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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Local Embedding and Effective Downfolding in the Auxiliary-Field Quantum Monte Carlo Method

A local embedding and effective downfolding scheme has been developed and implemented in the auxiliary-field quantum Monte Carlo (AFQMC) method. A local cluster in which electrons are fully correlated is defined, and the frozen orbital method is used on the remainder of the system to construct an effective Hamiltonian, which operates within the local cluster. Local embedding, which involves only the occupied sector, has previously been employed in the context of Co/graphene. Here, the methodology is extended in order to allow for effective downfolding of the virtual sector, thus allowing for significant reduction in the computational effort required for AFQMC calculations. The system size, which can be feasibly treated with AFQMC, is therefore greatly extended as only a single local cluster is explicitly correlated at the AFQMC level of theory. The approximation is controlled by the separate choice of the spatial size of the active occupied region (Ro) and of the active virtual region (Rv). In conclusion, the systematic dependence of the AFQMC energy on Ro and Rv is investigated, and it is found that relative AFQMC energies of physical and chemical interest converge rapidly to the full AFQMC treatment (i.e., using no embedding or downfolding).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1.0

Fusion Transfer Learning (FTL) model provides a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. The knowledge transfer process leverages a pre-trained neural encoder-decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL's capacity to capture transitional behaviors and dynamical features in plasma dynamics -- a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics (MHD) modes.

Bai, Zhe↗
DOE OSTI2023

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗
DOE OSTI2015

BROWN DWARF BINARIES FROM DISINTEGRATING TRIPLE SYSTEMS

Binaries in which both components are brown dwarfs (BDs) are being discovered at an increasing rate, and their properties may hold clues to their origin. We have carried out 200,000 N-body simulations of three identical stellar embryos with masses drawn from a Chabrier IMF and embedded in a molecular core. The bodies are initially non-hierarchical and undergo chaotic motions within the cloud core, while accreting using Bondi–Hoyle accretion. The coupling of dynamics and accretion often leads to one or two dominant bodies controlling the center of the cloud core, while banishing the other(s) to the lower-density outskirts, leading to stunted growth. Eventually each system transforms either to a bound hierarchical configuration or breaks apart into separate single and binary components. The orbital motion is followed for 100 Myr. In order to illustrate 200,000 end-states of such dynamical evolution with accretion, we introduce the “triple diagnostic diagram,” which plots two dimensionless numbers against each other, representing the binary mass ratio and the mass ratio of the third body to the total system mass. Numerous freefloating BD binaries are formed in these simulations, and statistical properties are derived. The separation distribution function is in good correspondence with observations, showing a steep rise at close separations, peaking around 13 AU and declining more gently, reaching zero at separations greater than 200 AU. Unresolved BD triple systems may appear as wider BD binaries. Mass ratios are strongly peaked toward unity, as observed, but this is partially due to the initial assumptions. Eccentricities gradually increase toward higher values, due to the lack of viscous interactions in the simulations, which would both shrink the orbits and decrease their eccentricities. Most newborn triple systems are unstable and while there are 9209 ejected BD binaries at 1 Myr, corresponding to about 4% of the 200,000 simulations, this number has grown to 15,894 at 100 Myr (∼8%). The total binary fraction among freefloating BDs is 0.43, higher than indicated by current observations, which, however, are still incomplete. Also, the gradual breakup of higher-order multiples leads to many more singles, thus lowering the binary fraction. The main threat to newly born triple systems is internal instabilities, not external perturbations. At 1 Myr there are 1325 BD binaries still bound to a star, corresponding to 0.66% of the simulations, but only 253 (0.13%) are stable on timescales >100 Myr. These simulations indicate that dynamical interactions in newborn triple systems of stellar embryos embedded in and accreting from a cloud core naturally form a population of freefloating BD binaries, and this mechanism may constitute a significant pathway for the formation of BD binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Design and implementation of the cosmic ray tagger system for the ICARUS detector at FNAL

The ICARUS-T600 Liquid Argon Time Projection Chamber is operating at Fermilab at shallow depth and thus exposed to a high flux of cosmic rays that can fake neutrino interactions. A cosmic ray tagging (CRT) system (∼ 1100 m 2 ), surrounding the cryostat with two layers of fiber embedded plastic scintillators, was developed to mitigate the cosmic ray induced background. Using nanosecond-level timing information, the CRT can distinguish incoming cosmic rays from outgoing particles from neutrino interactions in the TPC. In this paper an overview of the CRT system, its installation and commissioning at Fermilab, and its performance are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Systematically improvable multiscale solver for correlated electron systems

