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DOE OSTI2025

High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

A reformation in energy is underway to replace fossil fuels with renewable sources, driven by the development of new, robust, and multi-functional materials. High-entropy materials (HEMs) have emerged as promising candidates for various green energy applications, having unusual chemistries that give rise to remarkable functionalities. This review examines recent innovations in HEMs, focusing on hydrogen generation/storage, fuel cells, batteries, semiconductors/electronics, and catalysis—where HEMs have demonstrated the ability to outperform state-of-the-art materials. We present new master plots that illustrate the superior performance of HEMs compared to conventional systems for hydrogen generation/storage and heat-to-electricity conversion. We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. The review also presents current challenges and proposes future directions for the field. We emphasize the need for continued integration of modeling, data, and experiments to investigate and leverage the underlying mechanisms of the HEMs that are powering progress in sustainable energy.

batteries↗

DOE OSTI2023

Solvation of furfural at metal–water interfaces: Implications for aqueous phase hydrogenation reactions

Metal–water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces’ degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal–water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal–water interfaces compared to the metal–gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. In conclusion, our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates.

aqueous-phase hydrogenation↗

DOE OSTI2024

First-principles calculation of lattice distortion, electronic structure, and bonding properties of GeTe-based and PbSe-based high-entropy chalcogenides

The massive amount of wasted heat energy from industry has pushed the development of thermoelectric (TE) materials that directly convert heat into electricity to a new level of concern. Recently, multicomponent alloys such as GeTe-based and PbSe-based high-entropy (HE) chalcogenides have attracted a great deal of attention due to their potential application as TE materials. The nature of the interatomic bonding, lattice distortion (LD), and the electronic structure in this class of materials is not fully understood. Herein, we report a comprehensive computational investigation of nine GeTe-based HE alloys with eight metallic elements (Ag, Pb, Sb, Bi, Cu, Cd, Mn, and Sn) with large supercells of 1080 atoms each; seven PbSe-based HE solid solutions: Pb0.99−ySb0.012SnySe1−2xTexSx (x = 0.1, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, with y = 0) with supercells of 1000 atoms each; and five Pb0.99−ySb0.012SnySe1−2xTexSx (y = 0.05, 0.1, 0.15, 0.2, 0.25 with x = 0.25) solid solutions with supercells of 1000 atoms each. All these HE models are theoretically investigated for the first time. The electronic structure, interatomic bonding, charge transfer, and lattice distortion (LD) are investigated by first-principles calculations based on density functional theory. Multicomponent HE alloys can cause a significant LD, which affects their mechanical, thermal, and TE properties. The calculations for the GeTe-based HE chalcogenides showed that they are semiconductors with a narrow bandgap, except for m8, which has a semi-metallic characteristic, and this makes them good candidates for TE applications. For most of these models, the Fermi level shifts upward and locates deeply in the conduction bands, resulting in the enhancement of the electrical conductivity (σ). The bonding properties showed that most bonds in m5 are more dispersed, indicating highest LD and lower lattice thermal conductivity. For PbSe-based HE solid solutions, the LD calculations showed that the models Pb0.99Sb0.012Se0.5Te0.25S0.25 and Pb0.89Sb0.012Sn0.1Se0.5Te0.25S0.25 have the higher LD, and thus a lower lattice thermal conductivity. Such investigations are in high demand since it enables us to design new HE chalcogenides for TE applications. We use the novel concept of total bond order density as a single quantum mechanical metric to characterize the internal cohesion of these HE alloys and correlate with calculated properties, especially the mechanical properties. This work provides a solid database for HE chalcogenides and a road map for many potential applications. Moreover, the computational procedure we developed can be used to design new HE chalcogenides for specific TE applications.

Physics↗

DOE OSTI2021

Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed. While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Here, starting with 70 150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

08 HYDROGEN↗

DOE OSTI2021

Energy barriers for Dy and H penetrating graphene on 6 H -SiC(0001) and freestanding bilayer graphene from first-principles calculations

