SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Predictions of high thermoelectric performance in RECuZnP 2 were verified by elastic, electrical, and thermal measurements. Low thermal conductivities result from strong anharmonicity, with electron transport limited by polar optical phonons.
The next-generation indium-based lead-free halide material Cs 2 InAgCl 6 is promising for photovoltaic applications due to its good air stability and non-toxic behavior while it shows good thermoelectric properties when doped with Pb.
The solvation shell structures of Ca 2+ in solutions are probed by calcium L-edge soft X-ray XAS and DFT/MD simulations.
From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.
Structure-driven evolution of magnetic behaviour of AuCo nanoparticles showcases efficacy of the elementary intermixing in enhancing magnetisation and magnetic anisotropy.
We report the synthesis and structure of the most highly distorted four-coordinate d 3 ion known to date that also serves as the second known example of a bis(biphenolato) transition metal complex. We demonstrate the application of density functional theory to calculate the magnetic parameters derived from the experimental and simulated EPR spectra.
High reducible distorted bimetallic sites with medium size in Ni 5 Co 5 -AC promoted the production of cyclohexanol by hydrogenation of anisole and subsequent cleavage of C 6 H 11 O–CH 3 bond.
Appropriately identifying and treating molecules and materials with significant multi-reference (MR) character is crucial for achieving high data fidelity in virtual high-throughput screening (VHTS). Despite development of numerous MR diagnostics, the extent to which a single value of such a diagnostic indicates the MR effect on a chemical property prediction is not well established. We evaluate MR diagnostics for over 10 000 transition-metal complexes (TMCs) and compare to those for organic molecules. We observe that only some MR diagnostics are transferable from one chemical space to another. By studying the influence of MR character on chemical properties (i.e., MR effect) that involve multiple potential energy surfaces (i.e., adiabatic spin splitting, ΔE H–L , and ionization potential, IP), we show that differences in MR character are more important than the cumulative degree of MR character in predicting the magnitude of an MR effect. Motivated by this observation, we build transfer learning models to predict CCSD(T)-level adiabatic ΔE H–L and IP from lower levels of theory. By combining these models with uncertainty quantification and multi-level modeling, we introduce a multi-pronged strategy that accelerates data acquisition by at least a factor of three while achieving coupled cluster accuracy (i.e., to within 1 kcal mol –1 MAE) for robust VHTS.
In addition to the semiconducting phase in AgNi 0.66 Co 0.33 O 2 , it is found that the coexistence of metallic phase when more than x = 0.33 of Co dopant is substituted in the single layer of NiO 2 in AgNi 0.66 Co 0.33 O 2 .
The interactions between Hf and CO are studied using multi-reference, couple cluster, and density functional theory. Calculations suggest that B3LYP is suitable for representing both molecular and solid-state models of Hf-CO interactions.
Non-equilibrium plasma has been found to have a synergistic effect on catalytic synthesis of NH 3 .
The impact of explicit water molecules on the binding of two rare earth nitrate aqua complexes, [X(NO 3 ) 3 (H 2 O) n ] (X = Nd, Yb), has been explored on both the internal pores and external surfaces of MCM-22.
The optical properties of the tetragonal phase of BaTiO 3 have been studied using density functional methods, applying the generalized gradient approximation at room temperature and a hybrid functional for static lattice analysis.
A schematic for the preparation of a g-C 3 N 4 -CNT/S composite cathode for lithium–sulfur batteries.
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.
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.
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.
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.