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe a framework for a general multiscale method based on embedding a self-energy of a strongly correlated subsystem into a self-energy generated by a method able to treat large weakly correlated systems approximately. As an example, we present the embedding of an exact diagonalization self-energy into a self-energy generated from self-consistent second-order perturbation theory. Using a quantum impurity model, generated from a cluster dynamical mean field approximation to the two-dimensional Hubbard model, as a benchmark, we illustrate that our method allows us to obtain accurate results at a fraction of the cost of typical Monte Carlo calculations. We test the method in multiple regimes of interaction strengths and dopings of the model. Here, the general embedding framework we present avoids difficulties such as double counting corrections, frequency-dependent interactions, or vertex functions. As it is solely formulated at the level of the single-particle Green's function, it provides a promising route for the simulation of realistic materials that are currently difficult to study with other methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Time-dependent potential-functional embedding theory

We introduce a time-dependent potential-functional embedding theory (TD-PFET), in which atoms are grouped into subsystems. In TD-PFET, subsystems can be propagated by different suitable time-dependent quantum mechanical methods and their interactions can be treated in a seamless, first-principles manner. TD-PFET is formulated based on the time-dependent quantum mechanics variational principle. The action of the total quantum system is written as a functional of the time-dependent embedding potential, i.e., a potential-functional formulation. By exploiting the Runge-Gross theorem, we prove the uniqueness of the time-dependent embedding potential under the constraint that all subsystems share a common embedding potential. We derive the integral equation that such an embedding potential needs to satisfy. As proof-of-principle, we demonstrate TD-PFET for a Na{sub 4} cluster, in which each Na atom is treated as one subsystem and propagated by time-dependent Kohn-Sham density functional theory (TDDFT) using the adiabatic local density approximation (ALDA). Our results agree well with a direct TDDFT calculation on the whole Na{sub 4} cluster using ALDA. We envision that TD-PFET will ultimately be useful for studying ultrafast quantum dynamics in condensed matter, where key regions are solved by highly accurate time-dependent quantum mechanics methods, and unimportant regions are solved by faster, less accurate methods.

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

Transformational Challenge Reactor preconceptual core design studies

In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Kernel-based global sensitivity analysis obtained from a single data set

Results from global sensitivity analysis (GSA) often guide the understanding of complicated input–output systems. Kernel-based GSA methods have recently been proposed for their capability of treating a broad scope of complex systems. In this paper, we develop a new set of kernel GSA tools when only a single set of input–output data is available. Three key advances are made: (1) A new numerical estimator is proposed that demonstrates an empirical improvement over previous procedures. (2) A computational method for generating inner statistical functions from a single data set is presented. (3) A theoretical extension is made to define conditional sensitivity indices, which reveal the degree that the inputs carry shared information about the output when inherent input–input correlations are present. Utilizing these conditional sensitivity indices, a decomposition is derived for the output uncertainty based on what is called the optimal learning sequence of the input variables, which remains consistent when correlations exist between the input variables. Further, while these advances cover a range of GSA subjects, a common single data set numerical solution is provided by a technique known as the conditional mean embedding of distributions. The new methodology is implemented on benchmark systems to demonstrate the provided insights.

42 ENGINEERING↗
DOE OSTI2019

Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort

Scientific Named Entity Referent Extraction is often more complicated than traditional Named Entity Recognition (NER). For example, in polymer science, chemical structure may be encoded in a variety of nonstandard naming conventions, and authors may refer to polymers with conventional names, commonly used names, labels (in lieu of longer names), synonyms, and acronyms. As a result, accurate scientific NER methods are often based on task-specific rules, which are difficult to develop and maintain, and are not easily generalized to other tasks and fields. Machine learning models require substantial expert-annotated data for training. Here we propose polyNER: a semi-automated system for efficient identification of scientific entities in text. PolyNER applies word embedding models to generate entity-rich corpora for productive expert labeling, and then uses the resulting labeled data to bootstrap a context-based word vector classifier. Evaluation on materials science publications shows that the polyNER approach enables improved precision or recall relative to a state-of-the-art chemical entity extraction system at a dramatically lower cost: it required just two hours of expert time, rather than extensive and expensive rule engineering, to achieve that result. This result highlights the potential for human-computer partnership for constructing domain-specific scientific NER systems.

