Yizhuo Xu, Nikita Rog, Catherine Mollart, Ganna Gryn’ova, Abbie Trewin, Cher Hon Lau
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引用次数: 0
Abstract
Here we present a solvent decision-making pathway for
less hazardous
and scalable synthesis of TpPa-1 covalent organic framework (COF)
underpinned by environmental compatibility (CHEM21 framework), processability
(Hansen solubility parameters), and thermodynamic suitability (free
energy of solvation). Our analyses suggest that solvents with moderate
solvation, such as 1,4-dioxane, propylene carbonate, and diacetin,
hinder excessive reaction reversibility and promote crystallite growth.
Balancing solvent greenness, compatibility, and thermodynamics, we
find that diacetin is optimal for a continuous-flow synthesis. Compared
with TpPa-1 COF synthesized in diacetin under batch conditions, the
Brunauer–Emmett–Teller surface area of flow-derived
TpPa-1 reached 418 m2 g–1, increasing
CO2 uptake by 50% at 298 K. The flow process achieved a
30-fold increase in space-time yield (STY), with excellent reproducibility
and an 89% reduction in specific energy consumption. This solvent-thermodynamics-guided
approach establishes a physically transparent and sustainable framework
for optimizing COF synthesis under continuous-flow conditions.
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)