Naturally-meaningful and efficient descriptors: machine learning of material properties based on robust one-shot ab initio descriptors

Establishing a data-driven pipeline for the discovery of novel materials requires the engineering of material features that can be feasibly calculated and can be applied to predict a material's target properties. Here we propose a new class of descriptors for describing crystal structures, which we term Robust One-Shot Ab initio (ROSA) descriptors. ROSA is computationally cheap and is shown to accurately predict a range of material properties. These simple and intuitive class of descriptors are generated from the energetics of a material at a low level of theory using an incomplete ab initio calculation. We demonstrate how the incorporation of ROSA descriptors in ML-based property prediction leads to accurate predictions over a wide range of crystals, amorphized crystals, metal-organic frameworks and molecules. We believe that the low computational cost and ease of use of these descriptors will significantly improve ML-based predictions.Comment: 13 pages, accepted in Journal of Cheminformatic

Electrically Sorted Single-Walled Carbon Nanotubes-Based Electron Transporting Layers for Perovskite Solar Cells

© 2019 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Incorporation of as prepared single-walled carbon nanotubes (SWCNTs) into the electron transporting layer (ETL) is an effective strategy to enhance the photovoltaic performance of perovskite solar cells (PSCs). However, the fundamental role of the SWCNT electrical types in the PSCs is not well understood. Herein, we prepared semiconducting (s-) and metallic (m-) SWCNT families and integrated them into TiO2 photoelectrodes of the PSCs. Based on experimental and theoretical studies, we found that the electrical type of the nanotubes plays an important role in the devices. In particular, the mixture of s-SWCNTs and m-SWCNTs (2:1 w/w)-based PSCs exhibited a remarkable efficiency of up to 19.35%, which was significantly higher than that of the best control cell (17.04%). In this class of PSCs, semiconducting properties of s-SWCNTs play a critical role in extracting and transporting electrons, whereas m-SWCNTs provide high conductance throughout the electrode

Sensing sulfur-containing gases using titanium and tin decorated zigzag graphene nanoribbons from first-principles

Atom implantation in graphene or graphene nanoribbons offers a rich opportunity to tune the material structure and functional properties. In this study, zigzag graphene nanoribbons with Ti or Sn adatoms stabilised on a double carbon vacancy site are theoretically studied to investigate their sensitivity to sulfur-containing gases (H2S and SO2). Due to the abundance of oxygen in the atmosphere, we also consider the sensitivity of the structures in the presence of oxygen. Density functional theory calculations are performed to determine the adsorption geometry and energetics, and nonequilibrium Green's function method is employed to compute the current–voltage characteristics of the considered systems. Our results demonstrate the sensitivity of both Ti- and Sn-doped systems to H2S, and the mild sensitivity of Ti-doped sensor systems to SO2. The Ti-doped sensor structure exhibits sensitivity to H2S with or without oxidation, while oxidation of the Sn-doped sensor structure reduces its ability to adsorb H2S and SO2 molecules. Interestingly, oxygen dissociates on the Ti-doped sensor structure, but it does not affect the sensor's response to the H2S gas species. Oxidation prevents the dissociation of the H–S bond when H2S adsorbs on the Ti-doped structure, thus enhancing its reusability for this gas species. Our study suggests the potential of Ti- and Sn-doped graphene in selective gas sensing, irrespective of the sensing performance of the bulk oxides

Liquid-Metal Synthesized Ultrathin SnS Layers for High-Performance Broadband Photodetectors