Crowdsourcing↗
DOE OSTI2019

Absolutely Localized Projection-Based Embedding for Excited States

We present a quantum embedding method that allows for calculation of local excited states embedded in a Kohn–Sham density functional theory (DFT) environment. Projection-based quantum embedding methodologies provide a rigorous framework for performing DFT-in-DFT and wave function in DFT (WF-in-DFT) calculations. The use of absolute localization, where the density of each subsystem is expanded in only the basis functions associated with the atoms of that subsystem, provide improved computationally efficiency for WF-in-DFT calculations by reducing the number of orbitals in the WF calculation. In this work, we extend absolutely localized projection-based quantum embedding to study localized excited states using EOM-CCSD-in-DFT and TDDFT-in-DFT. The embedding results are highly accurate compared to the corresponding canonical EOM-CCSD and TDDFT results on the full system, with TDDFT-in-DFT frequently more accurate than canonical TDDFT. The absolute localization method is shown to eliminate the spurious low-lying excitation energies for charge-transfer states and prevent overdelocalization of excited states. Additionally, we attempt to recover the environment response caused by the electronic excitations in the high-level subsystem using different schemes and compare their accuracy. Finally, we apply this method to the calculation of the excited-state energy of green fluorescent protein and show that we systematically converge to the full system results. Here we demonstrate how this method can be useful in understanding excited states, specifically which chemical moieties polarize to the excitation. Furthermore, this work shows absolutely localized projection-based quantum embedding can treat local electronic excitations accurately and make computationally expensive WF methods applicable to systems beyond current computational limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Regenerable Photovoltaic Devices with a Hydrogel-Embedded Microvascular Network

Light-driven degradation of photoactive molecules could be one of the major obstacles to stable long term operation of organic dye-based solar light harvesting devices. One solution to this problem may be mimicking the regeneration functionality of a plant leaf. We report an organic dye photovoltaic system that has been endowed with such microfluidic regeneration functionality. A hydrogel medium with embedded channels allows rapid and uniform supply of photoactive reagents by a convection-diffusion mechanism. A washing-activation cycle enables reliable replacement of the organic component in a dye-sensitized photovoltaic system. Repetitive restoration of photovoltaic performance after intensive device degradation is demonstrated.

14 SOLAR ENERGY↗
DOE OSTI2014

The properties of Lyα nebulae: gas kinematics from nonresonant lines

With the Very Large Telescope/X-shooter, we obtain optical and near-infrared spectra of six Lyα blobs at z ∼ 2.3. For a total sample of eight Lyα blobs (including two that we have previously studied), the majority (6/8) have broadened Lyα profiles with shapes ranging from a single peak to symmetric or asymmetric double-peaked. The remaining two systems, in which the Lyα profile is not significantly broader than the [O III] or Hα emission lines, have the most spatially compact Lyα emission, the smallest offset between the Lyα and the [O III] or Hα line velocities, and the only detected C IV and He II lines in the sample, implying that a hard ionizing source, possibly an active galactic nucleus (AGN), is responsible for their lower optical depth. Using three measures—the velocity offset between the Lyα line and the nonresonant [O III] or Hα line (Δv {sub Lyα}), the offset of stacked interstellar metal absorption lines, and a new indicator, the spectrally resolved [O III] line profile—we study the kinematics of gas along the line of sight to galaxies within each blob center. These three indicators generally agree in velocity and direction and are consistent with a simple picture in which the gas is stationary or slowly outflowing at a few hundred km s{sup –1} from the embedded galaxies. The absence of stronger outflows is not a projection effect: the covering fraction for our sample is limited to <1/8 (13%). The outflow velocities exclude models in which star formation or AGNs produce 'super-' or 'hyper' winds of up to ∼1000 km s{sup –1}. The Δv {sub Lyα} offsets here are smaller than typical of Lyman break galaxies but similar to those of compact Lyα emitters (LAEs). The latter suggests a connection between blob galaxies and LAEs and that outflow speed cannot be a dominant factor in driving extended Lyα emission. For one Lyα blob (CDFS-LAB14), whose Lyα profile and metal absorption line offsets suggest no significant bulk motion, we use a simple radiative transfer model to make the first column density measurement of gas in an embedded galaxy, finding it consistent with a damped Lyα absorption system. Overall, the absence of clear inflow signatures suggests that the channeling of gravitational cooling radiation into Lyα is not significant over the radii probed here. However, one peculiar system (CDFS-LAB10) has a blueshifted Lyα component that is not obviously associated with any galaxy, suggesting either displaced gas arising from tidal interactions among blob galaxies or gas flowing into the blob center. The former is expected in these overdense regions where Hubble Space Telescope images resolve many galaxies. The latter might signify the predicted but elusive cold gas accretion along filaments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Core-shell metallic alloy nanopillars-in-dielectric hybrid metamaterials with magneto-plasmonic coupling

