Abstract Biomass supply chain performance is heavily affected by uncertainties stemming from supply, demand, or unexpected disruptions. Unlike petrochemical plants that use crude oil, biorefineries often have to deal with the uneven spatial-temporal distribution of feedstock supply. The modular production strategy provides more flexibility in chemical manufacturing by allowing fast capacity expansion and unit movement. However, modeling and optimizing modular biomass supply chain under uncertainties becomes challenging due to high dimensionality and the existence of discrete decisions. This wo ..read more

Abstract Atomically dispersed dual-metal sites catalysts, also named as dual-atom catalysts, have become a frontier, since they combine the merits of homogeneous and heterogeneous catalysts to satisfy the demands for critical catalytic reactions in green energy industrial equipment. However, the absence of further understanding for the evolution of catalyst structures in reaction environments results in a significant gap between the theoretical and experimental. Here, we provide a model to understand the evolution of the active configuration in acidic oxygen reduction and evolution reactions a ..read more

Abstract Carbon dioxide (CO2) electrolysis is an important process for storing excess renewable electricity. However, this process is commonly carried out in a high-purity-CO2 environment. Here, we conduct a systematic investigation into the operational performance of CO2 capture solutions for producing syngas. Using Ni-N-C electrocatalysts, by reducing the thickness of the catalytic layer and accelerating the mass transport, we achieve 58.6% CO Faradaic efficiency at a current density of 100 mA cm−2 and a full cell voltage of 3.67 V. Efficient syngas (MolH2/MolCO = 1–4) production has achieve ..read more

Abstract Intracellular biosynthesis of massive quantum dots inside bacteria remains a grand challenge, with such a technology unsatisfactory due to the high toxicity of metal ions to the cell and the ultralow yield of quantum dots. Herein, a gshA-overexpressed Shewanella oneidensis MR-1 strain was constructed with the ability to effectively detoxify SeO32− species, rendering the formation of substantial CdSe quantum dots across the entire cell entity. As such, the photoexcited electrons generated from the entire bacterium entity led to promoted electron mobilization efficiency and photoelectro ..read more

Abstract This study proposed an auto-configurable machine learning framework based on the differential evolution algorithm (AutoML-DE) driven by hybrid data for the screening and discovery of promising CO2 to light olefins (CO2TLO) catalysts candidates. The hybrid dataset comprises 532 experimental data from the literature and 296 simulation data. Results show that the AutoML-DE model with extreme gradient boosting algorithms demonstrated superior performance for predicting the conversion ratio of CO2 and selectivity of light olefins (average R 2 > 0.86). After identifying the input feature ..read more

Abstract A process of simultaneous desulfurization and dehydration of flue gas with ionic liquid was explored. The selection of ionic liquid was completed based on COSMO-SAC model. Random forest (RF) and one-dimensional convolutional neural network were trained for the prediction of CO2 and SO2 solubility. A feature selection method is designed to remove verbose descriptors. The feature importance was analyzed by SHAP analysis. Quantum chemistry calculation and molecular dynamics (MD) simulation were used to investigate the type and position of intermolecular forces. The results show that the ..read more

AIChE Journal, Volume 70, Issue 5, May 2024 ..read more

Abstract In this work, a particle-resolved computational fluid dynamics model of the acetylene hydrogenation process is developed to investigate the effects of catalyst particle structures on the reaction–diffusion behaviors aiming to improve selectivity toward target ethylene. The effects of packing structures on mass and heat transfer are explored by employing particles with varying shapes, wall thicknesses, and external diameters. The simulation results reveal that decreasing diffusion paths and elevating reactor bed temperature will enhance ethylene selectivity, and cylinder and Raschig ri ..read more

Abstract Metal–organic framework (MOF) membranes are widely used in gas separation processes. However, the effect of solvents on the formation of large-area MOF membranes, which directly influences separation performance, has rarely been investigated. In this study, three solvents (methanol, ethanol, and water) were selected to systematically investigate their effects on the zeolite imidazolium frameworks (ZIF) membrane formation via experimental validation and simulations. The results indicated that the solvent selection influenced crystallization rate, crystal size, and ZIF-8 membrane format ..read more

Abstract This work presents an image-based hybrid model incorporating the initial spatial distribution for mesenchymal stem cell (MSC) cultivation process design. First, three levels of seeding bias in static MSC cultivation were experimentally investigated, and the resulting initial distribution was quantified using phase contrast microscopy image analysis. Second, the observed spatial heterogeneity was defined as a new parameter by calculating the standard deviation of the seeded cell number fraction among numerical 8 × 8 tiles on two-dimensional plates. Third, the parameter was incorporated ..read more