysics Coupling – Developed multiscale simulation methods coupling FEM electromagnetic solvers with thermal transport equations. Reactive molecular dynamics (ReaxFF MD) simulations were performed to investigate catalytic reaction mechanisms at the atomistic level. Demonstrated electromagnetic-thermal co-simulation capabilities for porous catalyst structures. 4. System Optimization – Designed and optimized EM-assisted catalytic systems using nickel foam and carbon foam structures, demonstrating significant temperature increases due to microwave heating. Observed and characterized plasma generation in carbon fiber catalysts. Investigated multiple reaction chamber geometries for improved microwave energy deposition. The project produced significant scientific contributions including 15+ peer-reviewed publications, trained multiple Ph.D. students and undergraduate researchers, and advanced the understanding of microwave-assisted hydrogen production from fossil fuels.
08 HYDROGEN↗
Multiscale Analysis of Delamination of Carbon Fiber-Epoxy Laminates with Carbon Nanotubes
A multi-scale analysis is presented to parametrically describe the Mode I delamination of a carbon fiber/epoxy laminate. In the midplane of the laminate, carbon nanotubes are included for the purposes of selectively enhancing the fracture toughness of the laminate. To analyze carbon fiber epoxy carbon nanotube laminate, the multi-scale methodology presented here links a series of parameterizations taken at various length scales ranging from the atomistic through the micromechanical to the structural level. At the atomistic scale molecular dynamics simulations are performed in conjunction with an equivalent continuum approach to develop constitutive properties for representative volume elements of the molecular structure of components of the laminate. The molecular-level constitutive results are then used in the Mori-Tanaka micromechanics to develop bulk properties for the epoxy-carbon nanotube matrix system. In order to demonstrate a possible application of this multi-scale methodology, a double cantilever beam specimen is modeled. An existing analysis is employed which uses discrete springs to model the fiber bridging affect during delamination propagation. In the absence of empirical data or a damage mechanics model describing the effect of CNTs on fracture toughness, several tractions laws are postulated, linking CNT volume fraction to fiber bridging in a DCB specimen. Results from this demonstration are presented in terms of DCB specimen load-displacement responses.
Riddick, Jaret C.↗
Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture
Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Here, Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
From Micro-environments to Macroscopic Effects: How the Alkaline Hydrogen Evolution Reaction Drives Cu Cathodic Corrosion
Cathodic corrosion of copper (Cu) has posed a significant challenge for over a century, impeding various technological progresses such as electrochemical conversion of CO 2 (eCO 2 RR) into fuels and other value-added carbon products. Here, in this study, employing a combined Density Functional Theory (DFT) and kinetic Monte Carlo (kMC) simulation approach, we delve into the atomistic level mechanism driving this phenomenon in Cu. Our hypothesis posits the pivotal role of alkaline hydrogen evolution reaction (HER) in facilitating cathodic corrosion in Cu. We rigorously develop a pH-dependent hydroxide (OH) adsorption mechanism and calculate the equilibrium OH coverage (𝜃 OH ) at varying pH levels, the thermodynamic stability of subsurface oxygen (O sub ), as well as the Cu-vacancy mediated diffusion of subsurface oxygens (O sub ). Through comprehensive analysis, we establish correlation among various microenvironments, including oxygen diffusion in subsurface layers, pH-dependent OH adsorption, and Cu dissolution into the electrolyte as (Cu-OH) complexes. Furthermore, our investigation explores the correlation between surface coordination environment of active sites and cathodic corrosion of Cu. Finally, by integrating DFT-derived thermodynamic data into a kMC model, we successfully predict the formation of experimentally observed corrosion pits on Cu-surfaces. This combined approach not only advances our fundamental understanding of Cu cathodic corrosion but also offers insights crucial for developing effective corrosion mitigation strategies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Salts in Hot Water: Developing a Scientific Basis for Supercritical Desalination and Strategic Metal Recovery
The w21_superdesal project is part of an LDRD-DR on supercritical desalination (20190057DR). The goal of the simulation work is to use atomistic simulations to understand at a molecular level the changes in hydrogen bonding and ion solvation that occur as we increase the temperature and/or pressure and change the density and ion concentration. Our simulation results will also aid in the interpretation of experimental data and guide the development of applied thermodynamic models for engineering design calculations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cabana: A Performance Portable Library for Particle-Based Simulations
Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.
97 MATHEMATICS AND COMPUTING↗
Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis
Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Herein, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.
36 MATERIALS SCIENCE↗
Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations
We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.
Do, Hung Nguyen↗
A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods
Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.
Saether, E.↗
Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains
Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.
Glaessgen, E. H.↗