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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 235 records · Page 13

Bandgap engineering of SrZrS 3 chalcogenide perovskite via substitutional doping for photovoltaic applications: a first-principles DFT study

Strontium zirconium sulfide (SrZrS 3 ) has garnered significant attention for photovoltaic (PV) applications due to its excellent optoelectronic properties, high chemical and moisture stability, and non-toxicity. However, the bandgaps of both the α- and β-phases lie outside the optimum ranges for both single-junction solar cells (SJSCs) and tandem solar cells (TSCs), thereby limiting their applications in PV technologies. In this study, we employed hybrid density functional theory to engineer the band gaps of α- and β-SrZrS 3 through substitutional doping. We considered three dopants (Hf, Sn, and Ti) at the Zr site of SrZrS 3 with varying doping concentrations and investigated their effects on the structural, electronic, and optical properties of the materials. We found that Sn and Ti doping effectively lowers the band gaps of both α- and β-SrZrS 3 , whereas Hf doping increases them. For x values up to 0.25, the band gaps of the α-SrZr 1−x Sn x S 3 and α-SrZr 1−x Ti x S 3 are within the optimum range for SJSCs, and those of β-SrZr 1−x Sn x S 3 and β-SrZr 1−x Ti x S 3 lie within the optimum range for Si/perovskite as well as perovskite/perovskite TSCs. The three dopants exhibited significant effects on the optical properties of both α- and β-SrZrS 3 , including the absorption coefficient, energy-loss functions, reflectivity, and refractivity spectra. Thermodynamic stability analysis revealed that for both phases, SrZr 1−x Hf x S 3 can be synthesized via exothermic processes, whereas the formation of SrZr 1−x Ti x S 3 and SrZr1−xSn x S 3 is endothermic and hence, not thermodynamically favorable. Further analysis showed that SrZr 1−x Ti x S 3 in both α- and β-phases are stable under thermodynamic equilibrium conditions, whereas SrZr 1−x Sn x S 3 is prone to dissociation into ternary phases (SrZrS 3 and SrSnS 3 ), especially at higher doping concentrations. These results show that Ti doping is effective in tuning the band gaps of α- and β-SrZrS 3 toward the optimal values for PV applications.

14 SOLAR ENERGY↗

Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

Machine-learned interatomic potentials (MLIPs) are revolutionizing computational materials science and chemistry by offering an efficient alternative to ab initio molecular dynamics (MD) simulations. However, fitting high-quality MLIPs remains a challenging, time-consuming, and computationally intensive task where numerous trade-offs have to be considered, e.g., How much and what kind of atomic configurations should be included in the training set? Which level of ab initio convergence should be used to generate the training set? Which loss function should be used for fitting the MLIP? Which machine learning architecture should be used to train the MLIP? The answers to these questions significantly impact both the computational cost of MLIP training and the accuracy and computational cost of subsequent MLIP MD simulations. In this study, we use a configurationally diverse beryllium dataset and quadratic spectral neighbor analysis potential. We demonstrate that joint optimization of energy versus force weights, training set selection strategies, and convergence settings of the ab initio reference simulations, as well as model complexity can lead to a significant reduction in the overall computational cost associated with training and evaluating MLIPs. This opens the door to computationally efficient generation of high-quality MLIPs for a range of applications which demand different accuracy versus training and evaluation cost trade-offs.

36 MATERIALS SCIENCE↗

High electron mobility of Al x Ga1− x N evaluated by unfolding the DFT band structure

We calculate the alloy-disorder-limited electron mobility of AlxGa1−xN from first principles. AlxGa1−xN is a technologically important ultra-wide-bandgap alloy with promise in light emitting diodes and high-power transistors. Alloying introduces statistical disorder, which causes electrons to scatter between different crystal-momentum states, leading to a reduction in mobility for intermediate alloy compositions. The corresponding lifetime, which appears as an energy broadening in the band structure, can be evaluated by unfolding the band structure from the supercell basis to the primitive-cell basis. We fit the first-principles band broadening with a model scattering potential and evaluate the low-field electron mobility using the semiclassical Boltzmann transport equation in the relaxation-time approximation. Our calculated mobility is in agreement with experimental values. We also find the lowest alloy-scattering electron mobility (total electron mobility) across the entire composition range to be 186 cm2/V s (136 cm2/V s), which is comparable to the highest electron mobility predicted in the competitor system, β-(AlxGa1−x)2O3. Our results elucidate the intrinsic limits imposed by alloy disorder on electron transport in AlxGa1−xN.

