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Department of Chemistry and Biochemistry, Queens College, Flushing, New York 11367, United States.
Semiconductor nanomaterials and nanostructured interfaces have important technological applications, ranging from fuel production to electrosynthesis. Their photocatalytic activity is known to be highly heterogeneous, both in an ensemble of nanomaterials and within a single entity. Photoelectrochemical imaging techniques are potentially useful for high-resolution mapping of photo(electro)catalytic active sites; however, the nanoscale spatial resolution required for such experiments has not yet been attained.
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr 45470, Germany.
X-ray spectroscopies are uniquely poised to describe the geometric and electronic structure of metalloenzyme active sites under a wide variety of sample conditions. UV/Vis (ultraviolet/visible) spectroscopy is a similarly well-established technique that can identify and quantify catalytic intermediates. The work described here reports the first simultaneous collection of full in situ UV/Vis and high-energy resolution fluorescence detected x-ray absorption spectra.
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View Article and Find Full Text PDFLiAlClS: a low-cost and high-performance solid electrolyte for solid-state batteries.
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Materials Science and Engineering Program, The Graduate School, Florida State University 2005 Levy Ave. Tallahassee FL 32310 USA
Solid electrolytes (SEs) are crucial for advancing next-generation rechargeable battery technologies, but their commercial viability is partially limited by expensive precursors, unscalable synthesis, or low ionic conductivity. Lithium tetrahaloaluminates offer an economical option but exhibit low Li conductivities with high activation energy barriers. This study reports the synthesis of lithium aluminum chalcohalide (LiAlClS) using inexpensive precursors one-step mechanochemical milling.
View Article and Find Full Text PDFExploratory multivariate analysis using R Language for method development in liquid chromatography.
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Department of Medical Biochemistry, Faculty of Medicine in Hradec Králové, Charles University, Šimkova 870, 500 03, Hradec Králové, Czech Republic.
The visual evaluation of data derived from screening and optimization experiments in the development of new analytical methods poses a considerable time investment and introduces the risk of subjectivity. This study presents a novel approach to processing such data, based on factor analysis of mixed data and hierarchical clustering - multivariate techniques implemented in the R programming language. The methodology is demonstrated in the early-stage screening and optimization of the chromatographic separation of 15 structurally diverse drugs that affect the central nervous system, using a custom R Language script.
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