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Understanding mechanisms of decontamination of chemical warfare agents (CWA) is an area of intense research aimed at developing new filtration materials to protect soldiers and civilians in case of state-sponsored or terrorist attack. In this study, we employed complementary structural, chemical, and dynamic probes and data collection, to elucidate the complex chemistry, capture, and decomposition of the CWA simulant, dimethyl chlorophosphonate (DMCP). Our work reveals key details of the reactive adsorption of DMCP and demonstrates the versatility of zeolitic imidazolate framework (ZIF-8) as a plausible material for CWA capture and decomposition. The synchrotron-based powder X-ray diffraction (PXRD) and pair distribution function (PDF) studies, combined with Fourier transform infrared (FT-IR) spectroscopy, X-ray photoelectron spectroscopy (XPS), zinc K-edge X-ray absorption near edge structure (XANES), and Raman spectroscopies, showed that the unique structure, chemical state, and topology of ZIF-8 enable accessibility, adsorption, and hydrolysis of DMCP into the pores and revealed the importance of linker chemistry and Zn sites for nerve agent decomposition. DMCP decontamination and decomposition product(s) formation were observed by thermogravimetric analysis, FT-IR spectroscopy, and phosphorus (P) K-edge XANES studies. Differential PDF analysis indicated that the average structure of ZIF-8 (at the 30 Å scale) remains unchanged after DMCP dosing and provided information on the dynamics of interactions of DMCP with the ZIF-8 framework. Using PXRD and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), we showed that nearly 90% regeneration of the ZIF-8 structure and complete liberation of DMCP and decomposition products occur upon heating.
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http://dx.doi.org/10.1021/acsami.0c12985 | DOI Listing |
Particle-based reaction-diffusion models offer a high-resolution alternative to the continuum reaction-diffusion approach, capturing the discrete and volume-excluding nature of molecules undergoing stochastic dynamics. These methods are thus uniquely capable of simulating explicit self-assembly of particles into higher-order structures like filaments, spherical cages, or heterogeneous macromolecular complexes, which are ubiquitous across living systems and in materials design. The disadvantage of these high-resolution methods is their increased computational cost.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
Department of Sustainable Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu, India. Electronic address:
This study explores the integration of ammonium hydroxide with diesel fuel, focusing on enhancing combustion efficiency and reducing emissions. The research addresses the challenge of ammonia's high activation energy during decomposition by introducing a carbon nanotube catalyst, which significantly improves catalytic performance. Additionally, an electrostatic precipitator (ESP) was developed to capture nanoparticles from engine exhaust, preventing their release into the atmosphere.
View Article and Find Full Text PDFGenome Biol
December 2024
Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, USA.
Longitudinal studies are crucial for understanding complex microbiome dynamics and their link to health. We introduce TEMPoral TEnsor Decomposition (TEMPTED), a time-informed dimensionality reduction method for high-dimensional longitudinal data that treats time as a continuous variable, effectively characterizing temporal information and handling varying temporal sampling. TEMPTED captures key microbial dynamics, facilitates beta-diversity analysis, and enhances reproducibility by transferring learned representations to new data.
View Article and Find Full Text PDFBMC Bioinformatics
December 2024
Center of Intelligent Medicine, School of Control Science and Engineering, Shandong University, Jinan, 250061, Shandong, China.
Recent developments in spatially resolved transcriptomics (SRT) enable the characterization of spatial structures for different tissues. Many decomposition methods have been proposed to depict the cellular distribution within tissues. However, existing computational methods struggle to balance spatial continuity in cell distribution with the preservation of cell-specific characteristics.
View Article and Find Full Text PDFBMC Bioinformatics
December 2024
School of Software, Henan University of Engineering, Zhengzhou, Henan, China.
Background: Using information measures to infer biological regulatory networks can capture nonlinear relationships between variables. However, it is computationally challenging, and there is a lack of convenient tools.
Results: We introduce Informeasure, an R package designed to quantify nonlinear dependencies in biological regulatory networks from an information theory perspective.
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