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Dinitrogen trioxide (N2O3) is a potent nitrosating agent featured with high reactivity and appealing atom economy. Because of its instability and the entanglement of chemical and phase equilibria, N2O3 has rarely been utilized in organic synthesis as a stock reagent with well-defined composition. In this review, the preparations of pure N2O3 and its concentrated solution (>0.1 M) are discussed from the aspect of phase equilibrium. Understanding the physical and chemical characteristics of N2O3, along with how reaction parameters (temperature, pressure, molar ratio) interact, plays a crucial role in managing the concentration of N2O3 in the liquid phase. This control holds practical significance in achieving quantitative reactions. [ABSTRACT FROM AUTHOR]

This communication introduces a highly efficient, safe and sustainable flow protocol for the oxidative neutralization of sulfur-based chemical warfare agent simulants using ozone. The methodology employs preliminary in silico mechanistic studies and chemical analogy studies with DFT to scout reaction profiles and kinetics. It unveils crucial parameters that guide selectivity and prevent the formation of undesirable overoxidized by-products. This computational foundation is seamlessly translated into real-world neutralization experiments conducted under flow conditions, yielding remarkably swift neutralization rates under mild conditions. Full oxidative neutralization of CWA simulants with ozone is achieved within a second, without the need for additives or catalysts, in an EtOH/water mixture. This convergence of computational insights and experimental validation provides a promising avenue toward new neutralization protocols, foreseeing transformative possibilities with low waste generation and high safety. [ABSTRACT FROM AUTHOR]

The use of micro/meso‐fluidic reactors has resulted in both new scenarios for chemistry and new requirements for chemists. Through flow chemistry, large‐scale reactions can be performed in drastically reduced reactor sizes and reaction times. This obvious advantage comes with the concomitant challenge of re‐designing long‐established batch processes to fit these new conditions. The reliance on experimental trial‐and‐error to perform this translation frequently makes flow chemistry unaffordable, thwarting initial aspirations to revolutionize chemistry. By combining computational chemistry and machine learning, we have developed a model that provides predictive power tailored specifically to flow reactions. We show its applications to translate batch to flow, to provide mechanistic insight, to contribute reagent descriptors, and to synthesize a library of novel compounds in excellent yields after executing a single set of conditions. [ABSTRACT FROM AUTHOR]

Multidisciplinary lab experiments combining microfluidics, nanoparticle synthesis, and characterization are presented. These experiments rely on the implementation of affordable yet efficient microfluidic setups based on perfluoroalkoxyalkane (PFA) capillary coils and standard HPLC connectors in upper undergraduate chemistry laboratories. Fundamental principles and concepts as well as practical tips for the rapid deployment of microfluidics are presented. In-line membrane separation, the segmented-flow regime, high-temperature experiments, and in-line analytical techniques are illustrated by the preparation of inorganic nanoparticles (silver, gold, and cadmium selenide or telluride) in microreactors. Besides microfluidics, analytical techniques for nanoparticle analysis are also illustrated.