Lone Pair Induced 1D Character and Weak Cation-Anion Interactions: Two Ingredients for Low Thermal Conductivity in Mixed-Anion Metal Chalcohalide CuBiSCl.

Mixed-anion compounds, which incorporate multiple types of anions into materials, display tailored crystal structures and physical/chemical properties, garnering immense interest in various applications such as batteries, catalysis, photovoltaics, and thermoelectrics. However, detailed studies regarding correlations among crystal structure, chemical bonding, and thermal/vibrational properties are rare for these compounds, which limits the exploration of mixed-anion compounds for associated thermal applications. In this work, we investigate the lattice dynamics and thermal transport properties of the metal chalcohalide, CuBiSCl.

Is the Presence of Sn a Crucial Factor for the Generation of Low Thermal Conductivity in Tin-Based Sulfides?

Comprehending the relationship between crystal structures and transport properties is crucial to develop materials with improved electrical and thermal properties for thermoelectric applications. In this article, we report on the complex crystal structure and physical properties of CrSnS, a -type magnetic semiconductor with a low energy band gap and low thermal conductivity. Importantly, we demonstrate that the high level of structural complexity is related to the coexistence of two sublattices: a host lattice, [CrSnS], characterized by a mixed Sn/Cr occupancy of its cationic sites, and a guest lattice characterized by [SnS] chains, containing Sn cations only, closely related to the ones encountered in the orthorhombic SnS compound.

Who shops at their nearest grocery store? A cross-sectional exploration of disparities in geographic food access among a low-income, racially/ethnically diverse cohort in Central Texas.

We examined whether Central Texans shop at their nearest supermarket, how far they travel for groceries, and explored differences by race/ethnicity, urbanicity, motivations for store selection and other demographic characteristics. Using cross-sectional data and GIS, continuous network distances from participants' homes to nearest and usual supermarkets were calculated and multivariate linear regression assessed differences. <19% shopped at their nearest supermarket.