Combining plasmonic and magnetic properties, namely magneto-plasmonic coupling, inspires great research interest and the search for magneto-plasmonic nanostructure becomes considerably critical. In this work, we designed a nanopillar-in-matrix structure with core–shell alloyed nanopillars for both BaTiO 3 (BTO)-Au 0.5 Co 0.5 (AuCo) and BTO-Au 0.25 Cu 0.25 Co 0.25 Ni 0.25 (AuCuCoNi) hybrid systems, i.e., ferromagnetic alloy cores (e.g., Co or CoNi) with plasmonic shells (e.g., Au or Au/Cu). These core–shell alloy nanopillars are uniformly embedded into a dielectric BTO matrix to form a vertically aligned nanocomposite (VAN) structure. Both hybrid systems present excellent epitaxial quality and interesting multi-functionality, e.g., high magnetic anisotropy, magneto-optical coupling response, tailorable plasmonic resonance wavelength, tunable hyperbolic properties and strong optical anisotropy. These alloyed nanopillars-in-matrix designs provide enormous potential for complex hybrid material designs with multi-functionality and demonstrate strong interface enabled magneto-plasmonic coupling along with plasmonic and magnetic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Simple bond-order-type interatomic potential for an intermixed Fe-Cr-C system of metallic and covalent bondings in heat-resistant ferritic steels

It is known that M{sub 23}C{sub 6}(M = Cr/Fe) behavior in heat-resistant ferritic steels affects the strength of the material at high temperature. The ability to garner direct information regarding the atomic motion using classical molecular dynamics simulations is useful for investigating the M{sub 23}C{sub 6} behavior in heat-resistant ferritic steels. For such classical molecular dynamics calculations, a suitable interatomic potential is needed. To satisfy this requirement, an empirical bond-order-type interatomic potential for Fe-Cr-C systems was developed because the three main elements to simulate the M{sub 23}C{sub 6} behavior in heat-resistant ferritic steels are Fe, Cr, and C. The angular-dependent term, which applies only in non-metallic systems, was determined based on the similarity between a Finnis-Sinclair-type embedded-atom-method interatomic potential and a Tersoff-type bond-order potential. The potential parameters were determined such that the material properties of Fe-Cr-C systems were reproduced. These properties include the energy and lattice constants of 89 crystal structures; the elastic constants of four realistic precipitates; the bulk moduli of B1, B2, and B3 crystals; the surface energies of B1 and B2 crystals; and the defect-formation energies and atomic configurations of 66 Fe-Cr-C complexes. Most of these material properties were found to be reproduced by our proposed empirical bond-order potentials. The formation energies and lattice constants of randomly mixed Fe-Cr alloys calculated using the interatomic potentials were comparable to those obtained through experiments and first-principles calculations. Furthermore, the energies and structures of interfaces between Cr carbide and α-Fe as predicted through first-principles calculations were well reproduced using these interatomic potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Projector-Free Capped-Fragment Scheme within Density Functional Embedding Theory for Covalent and Ionic Compounds

