Inorganic Halide Double Perovskites with Optoelectronic Properties Modulated by Sublattice Mixing.

All-inorganic halide double perovskites have emerged as a promising class of materials that are potentially more stable and less toxic than lead-containing hybrid organic-inorganic perovskite optoelectronic materials. In this work, 311 cesium chloride double perovskites (Cs2BB'Cl6) were selected from a set of 903 compounds as likely being stable on the basis of a statistically learned tolerance factor (τ) for perovskite stability. First-principles calculations on these 311 double perovskites were then performed to assess their stability and identify candidates with band gaps appropriate for optoelectronic applications. We predict that 261 of the 311 Cs2BB'Cl6 compounds are likely synthesizable on the basis of a thermodynamic analysis of their decomposition to competing compounds (decomposition enthalpy <0.05 eV/atom). Of these 261 likely synthesizable compounds, 47 contain no toxic elements and have direct or nearly direct (within 100 meV) band gaps between 1 and 3 eV, as computed with hybrid density functional theory (HSE06). Within this set, we identify the triple-alkali perovskites Cs2[Alk]+[TM]3+Cl6, where Alk is a group 1 alkali cation and TM is a transition-metal cation, as a class of Cs2BB'Cl6 double perovskites with remarkable optical properties, including large and tunable exciton binding energies as computed by the GW-Bethe-Salpeter equation (GW-BSE) method. We attribute the unusual electronic structure of these compounds to the mixing of the Alk-Cl and TM-Cl sublattices, leading to materials with small band gaps, large exciton binding energies, and absorption spectra that are strongly influenced by the identity of the transition metal. The role of the double-perovskite structure in enabling these unique properties is probed through an analysis of the electronic structures and chemical bonding of these compounds in comparison with other transition-metal and alkali transition-metal halides.

Highly dispersed Co deposited on Al2O3 particles via CoCp2 + H2 ALD.

Highly dispersed cobalt atoms were deposited on porous alumina particles using atomic layer deposition (ALD) with a CoCp2/H2 chemistry at approximately 7 wt%. H2 did not completely reduce the cyclopentadienyl organic ligands bound to deposited Co atoms at ALD reaction conditions. A sharp decline in Co deposited per cycle for two or more ALD cycles indicates that much of the Al2O3 surface is sterically blocked from further CoCp2 deposition after the first CoCp2 exposure. Temperature programmed reduction confirmed that the adsorbed precursor organic ligands persist after H2 exposures during ALD and temperatures as high as 500 °C are required to fully reduce the organic ligands to CH4. High resolution, element sensitive imaging showed that Co atoms were dispersed on the Al2O3 surface and could deposit in previously unobserved multiple growth morphologies, specifically layers that were continuous over several angstroms or discrete nanoparticles. Density functional theory calculations were used to examine Co atom adsorption, show the altered haptic binding of cracked Cp ligands, and to calculate the thermodynamics of Cp ligand decomposition. The lateral steric hindrance between organic ligands bound to deposited Co atoms, Cp ligand decomposition mechanism, and local Al2O3 surface termination all likely determine the observed Co growth morphology during initial ALD cycles.

Activating Nitrogen for Electrochemical Ammonia Synthesis via an Electrified Transition-Metal Dichalcogenide Catalyst.

The complex interplay between local chemistry, the solvent microenvironment, and electrified interfaces frequently present in electrocatalytic reactions has motivated the development of quantum chemical methods that can accurately model these effects. Here, we predict the thermodynamics of the nitrogen reduction reaction (NRR) at sulfur vacancies in 1T'-phase MoS2 and highlight how the realistic treatment of potential within grand canonical density functional theory (GC-DFT) seamlessly captures the multiple competing effects of applied potential on a catalyst interface interacting with solvated molecules. In the canonical approach, the computational hydrogen electrode is widely used and predicts that adsorbed N2 structure properties are potential-independent. In contrast, GC-DFT calculations show that reductive potentials activate N2 toward electroreduction by controlling its back-bonding strength and lengthening the N-N triple bond while decreasing its bond order. Similar trends are observed for another classic back-bonding ligand in CO, suggesting that this mechanism may be broadly relevant to other electrochemistries involving back-bonded adsorbates. Furthermore, reductive potentials are required to make the subsequent N2 hydrogenation steps favorable but simultaneously destabilizes the N2 adsorbed structure resulting in a trade-off between the favorability of N2 adsorption and the subsequent reaction steps. We show that GC-DFT facilitates modeling all these phenomena and that together they can have important implications in predicting electrocatalyst selectivity for the NRR and potentially other reactions.

Insights into Electrochemical CO2 Reduction on Metallic and Oxidized Tin Using Grand-Canonical DFT and In Situ ATR-SEIRA Spectroscopy.

