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Although cyclic voltammetry (CV) measurements in solution have been widely used to determine the highest occupied molecular orbital energy (E_HOMO) of semiconducting organic molecules, an understanding of the experimentally observed discrepancies due to the solvent used is lacking. To explain these differences, we investigate the solvent effects onE_HOMOby combining density functional theory and molecular dynamics calculations for four donor molecules with a common backbone moiety. We compare the experimentalE_HOMOvalues to the calculated values obtained from either implicit or first solvation shell theories. We find that the first solvation shell method can capture theE_HOMOvariation arising from the functional groups in solution, unlike the implicit method. We further applied the first solvation shell method to other semiconducting organic molecules measured in solutions for different solvents. We find that theE_HOMOobtained using an implicit method is insensitive to solvent choice. The first solvation shell, however, producesE_HOMOvalues that are sensitive to solvent choices and agrees with published experimental results. The solvent sensitivity arises from a hierarchy of three effects: (1) the solute electronic state within a surrounding dielectric continuum, (2) ambient temperature or solvent atoms changing the solute geometry, and (3) electronic interactions between the solute and solvents. The implicit method, on the other hand, only captures the effect of a dielectric environment. Our findings suggest thatE_HOMOobtained by CV measurements should account for the influence of solvent when the results are reported, interpreted, or compared to other molecules.

 

Abstract The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov . 

Control of surface functionalization of MXenes holds great potential, and in particular, may lead to tuning of magnetic and electronic order in the recently reported magnetic Cr₂TiC₂T_x. Here, vacuum annealing experiments of Cr₂TiC₂T_xare reported with in situ electron energy loss spectroscopy and novel in situ Cr K‐edge extended energy loss fine structure analysis, which directly tracks the evolution of the MXene surface coordination environment. These in situ probes are accompanied by benchmarking synchrotron X‐ray absorption fine structure measurements and density functional theory calculations. With the etching method used here, the MXene has an initial termination chemistry of Cr₂TiC₂O_1.3F_0.8. Annealing to 600 °C results in the complete loss of F, but O termination is thermally stable up to (at least) 700 °C. These findings demonstrate thermal control of F termination in Cr₂TiC₂T_xand offer a first step toward termination engineering this MXene for magnetic applications. Moreover, this work demonstrates high energy electron spectroscopy as a powerful approach for surface characterization in 2D materials.