Quantum-mechanics-(QM)-based simulations now routinely aid in understanding and even discovering new chemistries involving molecules and materials exhibiting desired functionalities. Ab initio correlated wavefunction (CW) theories systematically improve QM methods, with many exhibiting high accuracy. However, execution of CW methods requires expensive computations that typically scale poorly with system size. Divide-and-conquer approaches partition large systems into smaller fragments; a lower level of theory treats fragment interactions while a preferred higher level of theory describes the important fragment. These methods offer ways to incorporate CWs into chemical simulations of large systems, e.g., biomolecules, surfaces, large inorganic clusters, bulk crystals, etc. Here we propose a partitioning protocol that utilizes capping atoms to saturate severed covalent bonds at fragment interfaces and density functional embedding theory (DFET) to describe fragment interactions. The capping groups in each fragment provide an ad-hoc potential that approximates the effects of the environment. An embedding potential optimized via DFET then serves as an augmentation of the capping group to simulate the effects of the environment. We concurrently use an auxiliary fragment (a separate system comprised of only the combined capping groups) to account for, and thereby correct, the electron density contributions of all the capping groups added to all of the fragments. This method depends only on the capped-subsystem and auxiliary-fragment electron densities, forgoing, as with the original DFET developed for metallic systems, orbital-based projector approaches that determine a nonlocal action of the embedding potential onto the fragment electrons. By using an auxiliary fragment, the method maintains a purely electron-density-dependent embedding potential, substantially lessening the cost and leading to simpler implementation. In this work, we demonstrate the utility of our capped-DFET and ensuing capped embedded CW method in two contrasting systems, namely, an organic molecule and an ionic metal oxide cluster.

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

A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds

Abstract Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale environment is in statistical equilibrium with a large number of small and short‐lived convective clouds. They fail to capture nonequilibrium transitions such as the diurnal cycle and the formation of mesoscale convective systems as well as observed precipitation statistics and extremes. Informed by analysis of radar observations, cloud‐permitting model simulation, theory, and machine learning, this work presents a new stochastic cloud population dynamics model for characterizing the interactions between convective and stratiform clouds, with the goal of informing the representation of these interactions in global climate models. Fifteen wet seasons of precipitating cloud observations by a C‐band radar at Darwin, Australia are fed into a machine learning algorithm to obtain transition functions that close a set of coupled equations relating large‐scale forcing, mass flux, the convective cell size distribution, and the stratiform area. Under realistic large‐scale forcing, the derived transition functions show that, on the one hand, interactions with stratiform clouds act to dampen the variability in the size and number of convective cells and therefore in the convective mass flux. On the other, for a given convective area fraction, a larger number of smaller cells is more favorable for the growth of stratiform area than a smaller number of larger cells. The combination of these two factors gives rise to solutions with a few convective cells embedded in a large stratiform area, reminiscent of mesoscale convective systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

eQE: An open‐source density functional embedding theory code for the condensed phase

Abstract In this work, we present the main features and algorithmic details of a novel implementation of the frozen density embedding (FDE) formulation of subsystem density functional theory (DFT) that is specifically designed to enable ab initio molecular dynamics (AIMD) simulations of large‐scale condensed‐phase systems containing 1000s of atoms. This code (available at http://eqe.rutgers.edu ) has been given the moniker of embedded Quantum ESPRESSO (eQE) as it is a generalization of the open‐source Quantum ESPRESSO (QE) suite of programs. The strengths of eQE reside in a hierarchical parallelization scheme that allows for an efficient and fully self‐consistent treatment of the electronic structure (via the addition of an additional DIIS extrapolation layer) while simultaneously exploiting the inherent symmetries and periodicities in the system (via sampling of subsystem‐specific first Brillouin zones and utilization of subsystem‐specific basis sets). While bulk liquids and molecular crystals are two classes of systems that exemplify the utility of the FDE approach (as these systems can be partitioned into weakly interacting subunits), we show that eQE has significantly extended this regime of applicability by outperforming standard semilocal Kohn–Sham DFT (KS‐DFT) for large‐scale heterogeneous catalysts with quite different layer‐specific electronic structure and intrinsic periodicities. eQE features very favorable strong parallel scaling for a model system of bulk liquid water composed of 256 water molecules, which allows for a significant decrease in the overall time to solution when compared to KS‐DFT. We show that eQE achieves speedups greater than one order of magnitude ( ) when performing AIMD simulations of such large‐scale condensed‐phase systems as: (1) molecular liquids via bulk liquid water represented by 1024 independent water molecules (3072 atoms with a 25.3× speedup over KS‐DFT), (2) polypeptide/biomolecule solvation via ( gly ) 6 solvated in (H 2 O) 395 (1230 atoms with a 38.6× speedup over KS‐DFT), and (3) molecular crystals via a 3 × 3 × 3 periodic supercell of pentacene (1940 atoms with a 12.0× speedup over KS‐DFT). These results represent a significant improvement over the current state‐of‐the‐art and now enable subsystem DFT‐based AIMD simulations of realistically sized condensed‐phase systems of interest throughout chemistry, physics, and materials science.

Genova, Alessandro↗