Data-Driven Discovery of Intrinsic Direct-Gap 2D Materials as Potential Photocatalysts for Efficient Water Splitting

Intrinsic direct-gap two-dimensional (2D) materials hold great promise as photocatalysts, advancing the application of photocatalytic water splitting for hydrogen production. However, the time- and resource-efficient exploration and identification of such 2D materials from a vast compositional and structural chemical space present significant challenges within the realm of materials science research. To this end, we perform a data-driven study to find 2D materials with intrinsic direct-gap and desirable photocatalytic properties for overall water splitting. By implementing a three-staged large-scale screening, which incorporates machine-learned data from the V2DB, high-throughput density functional theory (DFT), and hybrid-DFT calculations, we identify 16 direct-gap 2D materials as promising photocatalysts. Subsequently, we conduct a comprehensive assessment of materials properties that are related to the solar water splitting performance, which include electronic and optical properties, solar-to-hydrogen conversion efficiencies, and carrier mobilities. Therefore, this study not only presents 16 2D photocatalysts but also introduces a rigorous data-driven approach for the future discovery of functional 2D materials from currently unexplored chemical spaces

Calculating the Circular Dichroism of Chiral Halide Perovskites: A Tight-Binding Approach

Chiral metal halide perovskites have emerged as promising optoelectronic materials for the emission and detection of circularly polarized visible light. Despite chirality being realized by adding chiral organic cations or ligands, the chiroptical activity originates from the metal halide framework. The mechanism is not well understood, as an overarching modeling framework is lacking. Capturing chirality requires going beyond electric dipole transitions, which is the common approximation in condensed matter calculations. We present a density functional theory (DFT) parametrized tight-binding (TB) model, which allows us to calculate optical properties including circular dichroism (CD) at low computational cost. Comparing Pb-based chiral perovskites with different organic cations and halide anions, we find that the structural helicity within the metal halide layers determines the size of the CD. Our results mark an important step in understanding the complex correlations of structural, electronic, and optical properties of chiral perovskites and provide a useful tool to predict new compounds with desired properties for novel optoelectronic applications

Anti-Ferromagnetic RuO₂: A Stable and Robust OER Catalyst over a Large Range of Surface Terminations

Rutile RuO2 is a prime catalyst for the oxygen evolution reaction (OER) in water splitting. Whereas RuO2 is typically considered to be non-magnetic (NM), it has recently been established as being anti-ferromagnetic (AFM) at room temperature. The presence of magnetic moments on the Ru atoms signals an electronic configuration that is markedly different from what is commonly assumed, the effect of which on the OER is unknown. We use density functional theory (DFT) calculations within the DFT+U approach to model the OER process on NM and AFM RuO2(110) surfaces. In addition, we model the thermodynamic stability of possible O versus OH terminations of the RuO2(110) surface and their effect on the free energies of the OER steps. We find that the AFM RuO2(110) surface gives a consistently low overpotential in the range 0.4–0.5 V, irrespective of the O versus OH coverage, with the exception of a 100% OH-covered surface, which is, however, unlikely to be present under typical OER conditions. In contrast, the NM RuO2(110) surface gives a significantly higher overpotential of ∼0.7 V for mixed O/OH terminations. We conclude that the magnetic moment of RuO2 supplies an important contribution to obtaining a low overpotential and to its insensitivity to the exact O versus OH coverage of the (110) surface

Native Defects and the Dehydrogenation of NaBH₄

Chemical reactions of hydrogen storage materials often involve mass transport through a bulk solid. Diffusion in crystalline solids proceeds by means of lattice defects. Using density functional theory (DFT) calculations, we identify the stability and the mobility of the most prominent lattice defects in the hydrogen storage material NaBH4. At experimental dehydrogenation conditions, the Schottky defects of missing Na+ and BH4– ions form the main vehicle for mass transport in NaBH4. Substituting a BH4– by a H– ion yields the most stable defect, locally converting NaBH4 into NaH. Such a substitution most likely occurs at the surface of NaBH4, releasing BH3. Adding Mg or MgH2 to NaBH4 promotes this scenario

Defects in Halide Perovskites: Does It Help to Switch from 3D to 2D?