Atomically thin materials face an ongoing challenge of scalability, hampering practical deployment despite their fascinating properties. Tin monosulfide (SnS), a low-cost, naturally abundant layered material with a tunable bandgap, displays properties of superior carrier mobility and large absorption coefficient at atomic thicknesses, making it attractive for electronics and optoelectronics. However, the lack of successful synthesis techniques to prepare large-area and stoichiometric atomically thin SnS layers (mainly due to the strong interlayer interactions) has prevented exploration of these properties for versatile applications. Here, SnS layers are printed with thicknesses varying from a single unit cell (0.8 nm) to multiple stacked unit cells (approximate to 1.8 nm) synthesized from metallic liquid tin, with lateral dimensions on the millimeter scale. It is reveal that these large-area SnS layers exhibit a broadband spectral response ranging from deep-ultraviolet (UV) to near-infrared (NIR) wavelengths (i.e., 280-850 nm) with fast photodetection capabilities. For single-unit-cell-thick layered SnS, the photodetectors show upto three orders of magnitude higher responsivity (927 A W-1) than commercial photodetectors at a room-temperature operating wavelength of 660 nm. This study opens a new pathway to synthesize reproduceable nanosheets of large lateral sizes for broadband, high-performance photodetectors. It also provides important technological implications for scalable applications in integrated optoelectronic circuits, sensing, and biomedical imaging

Are Dispersion Corrections Accurate Outside Equilibrium? A Case Study on Benzene

Modern approaches to modelling dispersion forces are becoming increasingly accurate, and can predict accurate binding distances and energies. However, it is possible that these successes reflect a fortuitous cancellation of errors at equilibrium. Thus, in this work we investigate whether a selection of modern dispersion methods agree with benchmark calculations across several potential-energy curves of the benzene dimer to determine if they are capable of describing forces and energies outside equilibrium. We find the exchange-hold dipole moment (XDM) model describes most cases with the highest overall agreement with reference data for energies and forces, with many-body dispersion (MBD) and its fractionally ionic (FI) variant performing essentially as well. Popular approaches, such as Grimme-D and van der Waals density functional approximations (vdW-DFAs) underperform on our tests. The meta-GGA M06-L is surprisingly good for a method without explicit dispersion corrections. Some problems with SCAN+rVV10 are uncovered and briefly discussed.<br /

Improved Lithium Diffusion in Anion-Substituted Li₇TaO₆

One approach to enhance the conductivity of a lithium-containing material is to widen the diffusion channel, such as the case of the superionic material Li10GeP2S6. This work unravels the enhanced diffusivity of Li+ in Li7TaS6 and Li7TaSe6, which are based on the known Li7TaO6 superionic conductor. Using density functional theory, we calculate the electronic and structural properties of the three materials and utilize ab initio molecular dynamics simulations to model the diffusion dynamics. Both Li7TaS6 and Li7TaSe6 are shown to exhibit an order of magnitude improvement in the diffusion coefficient relative to the parent material and a slight drop in their corresponding activation barriers. These materials are potential candidates for application in lithium solid-state electrolytes, with performance that is competitive with Li10GeP2S6

Blocking Directional Lithium Diffusion in Solid-State Electrolytes at the Interface: First-Principles Insights into the Impact of the Space Charge Layer

Understanding the degradation mechanisms in solid-state lithium-ion batteries at interfaces is fundamental for improving battery performance and for designing recycling methodologies for batteries. A key source of battery degradation is the presence of the space charge layer at the solid-state electrolyte–electrode interface and the impact that this layer has on the thermodynamics of the electrolyte structure. Currently, Li10GeP2S12 in its pristine form has one of the highest lithium conductivities and has been used as a template for designing even higher conductivity derived structures. However, being an ionic material with mostly linear diffusion, it is prone to path-blocker defects, which we show here to be especially prevalent in the space charge layer. We analyze the thermodynamic properties of a number of path-blocker defects using density functional theory and their potential crystal decomposition and find that the presence of an electrostatic potential in the space charge layer elevates the likelihood of existence of these defects, which otherwise would not be likely to form in the bulk of the electrolyte away from electrodes. We use ab initio molecular dynamics to assess the impact of these defects on the diffusivity of the crystal and find that they all reduce the lithium diffusivity. While our work focuses on Li10GeP2S12, it is relevant to any solid-state electrolyte with mainly linear diffusion