Currently, intercalation of foreign guest atoms into two-dimensional (2D) layered van der Waals materials is an active research area motivated in part by the development of next-generation energy-storage technologies and optoelectronic devices. One such extensively studied 2D material is the graphene-on-SiC system. To realize and control the desired intercalated structures, it is fundamentally important to understand the kinetic process of intercalation. For the intercalation of a guest atom into graphene layers on SiC substrate, a critical kinetic parameter is the energy barrier of a guest atom penetrating the perfect graphene top layer into the gallery under it. However, accurate theoretical calculations for such penetration barriers are unavailable in literature. From our first-principles density functional theory calculations, we obtain the global energy barriers of 3.47 and 1.80 eV for single Dy and H atoms penetrating the graphene top layer on a graphene buffer layer supported by a Si-terminated 6H-SiC(0001) substrate, respectively. Furthermore, for comparison as well as for examining the lateral strain effects, we also obtain the global barriers of 5.05 and 1.50 eV for single Dy and H atoms penetrating freestanding bilayer graphene with a tensile strain of about 8.8% to match our model for supported graphene, as well as the global barriers of 7.21 and 4.18 eV for penetrating unstrained freestanding bilayer graphene, respectively. From corresponding minimum energy paths with multiple energy minima and saddle points, we can also obtain various local energy barriers and the global backward barrier from the graphene gallery back to the top surface.

2D materials↗

DOE OSTI2024

Classical and quantum computing of shear viscosity for ( 2 + 1 ) D SU(2) gauge theory

We perform a nonperturbative calculation of the shear viscosity for ( 2 + 1 )-dimensional SU(2) gauge theory by using the lattice Hamiltonian formulation. The retarded Green’s function of the stress-energy tensor is calculated from real time evolution via exact diagonalization of the lattice Hamiltonian with a local Hilbert space truncation, and the shear viscosity is obtained via the Kubo formula. When taking the continuum limit, we account for the renormalization group flow of the coupling but no additional operator renormalization. We find the ratio of the shear viscosity and the entropy density η s is consistent with a well-known holographic result 1 4 π at several temperatures on a 4 × 4 honeycomb lattice with the local electric representation truncated at j max = 1 2 . We also find the ratio of the spectral function and frequency ρ x y ( ω ) ω exhibits a peak structure when the frequency is small. Both the exact diagonalization method and simple matrix product state classical simulation method beyond j max = 1 2 on bigger lattices require exponentially growing resources. So we develop a quantum computing method to calculate the retarded Green’s function and analyze various systematics of the calculation including j max truncation and finite size effects, Trotter errors and the thermal state preparation efficiency. Our thermal state preparation method still requires resources that grow exponentially with the lattice size, but with a very small prefactor at high temperature. We test our quantum circuit on both the Quantinuum emulator and the IBM simulator for a small lattice and obtain results consistent with the classical computing ones. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

A 3D porous honeycomb carbon as Na-ion battery anode material with high capacity, excellent rate performance, and robust stability

Motivated by the synthesis of three-dimensional (3D) honeycomb carbon structures and the subsequent theoretical prediction of an energetically more favorable hexagonal carbon phase composed of 28 carbon atoms in the unit cell (hC28) with ordered pores, excellent mechanical properties, and metallic feature, we explore its potential for a Na-ion battery (NIB) anode material. Using density functional theory based calculations, we find that hC28 is a promising candidate whose specific capacity of 717 mAh/g is almost three times larger than that of hard carbon (~250 mAh/g). In addition, migration barrier of Na ions along the honeycomb channel is only 0.08 eV and the volume change during the charging/discharging process is merely 2.30%, which are much less than those of other carbon-based NIB anode materials. The average voltage is also low (0.36 eV) which can provide high operating voltage when connected to the cathode. Finally, these encouraging results would pave the way towards the development of hC28 as NIB anode with high capacity, excellent rate performance, low open-circuit voltage, and long-term cycle life.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Single-atom catalysts with anionic metal centers: promising electrocatalysts for the oxygen reduction reaction and beyond

Ongoing efforts to develop single-atom catalysts (SACs) for the oxygen reduction reaction (ORR) typically focus on SACs with cationic metal centers, while SACs with anionic metal centers (anionic SACs) have been generally neglected. However, anionic SACs may offer excellent active sites for ORR, since anionic metal centers could facilitate the activation of O2 by back donating electrons to the antibonding orbitals of O2. In this work, we propose a simple guideline for designing anionic SACs: the metal centers should have larger electronegativity than the surrounding atoms in the substrate on which the metal atoms are supported. By means of density functional theory (DFT) simulations, we identified 13 anionic metal centers (Co, Ni, Cu, Ru, Rh, Pd, Ag, Re, Os, Ir, Pt, Au, and Hg) dispersed on pristine or defective antimonene substrates as new anionic SACs, among which anionic Au and Co metal centers exhibit limiting potentials comparable to, or even better than, conventional Pt-based catalysts towards ORR. We also found that anionic Os and Re metal centers on the defective antimonene can electrochemically catalyze the nitrogen reduction reaction (NRR) with a limiting potential close to that of stepped Ru(0001). Overall, our work shows promise towards the rational design of anionic SACs and their utility for applications as electrocatalysts for ORR and other important electrochemical reactions.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Oxygen Evolution on Iron Oxide Nanoparticles: The Impact of Crystallinity and Size on the Overpotential