Pant, Nick (ORCID:0000000254506045)↗

Breaking atomic-level ordering via biaxial strain in functional oxides: A DFT study

Oxygen vacancies are found to play a crucial role in inducing many functional properties at the heterointerfaces in complex oxides. Gaining better control over the properties requires an understanding of the atomic structure of oxygen vacancies at the heterointerfaces. In this paper, we elucidate the effects of the interfacial strain on the oxygen-vacancy ordering in fluorite δ-Bi 2 O 3 and perovskite LaNiO 2.5 using first-principles calculations. By applying biaxial strains, we find that the <110>-<111> oxygen vacancy order in δ-Bi2O3 is broken, resulting in a faster diffusion of oxygen ions. Similarly, the biaxial strain is used to leverage both ordered and disordered arrangements of vacancies in LaNiO 2.5 . Besides the vacancy order, we find that the biaxial strain can also be used to break the cation order in Gd 2 Ti 2 O 7 , where Gd and Ti antisites can be created on the cation sublattice, which leads to enhanced radiation tolerance and higher oxygen diffusivity. Overall, these results indicate that the biaxial strain that is commonly present at heterointerfaces can be used to gain control over both ordered and disordered arrangements of defects, potentially opening new opportunities to functionalize complex oxides.

36 MATERIALS SCIENCE↗

Toward alcohol synthesis from CO hydrogenation on Cu(111)-supported MoS 2 – predictions from DFT+KMC

In the quest for cheap and efficient catalysts for alcohol synthesis from syngas, a material of interest is single-layer MoS2 owing to its low cost, abundancy, and flexible structure. Because of the inertness of its basal plane, however, it is essential to find ways that make it catalytically active. Herein, by means of density functional theory based calculations of reaction pathways and activation energy barriers and accompanying kinetic Monte Carlo simulations, we show that while S vacancy row structures activate the MoS 2 basal plane, further enhancement of chemical activity and selectivity can be achieved by interfacing the MoS 2 layer with a metallic support. When defect-laden MoS2 is grown on Cu(111), there is not only an increase in the active region (surface area of active sites) but also charge transfer from Cu to MoS 2 , resulting in a shift of the Fermi level such that the frontier states (d orbitals of the exposed Mo atoms) appear close to it, making the MoS 2 /Cu(111) system ready for catalytic activity. Finally, our calculated thermodynamics of reaction pathways lead to the conclusion that the Cu(111) substrate promotes both methanol and ethanol as the products, while kinetic Monte Carlo simulations suggest a high selectivity toward the formation of ethanol.

2D materials↗

DFT-based insight into finite-temperature properties of ferroelectric perovskites with lone-pair: the case of CsGeX 3 (X = Cl, Br, I)

Ferroelectrics remain in the focus of scientific attention for decades owing to their fundamental and practical appeal. Recently, ferroelectricity has been demonstrated in semiconducting halide perovskites (Zhang et al 2022 Sci. Adv. 8 eabj5881), offering both a rare combination of ferroelectricity and semiconductivity in the same material and a possible alternative to the prevailing perovskite oxide ferroelectrics. We propose a route to simulating such materials at finite temperatures capable of reproducing key experimental and first-principle data, such as Curie temperature, phase transition sequence, spontaneous polarization, and soft mode frequencies. The key methodological finding is the superior performance of hybrid exchange correlation functionals in parametrization of effective Hamiltonians for ferroelectrics with lone pair. The parametrization for effective Hamiltonians for CsGeX 3 (X = Cl, Br, I) is reported. The application of methodology to study polarization reversal in CsGeX 3 allows for the development of a ‘minimalistic’ model for polarization reversal in ferroelectrics that provides an insight into the mechanisms of polarization reversal and its key features, such as the relationship between the coercive field, temperature, and AC field frequency. Importantly, the model reveals the origin of the well-known and ever-puzzling overestimation of coercive fields in computations. Furthermore, we report a variety of finite-temperature properties of CsGeX 3 ferroelectrics, such as dielectric susceptibility, pyroelectric coefficients, and energy storage density, which reveal that these halide perovskites possess properties comparable to their oxide counterparts. Here, we believe that our work provides significant methodological advancements, deepens fundamental understanding of ferroelectrics, and reveals the potential of halide perovskite ferroelectrics.

effective Hamiltonian↗

Ab initio modeling and experimental investigation of Fe 2 P by DFT and spin spectroscopies

Fe 2 P alloys have been identified as promising candidates for magnetic refrigeration at room-temperature and for custom magnetostatic applications. The intent of this study is to accurately characterize the magnetic ground state of the parent compound, Fe 2 P, with two spectroscopic techniques, μSR and NMR, in order to provide solid bases for further experimental analysis of Fe 2 P-type transition metal based alloys. Herein, we perform zero applied field measurements using both techniques below the ferromagnetic transition T C = 220 K. The experimental results are reproduced and interpreted using first principles simulations, validating this approach for quantitative estimates in alloys of interest for technological applications.

