Reaction Chemistry & Engineering最新文献

Biological products and specimens often require consistent ultracold storage to preserve their integrity. Existing time–temperature indicators (TTIs) are inadequate for monitoring ultracold conditions at the individual aliquot level. We adapted the autocatalytic permanganate–oxalate reaction to create visual TTIs functional below 0 °C. Using eutectic compositions of LiClO₄, NaClO₄, and Mg(ClO₄)₂, we depressed the melting points of the reaction mixtures to −18 °C, −37 °C, and −67 °C, respectively. The incorporation of perchlorate salts as antifreeze systems did not derail the kinetic behavior of the permanganate–oxalate reaction and allowed the reactions to pause below their melting points. Here, we developed and characterized eight customized TTIs, running from five minutes at 25 °C to 7 days at −20 °C. Temperature sensitivity was consistent with Arrhenius behavior (i.e., exponential increases in run time with linear decreases in temperature). The TTIs exhibited good accuracy and reproducibility, with within-batch and between-batch run-time precision at the targeted temperatures of ≤4.8% CV and ≤7.5% CV, respectively. The average absorbance vs. time trajectories, expressed as RMSD %CVs, were 4.5% for intra-batch and 10.4% for inter-batch runs. Indicators withstood multiple freeze/thaw cycles or extended pre-freezing periods with minimal impact on reaction kinetics. Once activated and stored below their melting points, TTIs maintained color intensity for at least 12 months. This work establishes the permanganate–oxalate system in eutectic perchlorate-based antifreeze solutions as a simple, inexpensive approach for ultracold-active TTIs, offering customizable kinetics and robust performance. The described TTIs can serve to improve quality monitoring of biologicals and biospecimens during ultracold storage and handling.

Research has demonstrated that heterometallic–organic frameworks (HMOFs) and their derivatives showcase exceptional application potential across various domains, including gas adsorption, energy storage, and environmental purification, often outperforming their monometallic MOF counterparts. The GSF synthesis protocol detailed in this paper introduces a pioneering mechanochemical approach for the production of manganese-based HMOFs. This technique facilitates the continuous fabrication of HMOFs in the absence of solvents, thereby cutting down on the production costs of MOFs and mitigating the issue of organic solvent pollution. This study provides experimental evidence and theoretical support for the standardization and large-scale application of the GSF method, while also holding significant scientific and practical value for advancing the innovative development of green chemical synthesis technologies.

The hydrodeoxygenation (HDO) of guaiacol, a model compound for lignin-derived pyrolysis oils, was investigated using Ru and Ni catalysts supported on activated carbons derived from both commercial and renewable (food waste) sources. Comprehensive characterization of support properties including porosity, surface area, hydrophobicity, and morphology revealed their significant influence on catalyst performance. Liquid-phase HDO reactions were conducted in both aqueous and organic (decane) environments to evaluate solvent effects on reaction pathways and product distributions. Ru-based catalysts demonstrated superior activity compared to Ni-based catalysts, while supports with higher mesoporosity facilitated better metal dispersion and enhanced catalytic performance. Notably, food waste-derived activated carbon supports performed comparably or better than commercial activated carbon when combined with Ru, indicating their potential as sustainable catalyst supports. Mathematical optimization techniques were employed to estimate kinetic parameters and elucidate reaction pathways, revealing notable differences between aqueous and organic media. Specifically, methoxycyclohexanone dominated in organic medium, while cyclohexanol prevailed in aqueous medium. The optimization study identified that cyclohexanol was not an intermediate for cyclohexane production, contrary to conventional understanding. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis provided insights into adsorption phenomena, explaining carbon balance discrepancies observed particularly in aqueous-phase reactions. This integrated experimental and computational approach advances the understanding of guaiacol HDO reaction mechanisms and provides guidance for the rational design of efficient catalysts for bio-oil upgrading.

Selenium-based catalysts have emerged as promising tools for industrial application due to their environmentally-friendly features. In the past decade, people have reported a wide variety of selenium-based catalysts, such as organoselenium catalysts, polymer-supported selenium catalysts, carbon-supported selenium catalysts, and metal or non-metal oxide-supported selenium catalysts. These catalysts have been extensively applied in numerous reactions of practical importance. Notably, metal or non-metal oxide-supported inorganic selenium catalysts hold great promise for industrial use owing to the low cost and durability of their supports. This paper aims to comprehensively review the current progress and give a perspective.

Herein, we have presented the synthesis of a Cu(II) Schiff base metal complex immobilized on a silica-coated NiFe₂O₄ magnetic nanoparticle (MNP) surface, forming a novel heterogeneous and magnetically retrievable nanocatalyst, NiFe₂O₄@SiO₂@CuSB. Comprehensive characterization through FT-IR, PXRD, SEM, EDS, TEM, SAED, VSM, BET, and XPS confirms the catalyst's structure, surface morphology, elemental composition, and properties. Using a one-pot multicomponent synthesis of naphthopyran derivatives, the catalytic performance of NiFe₂O₄@SiO₂@CuSB was evaluated. This efficient, eco-friendly protocol enables the synthesis of naphthopyran derivatives using a diverse range of aldehydes, malononitrile, and 2-naphthol, exhibiting excellent functional group tolerance. The desired products have been synthesized in high yields without any byproducts. The heterogeneity of the solid nanocatalyst was assessed using a hot filtration test. This innovative catalyst offers a practical way to efficiently produce bioactive compounds, which have applications in medical chemistry.

