本期推送精选了Green Chemical Engineering（GreenChE）近期最新上线文章5篇，包括1篇Review，4篇 Article，内容涵盖低共熔溶剂、机器学习、电催化以及生物化工等领域。欢迎您持续关注GreenChE期刊，精彩文章抢先看！

01 Review 

Deep eutectic solvents for fractionation and valorization of lignocellulose

Yansai Bao, Yang Wang, Chuanyu Yan*, Zhimin Xue*

❖The effect of the properties of DESs was discussed.

❖The efficiency of fractionation of lignocellulose was discussed.

❖Exploring solvent selection and enhancing bioproduct diversification is vital.

❖The recyclability of DESs is worth systematically investigating.

❖The application of DESs in biomass holds great potential for a sustainable future.

https://doi.org/10.1016/j.gce.2024.04.001

02 Article

Deep eutectic solvent-induced controllable synthesis of bifunctional Ni–Fe–P catalysts for electrochemical water splitting

Ruichang Xue¹, Rongrong Deng¹, Yan Li*, Mengqiu Gao, Jiafu Wang, Qibo Zhang*

❖A bifunctional Ni–Fe–P catalyst is fabricated with a simple one-step solvothermal process in Ethaline-DES.

❖The in-situ grown Ni–Fe–P/FF exhibits excellent catalytic performance for overall water splitting.

❖The regulating effect of Fe(III) ions in the solvothermal synthesis process is discussed.

❖It offers a facile and scalable approach for preparing high-performance Ni–Fe–P based water-splitting electrocatalyst.

https://doi.org/10.1016/j.gce.2024.04.002

03 Article

Tailored SrFeO_3-δ for chemical looping dry reforming of methane

Ao Zhu, Dongfang Li, Tao Zhu, Xing Zhu*

❖Sr_0.98Fe_0.7Co_0.3O_3-δ exhibits high redox activity.

❖SrFeO_3-δ is tailored via A-site defects engineering and B-site doping.

❖Structure-oxygen storage relationship of the perovskite is explored.

https://doi.org/10.1016/j.gce.2024.04.003

04 Article 

Machine learning-assisted prediction and optimization of solid oxide electrolysis cell for green hydrogen production

Qingchun Yang*, Lei Zhao, Jingxuan Xiao, Rongdong Wen, Fu Zhang, Dawei Zhang*

❖Four machine learning models are developed to predict the Ohmic resistance, current density, and H₂ production rate of the SOEC process.

❖An interpretable analysis based on the SHAP method is performed to explain the predictive performance of the preferred XGBoost model.

❖Interaction relationship between the input parameters and various output indicators is investigated by the PDP analysis.

❖XGBoost model is coupled with the GA algorithm to achieve the maximum H₂ production rate with the lowest current in the SOEC process.

https://doi.org/10.1016/j.gce.2024.04.004

05 Article 

A size shrinkable dendrimer-lipid hybrid nanoassembly for reversing tumor drug resistance

Xuanrong Sun*¹, Tenghan Zhang¹, Zhao Lou, Yujie Zhou, Yuteng Chu, Dongfang Zhou, Juhong Zhu, Yue Cai, Jie Shen*

❖An investigation of the relationship between nanomaterials size regulation and tumor lesion uptake.

❖Size-shrinkable dendrimer-liposomes for reversal of tumor drug resistance.

https://doi.org/10.1016/j.gce.2024.05.001