Electrochemical CO2 reduction (CO2R) to formate is an attractive carbon emissions mitigation strategy due to the existing market and attractive price for formic acid. Tin is an effective electrocatalyst for CO2R to formate, but the underlying reaction mechanism and whether the active phase of tin is metallic or oxidized during reduction is openly debated. In this report, we used grand-canonical density functional theory and attenuated total reflection surface-enhanced infrared absorption spectroscopy to identify differences in the vibrational signatures of surface species during CO2R on fully metallic and oxidized tin surfaces. Our results show that CO2R is feasible on both metallic and oxidized tin. We propose that the key difference between each surface termination is that CO2R catalyzed by metallic tin surfaces is limited by the electrochemical activation of CO2, whereas CO2R catalyzed by oxidized tin surfaces is limited by the slow reductive desorption of formate. While the exact degree of oxidation of tin surfaces during CO2R is unlikely to be either fully metallic or fully oxidized, this study highlights the limiting behavior of these two surfaces and lays out the key features of each that our results predict will promote rapid CO2R catalysis. Additionally, we highlight the power of integrating high-fidelity quantum mechanical modeling and spectroscopic measurements to elucidate intricate electrocatalytic reaction pathways.

Computationally Predicted High-Throughput Free-Energy Phase Diagrams for the Discovery of Solid-State Hydrogen Storage Reactions.

The design of multinary solid-state material systems that undergo reversible phase changes via changes in temperature and pressure provides a potential means of safely storing hydrogen. However, fully mapping the stabilities of known or newly targeted compounds relative to competing phases at reaction conditions has previously required many stringent experiments or computationally demanding calculations of each compound's change in Gibbs energy with respect to temperature, G(T). In this work, we have extended the approach of constructing chemical potential phase diagrams based on ΔGf(T) to enable the analysis of phase stability at non-zero temperatures. We first performed density functional theory calculations to compute the formation enthalpies of binary, ternary, and quaternary compounds within several compositional spaces of current interest for solid-state hydrogen storage. Temperature effects on solid compound stability were then accounted for using our recently introduced machine learned descriptor for the temperature-dependent contribution Gδ(T) to the Gibbs energy G(T). From these Gibbs energies, we evaluated each compound's stability relative to competing compounds over a wide range of conditions and show using chemical potential and composition phase diagrams that the predicted stable phases and H2 release reactions are consistent with experimental observations. This demonstrates that our approach rapidly computes the thermochemistry of hydrogen release reactions for compounds at sufficiently high accuracy relative to experiment to provide a powerful framework for analyzing hydrogen storage materials. This framework based on G(T) enables the accelerated discovery of active materials for a variety of technologies that rely on solid-state reactions involving these materials.

A three-dimensional spheroidal cancer model based on PEG-fibrinogen hydrogel microspheres.

Three-dimensional (3D) in vitro cancer models offer an attractive approach towards the investigation of tumorigenic phenomena and other cancer studies by providing dimensional context and higher degree of physiological relevance than that offered by conventional two-dimensional (2D) models. The multicellular tumor spheroid model, formed by cell aggregation, is considered to be the "gold standard" for 3D cancer models, due to its ease and simplicity of use. Although better than 2D models, tumor spheroids are unable to replicate key features of the native tumor microenvironment, particularly due to a lack of surrounding extracellular matrix components and heterogeneity in shape, size and aggregate forming tendencies. In order to address this issue, we have developed a 3D "tumor microsphere" model, formed by a dual-photoinitiator, aqueous-oil emulsion technique, for the encapsulation of cancer cells within PEG-fibrinogen hydrogel microspheres and for subsequent long-term 3D culture. In comparison to self-aggregated tumor spheroids, the tumor microspheres displayed a higher degree of size and shape homogeneity throughout long-term culture. In sharp contrast to cells in tumor spheroids, cells within tumor microspheres demonstrated significant loss in apico-basal polarity and cellular architecture, cellular and nuclear atypia, increased disorganization, elevated nuclear cytoplasmic ratio and nuclear volume density and reduction in cell-cell junction length, all of which are hallmarks of malignant transformation and tumorigenic progression. Additionally, the tumor microsphere model was extended for the 3D encapsulation and maintenance of a wide range of other cancer cell (metastatic and non-metastatic) types. Taken together, our results reinforce the importance of incorporating a biomimetic matrix in the cellular microenvironment of 3D tumor models and the influential effects of the matrix on the tumorigenic morphology of 3D cultured cells. The tumor microsphere system established in this study has the potential to be used in future investigations of 3D cancer cell-cell and cell-ECM interactions and in drug-testing applications.

Polymeric Biomaterials for In Vitro Cancer Tissue Engineering and Drug Testing Applications.

Biomimetic polymers and materials have been widely used in tissue engineering for regeneration and replication of diverse types of both normal and diseased tissues. Cancer, being a prevalent disease throughout the world, has initiated substantial interest in the creation of tissue-engineered models for anticancer drug testing. The development of these in vitro three-dimensional (3D) culture models using novel biomaterials has facilitated the investigation of tumorigenic and associated biological phenomena with a higher degree of complexity and physiological context than that provided by established two-dimensional culture models. In this review, an overview of a wide range of natural, synthetic, and hybrid biomaterials used for 3D cancer cell culture and investigation of cancer cell behavior is presented. The role of these materials in modulating cell-matrix interactions and replicating specific tumorigenic characteristics is evaluated. In addition, recent advances in biomaterial design, synthesis, and fabrication are also assessed. Finally, the advantages of incorporating polymeric biomaterials in 3D cancer models for obtaining efficacy data in anticancer drug testing applications are highlighted.