Two-dimensional (2D) organic–inorganic hybrid iodide perovskites have been put forward in recent years as stable alternatives to their three-dimensional (3D) counterparts. Using first-principles calculations, we demonstrate that equilibrium concentrations of point defects in the 2D perovskites PEA2PbI4, BA2PbI4, and PEA2SnI4 (PEA, phenethylammonium; BA, butylammonium) are much lower than in comparable 3D perovskites. Bonding disruptions by defects are more destructive in 2D than in 3D networks, making defect formation energetically more costly. The stability of 2D Sn iodide perovskites can be further enhanced by alloying with Pb. Should, however, point defects emerge in sizable concentrations as a result of nonequilibrium growth conditions, for instance, then those defects likely hamper the optoelectronic performance of the 2D perovskites, as they introduce deep traps. We suggest that trap levels are responsible for the broad sub-bandgap emission in 2D perovskites observed in experiments

First-Principles Study of LiBH₄ Nanoclusters and Their Hydrogen Storage Properties

Recent experimental studies suggest faster desorption kinetics, improved reversibility, and more favorable thermodynamics for confined LiBH₄ nanoparticles as compared to bulk. We study the structures, total energies, and decomposition reactions of LiBH₄ nanoparticles using density functional theory calculations. We find that the reaction energies of nanoclusters with a diameter ≳2 nm are very close to that of bulk LiBH₄. Only very small clusters with a diameter <1 nm are significantly destabilized relative to the bulk. The thermodynamics of such small clusters is unfavorable, however, and leads to dehydrogenation temperatures that are higher than that of the bulk. Although small (LiBH₄)_<i>n</i> nanoclusters exhibit a number of different geometries, they show only little variation in the total energy per formula unit. Of all possible decomposition reactions of (LiBH₄)_<i>n</i>, the reaction where diborane is released, is unfavorable for most cluster sizes, whereas the hydrogen desorption reaction to Li₂H₁₂B₁₂ is most favorable. This suggests that the experimentally observed improvement of the (de)­hydrogenation properties of LiBH₄ can be attributed to an improvement of the kinetics of the latter reaction

Hydrogen Storage by Polylithiated Molecules and Nanostructures

We study polylithiated molecules as building blocks for hydrogen storage materials, using first-principles calculations. CLi4 and OLi2 bind 12 and 10 hydrogen molecules, respectively, with an average binding energy of 0.10 and 0.13 eV, leading to gravimetric densities of 37.8 and 40.3 wt % of H2. Bonding between Li and C or O is strongly polar and H2 molecules attach to the partially charged Li atoms without dissociating, which is favorable for (de)hydrogenation kinetics. CLin and OLim molecules can be chemically bonded to graphene sheets to hinder the aggregation of such molecules. In particular B- or Be-doped graphene strongly bind the molecules without seriously affecting the hydrogen binding energy. This still leads to a hydrogen storage capacity in the range of 5−8.5 wt % of H2

Probing the Reactivity of ZnO with Perovskite Precursors

To achieve more stable and efficient metal halide perovskite devices, optimization of charge transport materials and their interfaces with perovskites is crucial. ZnO on paper would make an ideal electron transport layer in perovskite devices. This metal oxide has a large bandgap, making it transparent to visible light; it can be easily n-type doped, has a decent electron mobility, and is thought to be chemically relatively inert. However, in combination with perovskites, ZnO has turned out to be a source of instability, rapidly degrading the performance of devices. In this work, we provide a comprehensive experimental and computational study of the interaction between the most common organic perovskite precursors and the surface of ZnO, with the aim of understanding the observed instability. Using X-ray photoelectron spectroscopy, we find a complete degradation of the precursors in contact with ZnO and the formation of volatile species as well as new surface bonds. Our computational work reveals that different pristine and defected surface terminations of ZnO facilitate the decomposition of the perovskite precursor molecules, mainly through deprotonation, making the deposition of the latter on those surfaces impossible without the use of passivation

Model for the Formation Energies of Alanates and Boranates

We develop a simple model for the formation energies (FEs) of alkali and alkaline earth alanates and boranates, based upon ionic bonding between metal cations and AlH4- or BH4- anions. The FEs agree well with values obtained from first principles calculations and with experimental FEs. The model shows that details of the crystal structure are relatively unimportant. The small size of the BH4- anion causes a strong bonding in the crystal, which makes boranates more stable than alanates. Smaller alkali or alkaline earth cations do not give an increased FE. They involve a larger ionization potential that compensates for the increased crystal bonding

ML-Aided Computational Screening of 2D Materials for Photocatalytic Water Splitting

The exploration of two-dimensional (2D) materials with exceptional physical and chemical properties is essential for the advancement of solar water splitting technologies. However, the discovery of 2D materials is currently heavily reliant on fragmented studies with limited opportunities for fine-tuning the chemical composition and electronic features of compounds. Starting from the V2DB digital library as a resource of 2D materials, we set up and execute a funnel approach that incorporates multiple screening steps to uncover potential candidates for photocatalytic water splitting. The initial screening step is based upon machine learning (ML) predicted properties, and subsequent steps involve first-principles modeling of increasing complexity, going from density functional theory (DFT) to hybrid-DFT to GW calculations. Ensuring that at each stage more complex calculations are only applied to the most promising candidates, our study introduces an effective screening methodology that may serve as a model for accelerating 2D materials discovery within a large chemical space. Our screening process yields a selection of 11 promising 2D photocatalysts