36 MATERIALS SCIENCE↗

A Density Functional Theory (DFT) Study on the Effect of Chlorine in the Magnesium Zinc Oxide (MZO) Front Interface for Cadmium Telluride (CdTe) Thin Film Solar Cells

Cadmium telluride photovoltaics has benefitted greatly from the cadmium chloride treatment which causes a remarkable improvement in cell efficiencies. This work investigates the effect of elemental chlorine at the interface between the magnesium zinc oxide front contact and the cadmium telluride absorber in such a device. Band alignment including band bending and interface states and its role in potential charge carrier transport is the key feature studied. It is seen that a small amount of chlorine is leads to a more desirable band alignment. Higher concentrations of chlorine result in unfavorable band characteristics.

14 SOLAR ENERGY↗

Role of Pr-Vacancies and O-Interstitials on the Activity and Stability of (Pr 1−x Ln x ) 2 NiO 4 (Ln = La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) towards Oxygen Reduction Reactions: A DFT Study

Praseodymium nickelate, Pr 2 NiO 4 (PNO), is a promising electrode to promote oxygen reduction reaction (ORR) in a solid oxide fuel cell, but it exhibits phase transformation during electrochemical operation. The origin of the simultaneous phase transformation and high electrochemical performance remains obscure. We carried out a systematic density functional theory study to elucidate the mechanism for this conjugated phenomenon. Charge, electronic structure, and normal-mode analysis suggest the presence of peroxide. Our study shows that the formation of peroxide (O 2 2– ) is attributed to both oxygen interstitials and Pr vacancies. The peroxide species limits the oxygen ion migration due to the additional energy required to break its O–O bond, which leads to a decrease in ORR activity. Subsequently, we investigate the diffusion paths of Pr-ions while comparing them with those of other Ln 3+ ions (La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO. The formation energies for various Ln 3+ cation occupancies are calculated, as well as segregation energies in CeO 2 (111) surfaces. Lastly, criteria for effective Ln 3+ dopants are developed. La, Nd, and Pm are proposed as potential substituents in PNO to obtain a stable structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Fe 2 O 3 (0001) Surface Under Electroreduction Conditions: A DFT Study of L-Cysteine Adsorption

Local catalyst surface structure and environment can play a significant role towards catalytic activity and selectivity. Surface functionalization using organic additives, such as amino acid chains or peptides, can alter surface properties. Density Functional Theory calculations are used to evaluate the potential dependent surface stability of different terminations of the Fe 2 O 3 (0001) surface. Adsorption of L-Cysteine in different redox states and through different binding modes (carboxylic: O-Fe, amine: N-Fe and thiol: S-Fe) is evaluated. At moderate electrochemical reducing conditions, Fe 2 O 3 (0001) exposes a partially reduced termination with both surface H atoms and undercoordinated Fe atoms in the outermost layer. L-Cysteine adsorption occurs most preferentially through carboxylic acid, O-Fe, binding and does not significantly alter the relative surface stability of different surface terminations. A partially reduced surface with L-Cysteine functionalization will be stable under electroreduction conditions. As a result, stable functionalization of an oxide material through amino acid chains or peptide adsorption may provide an additional design lever to develop improved catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GDB-9-Ex_TD-DFT-PBE0: Dataset containing Time Dependent Density Functional Theory (TDDFT) calculations for organic molecules of the GDB-9-Ex dataset.

This dataset contains data-intensive quantum chemical electronic structure calculations for 96,766 organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Time Dependent Density Functional Theory (TDDFT) first principles method using the ORCA software. It provides UV-vis spectra calculations of molecules with a high level of accuracy. The optical spectra behavior was collected based on the optimized molecular geometries in the DFTB method with 3ob parameters. All calculations utilized the def2-TZVP basis sets with the auxiliary def2/J and def2-TZVP/C basis sets. The time-dependent density-functional theory (TDDFT) approach with the PBE0 exchange-correlation functional and ORCAs default integration grid was employed. For the excitation energy calculations, the lowest 50 excitation states were calculated.

AI dataset↗

Simultaneous mitigation of density and energy errors in approximate DFT for transition metal chemistry (Final Technical Report)

There were three major goals and objectives of this project: 1) Develop tools to understand density-driven errors in transition metal complexes, 2) Evaluate and minimize energy delocalization error and static correlation error through judicious functional choice, and 3) applying this workflow to machine-learning accelerated screening of redox couples. Over the reporting period, we developed a framework for eliminating flat plane errors. We introduced fully non-empirical coefficients. We demonstrated the approach on both molecules and solids. We investigated and eliminated density driven errors and demonstrated their impact on potential energy surfaces. We trained machine learning models both in a method-dependent fashion and to predict errors in method accuracy. We built large data sets of small molecule energetics and multi-reference character.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