The oxygen evolution reaction (OER) is a critical reaction in electrolysis and photoelectrolysis of water to generate and store clean energy. Therefore, the development of low-cost and efficient electrocatalysts for the OER is of great scientific and technological importance. Although promising iron oxide-based electrocatalysts have been recently developed for the OER, an in-depth experimental and theoretical analysis of the OER mechanism on iron oxide-based electrocatalysts is still needed to provide guidelines to optimize the performance of iron oxide-based electrocatalysts further. To address this need, we synthesized a series of monodisperse iron oxide nanoparticles to analyze their intrinsic OER activities. Using nanoparticles of the same size but different crystallinity, we show that amorphous iron oxide nanoparticles have better OER activity than crystalline ones. The size effect studies further revealed that the edge/defect sites are the active sites for the OER. Density functional theory calculations demonstrated that the edge/defect sites provide bridge sites to adsorb OER intermediates, resulting in low OER overpotential. These calculations confirm that the high OER activity of amorphous nanoparticles results from a high concentration of defect sites on their surface. These results provide novel strategies to increase the performance of iron oxide-based and likely other oxide-based OER electrocatalysts.

Electrochemistry↗

DOE OSTI2022

Rotational symmetry relation for efficient response function generation in the coarse mesh transport method COMET

The coarse mesh transport code COMET is a continuous energy hybrid stochastic-deterministic neutronics solver with high fidelity and formidable computation speed in solving reactor core problems. Its method is based on the incident flux expansion theory. In this work, we take advantage of the local geometric symmetry in many reactor cores lattices (e.g., fuel lattices and reflector blocks) to develop relations among the flux response expansion coefficients for symmetric surfaces to further improve the computational efficiency of the COMET response function generation tool (method). This is done by a rigorous derivation of the transformation matrices for the angular and spatial expansion moments resulting from a rotation of a coarse mesh by an arbitrary angle. The relations for the response coefficients for the symmetric surfaces can be then written as the Kronecker product of those transformation matrices. The method is implemented into COMET and tested on two advanced high temperature reactor (AHTR) full-length single assembly benchmark problems. The COMET results using the response function library based on the symmetry relations were compared to those using the library directly generated by continuous energy Monte Carlo for all surfaces. It was found that the eigenvalues and stripe-wise fission densities using the two libraries are in statistical agreement as expected. This indicates that the new method maintains the high fidelity of the original COMET method while improving the computational efficiency in the response function generation by 270% to 400%, depending on the local geometric symmetry. This method also reduces the size of the response function library by the same magnitude (270% to 400%). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Wavelength-Dependent Excitonic Properties of Covalent Organic Frameworks Explored by Theory and Experiments

Many aspects of the correlation between physical structure, light harvesting, and excitonic properties of covalent organic frameworks (COFs) remain unclear despite being key properties determining their photocatalytic function. One area of COF research that could bring clarity is through using both electronic structure theory and time-resolved spectroscopic analysis over a series of isomeric COFs. Here, we show structure-property relationships between four imine COFs built from a combination of ditopic and tritopic monomers using transient absorption spectroscopy together with time-dependent density functional theory. We find that monomer selection only moderately affects the charge transfer (CT) behavior of the COFs. Instead, we infer that imine chemistry profoundly impacts CT by acting as a CT mediator. Moreover, we discover two distinct valence bands arising from varying degrees of locally excited/CT mixing, which is responsible for energy dependent exciton dynamics. Finally, we use theory to hypothesize that interlayer interactions can modify excitonic properties that we correlate with tail states commonly observed, but rarely investigated in COFs. Furthermore, these results reveal that imine chemistry should be recognized as a very important factor to consider in the development of COF photocatalysts and the correlation of their structural environment with light harvesting and CT properties that should ultimately determine their photocatalytic function.