This work presents a comprehensive study on the catalytic and kinetic aspects of the ketonisation of acetic acid, a model volatile fatty acid, using Ce_1−xZr_xO₂ as catalysts. Volatile fatty acids are promising biomass derived feedstock for production of drop-in sustainable aviation fuels through a series of cascade reactions, with ketonisation as the first step followed by aldol condensation and subsequent hydrogenation. A series of Ce_1−xZr_xO₂ catalysts for ketonisation were prepared using a mechanochemical technique of ball milling, and their performance was evaluated for varying Ce/Zr mole ratios. Among the catalysts tested, Ce_0.75Zr_0.25O₂ exhibited the highest conversion and selectivity towards the desired product, acetone. The catalyst characterisation showed the formation of nano-aggregates with an average particle size of 340.8 nm and a specific surface area of 66.2 m² g⁻¹. The kinetics of the reaction indicated a second-order dependence on acetic acid, while the products (acetone, water, and CO₂) exhibited negative orders, suggesting competitive adsorption on the active sites of the catalyst. The activation energy for the reaction was determined to be 103.4 kJ mol⁻¹ suggesting the surface reaction as the rate controlling step. These findings provide valuable insights into the catalytic behaviour and kinetics of the ketonisation reaction.

The photovoltaic (PV)-driven electrolysis of polyethylene terephthalate (PET) plastic waste represents a sustainable pathway for resource recovery. Current research predominantly focuses on simulated electrolysis systems or integrated energy storage configurations, while practical implementation under real solar irradiation conditions remains insufficiently investigated. Herein, we report a direct PV-driven electrocatalytic strategy, capable of continuously and simultaneously upcycling PET using a NiOOH electrocatalyst. Remarkably, the catalyst exhibits stable operation for over 500 hours at 300 mA cm⁻² in the laboratory, and it retains a Faradaic efficiency above 86% within 36 hours under real solar light PV-driven conditions. Through catalyst characterization, we reveal that current fluctuations inherent to solar intermittency induce structural degradation of active catalytic species, highlighting the critical need for enhanced stability optimization. This study provides a pioneering proof-of-concept direct PV-driven electrocatalytic strategy and presents a chemical engineering guideline for scaling PV-powered plastic upcycling technologies.

The thermal transformations of various thienyl and phenyl derivatives of o-divinylbenzene in acidic media were investigated in an integrated experimental–theoretical study. Several derivatives (9–12) led to cyclization products when heated under acidic conditions, while some (13 and 14) were found to be non-reactive. The reactivity or non-reactivity of the investigated compounds is closely related to the position of the preferred protonation site in the investigated compounds, as shown by DFT calculations. If the preferred position of proton entry into the molecule coincides with the protonation position required for cyclization, the reaction proceeds, otherwise the derivatives are non-reactive. By blocking a preferred protonation position with a suitable substituent in the non-reactive precursors, protonation can be prevented at the undesired site and proton entry can be redirected to the site that allows the reaction to proceed. A detailed insight into the mechanism of the thermal reactions of 9–12 was presented.

The unbridled exploitation of fossil resources for obtaining energy, chemical inputs, materials and fuels has generated growing environmental concerns, driving the search for more sustainable alternatives. In this context, the use of lignocellulosic biomasses for the production of biorenewable platform molecules, such as furfural (FF) and 5-hydroxymethylfurfural (HMF), has been widely studied. Among the strategies investigated, the use of niobium-based catalysts stands out due to their high catalytic efficiency, versatility, high acidity and stability. Therefore, this work investigated the valorization of corncob biomass through the synthesis of FF and HMF, using for the first time niobium pentachloride as a catalyst in a biphasic system (ethyl acetate and saturated aqueous NaCl solution). Different reaction parameters were investigated and it was found that the best conditions for the conversion of corncob biomass into furans were 12.5% wt niobium pentachloride, 200 °C and 180 min. Under these conditions, FF and HMF were both obtained with yields of 26%, in addition to obtaining levulinic acid (LA) with a yield of 3%. Furthermore, under these conditions, the formation of three more products was also observed: 5-ethoxymethylfurfural (EMF), 5-acetoxymethylfurfural (AMF) and ethyl levulinate (LE), with yields of 12%, 4% and 2%, respectively. In addition, cellulose, inulin and bamboo biomass were also evaluated as substrate.

In the last few decades, several novel algorithms have been designed for finding critical points on a potential energy surface (PES) and the minimum energy paths connecting them. This has led to a considerable improvement in our understanding of reaction mechanisms and the kinetics of the underlying processes. These methods implicitly rely on computation of energy and forces on the PES, which are usually obtained via computationally demanding wave-function- or density-function-based ab initio methods. To mitigate the computational cost, efficient optimization algorithms are needed. Herein, we present two new first-order optimization algorithms: the adaptively accelerated relaxation engine (AARE), an enhanced molecular dynamics (MD) scheme, and the accelerated conjugate-gradient (Acc-CG) method, an improved version of the traditional conjugate gradient (CG) algorithm. We show the efficacy of these algorithms for unconstrained optimization on 2-dimensional and 4-dimensional test functions. Additionally, we also show the efficacy of these algorithms for optimizing an elastic band of images to the minimum energy path on 2-dimensional analytical potentials, heptamer island transitions, the HCN/CNH isomerization reaction, and the keto–enol tautomerization reaction.