14 SOLAR ENERGY↗

DOE OSTI2025

International Workshop on Electronic Structure 2024 (ES 24)

The 36th annual Workshop on Recent Developments in Electronic Structure Theory commenced on June 2-5, 2024 at Boston University with 136 in-person and 75 virtual attendees. The organizing committee was composed of five faculty at Boston University with seven local area faculty comprising the greater Boston area advisory committee. On the first day, two hands-on workshops, NEXMD and ComDMFT were held on June 2, two full days of presentations were held on June 3-4 and one half day on June 5. There were 19 invited speakers who spoke about the state-of-the-art in electronic structure methods, including density functional theory, many-body perturbation theory, and the incorporation of machine learning into electronic structure calculations. In addition, 45 young scientists presented posters on June 4. Housing at a reduced rate was provided at the Boston University dormitories. This conference provided a valuable opportunity for scientists, students, postdocs, and senior researchers alike, to disseminate their latest research results, discuss their ideas and best practices, learn from each other, and form new collaborations.

42 ENGINEERING↗

DOE OSTI2024

Defect Thermodynamics and Transport Properties of Perovskite and Fluorite Materials for Solid-Oxide and Proton Conducting Oxide Cells Evaluated Based on Density Functional Theory Modeling

Density functional theory based defect thermodynamic modeling was performed to determine the effect of humidity and H2/O2 gas pressure on various defect chemistry and transport properties of perovskite and fluorite oxides for solid-oxide and proton-conducting-oxide cell applications, with inclusion of the electronic-conducting oxides (as electrodes) and insulating oxides (as electrolytes). Automatic defect generation workflow and first-principles charged defect analysis were implemented on NETL Joule supercomputer for modeling defect equilibria and transport properties of insulating oxides as electrolytes in SOCs and proton-conducting ceramic cells. A GNU Octave defect model subroutines were developed to facilitate defect modeling of electronic conducting oxides in a wide range of operating conditions guided by modeling and experiments. The model includes the hydride defect formation reaction under reducing conditions and allows to incorporate nonstoichiometry effects on the defect thermodynamic parameters. The developed model serves as a platform to facilitate fundamental understanding of the defect thermodynamics in SOC oxide materials and can be used as a novel tool in computational materials screening for SOC and other energy applications.

Lee, Yueh-Lin↗

DOE OSTI2025

Cobalt–Nickel Exchange in Exfoliated Battery Layered Cathode Sheets with Application to Recycling

With the emerging dominance of electric vehicles (EV) in the transportation sector, recycling or upcycling spent battery materials will be required to reduce EV costs, lessen waste, and ease critical material supply chain issues for EV batteries. Here, motivated by work in the literature describing the exfoliation of layered oxides, first‐principles calculations are performed to show that Li x CoO 2 , if exfoliated into nanosheets, can readily undergo transition metal cation exchange in aqueous media. The substitution of Co 3+ or Co 4+ cations inside the sheet by Ni 2+ is associated with modest reaction barriers (Δ G* ≈ 0.3–0.7 eV) and is at most mildly endothermic (Δ G ≈ 0.2–0.3 eV). In contrast, previous battery degradation studies have shown that Co 3+ diffusion is strongly inhibited inside bulk layered oxides. This suggests that processing spent layered oxides as nanosheets can provide a potentially low‐energy‐cost pathway to altering the transition metal and/or dopant stoichiometry, which can be used toward developing new room‐temperature upcycling routes for cathodes from end‐of‐life batteries.

battery recycling↗

DOE OSTI2024

Additively manufactured Ni-20Cr to V functionally graded material: Computational predictions and experimental verification of phase formations

Throughout this work, a database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Real-space visualization of short-range antiferromagnetic correlations in a magnetically enhanced thermoelectric

Short-range magnetic correlations can significantly increase the thermopower of magnetic semiconductors, representing a noteworthy development in the decades-long effort to develop high-performance thermoelectric materials. Here, we reveal the nature of the thermopower-enhancing magnetic correlations in the antiferromagnetic semiconductor MnTe. Using magnetic pair distribution function analysis of neutron scattering data, we obtain a detailed, real-space view of robust, nanometer-scale, antiferromagnetic correlations that persist into the paramagnetic phase above the Neel temperature $T_N$ = 307 K. In this work, the magnetic correlation length in the paramagnetic state is significantly longer along the crystallographic c axis than within the ab plane, pointing to anisotropic magnetic interactions. Ab initio calculations of the spin-spin correlations using density functional theory in the disordered local moment approach reproduce this result with quantitative accuracy. These findings constitute the first real-space picture of short-range spin correlations in a magnetically enhanced thermoelectric and inform future efforts to optimize thermoelectric performance by magnetic means.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