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npj Computational Materials 2023年第1期9卷 639-648页

作者： andrij v.sylenko Dmytro Antypov vladimir v.Gusev Michael W.Gaultois Matthew S.Dyer Matthew J.Rosseinsky Department of Chemistry University of LiverpoolCrown StreetLiverpool L697ZDUnited Kingdom Department of Computer Science University of LiverpoolAshton StreetLiverpool L693BXUnited Kingdom

The unique nature of constituent chemical elements gives rise to fundamental differences in *** materials based on their phase fields,defined as sets of constituent elements,before specific differences emerge due to composition and structure can reduce combinatorial complexity and accelerate screening,exploiting the distinction from composition-level *** and evaluation of novelty of materials classes align with the experimental challenge of identifying new areas of *** address this,we present PhaseSelect,an end-to-end machine learning model that combines representation,classification,regression and novelty ranking of phase *** leverages elemental characteristics derived from computational and experimental materials data and employs attention mechanisms to reflect the individual element contributions when evaluating functional performance of phase *** demonstrate this approach for high-temperature superconductivity,high-temperature magnetism,and targeted bandgap energy applications,showcasing its versatility and potential for accelerating materials exploration.

关键词： materials phase elements

Intelligent nanogels with self-adaptive responsiveness for improved tumor drug delivery and augmented chemotherapy

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Bioactive Materials 2021年第10期6卷 3473-3484页

作者： Xin Li Helin Li Changchang Zhang andrij Pich Lingxi Xing Xiangyang Shi Department of Gynecology and Obstetrics XinHua Hospital Affiliated to Shanghai JiaoTong University School of MedicineShanghai200092China DWI-Leibniz-Institute for Interactive Materials e.v. 52056AachenGermany College of Chemistry Chemical Engineering and BiotechnologyDonghua UniversityShanghai201620China Institute for Technical and Macromolecular Chemistry RWTH Aachen University52074AachenGermany CQM-Centro de Química da Madeira Universidade da MadeiraCampus da Penteada9000-390FunchalPortugal Aachen Maastricht Institute for Biobased Materials Maastricht University6167RD GeleenNetherlands

For cancer nanomedicine,the main goal is to deliver therapeutic agents effectively to solid ***,we report the unique design of self-adaptive ultrafast charge-reversible chitosan-polypyrrole nanogels(CH-PPy NGs)for enhanced tumor delivery and augmented *** was first grafted with PPy to form CH-PPy polymers that were used to form CH-PPy NGs through glutaraldehyde cross-linking via a miniemulsion *** CH-PPy NGs could be finely treated with an alkaline solution to generate ultrafast charge-reversible CH-PPy-OH-4 NGs(R-NGs)with a negative charge at a physiological pH and a positive charge at a slightly acidic *** R-NGs display good cytocompatibility,excellent protein resistance,and high doxorubicin(DOX)loading ***,the prepared R-NGs/DOX have prolonged blood circulation time,enhanced tumor accumulation,penetration and tumor cell uptake due to their self-adaptive charge switching to be positively charged,and responsive drug delivery for augmented chemotherapy of ovarian carcinoma in ***,the tumor accumulation of R-NGs/DOX(around 4.7%)is much higher than the average tumor accumulation of other nanocarriers(less than 1%)reported *** developed self-adaptive PPy-grafted CH NGs represent one of the advanced designs of nanomedicine that could be used for augmented antitumor therapy with low side effects.

关键词： Ultrafast charge conversion Nanogels Active transportation Deep tumor penetration Enhanced antitumor activity

Dendrimer-decorated nanogels:Efficient nanocarriers for biodistribution in vivo and chemotherapy of ovarian carcinoma

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Bioactive Materials 2021年第10期6卷 3244-3253页

作者： Xin Li Zhijun Ouyang Helin Li Chaolei Hu Pabitra Saha Lingxi Xing Xiangyang Shi andrij Pich DWI-Leibniz-Institute for Interactive Materials e.v 52056AachenGermany Institute for Technical and Macromolecular Chemistry RWTH Aachen University52074AachenGermany College of Chemistry Chemical Engineering and BiotechnologyDonghua UniversityShanghai201620China CQM-Centro de Química da Madeira Universidade da MadeiraCampus da Penteada9000-390FunchalPortugal Department of Gynecology and Obstetrics XinHua HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai200092China Aachen Maastricht Institute for Biobased Materials Maastricht UniversityNL-6167 RDGeleenthe Netherlands

Nanomedicine has revolutionized disease theranostics by the accurate diagnosis and efficient ***,the PAMAM dendrimer decorated PvCL-GMA nanogels(NGs)were developed for favorable biodistribution in vivo and enhanced antitumor efficacy of ovarian *** an ingenious design,the NGs with a unique structure that GMA-rich domains were localized on the surface were synthesized via precipitation *** G2 dendrimer decoration,the overall charge is changed from neutral to positive,and the NGs-G2 display the whole charge nature of positively charged corona and neutral ***,the unique architecture and charge conversion of NGs-G2 have a profound impact on the biodistribution and drug delivery in *** a consequence of this alteration,the NGs-G2 as nanocarriers emerge the highly sought biodistribution of reduced liver accumulation,enhanced tumor uptake,and promoted drug release,resulting in the significantly augmented antitumor efficacy with low side ***,this finding is contrary to some reported work that the nanocarriers with positive charge have preferential liver ***,the NGs-G2 also displayed thermal/pH dual-responsive behaviors,excellent biocompatibility,improved cellular uptake,and stimuli-responsive drug ***,this work demonstrates a novel insight into the strategy for optimizing design,improving biodistribution and enhancing theranostic efficacy of nanocarriers.

关键词： Nanogels Dendrimer Surface charge Thermal/pH dual-responsiveness Drug delivery

A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning

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npj Computational Materials 2023年第1期9卷 2265-2278页

作者： Cameron J.Hargreaves Michael W.Gaultois Luke M.Daniels Emma J.Watts vitaliy A.Kurlin Michael Moran Yun Dang Rhun Morris Alexandra Morscher Kate Thompson Matthew A.Wright Beluvalli-Eshwarappa Prasad Frédéric Blanc Chris M.Collins Catriona A.Crawford Benjamin B.Duff Jae Evans Jacinthe Gamon Guopeng Han Bernhard T.Leube Hongjun Niu Arnaud J.Perez Aris Robinson Oliver Rogan Paul M.Sharp Elvis Shoko Manel Sonni William J.Thomas andrij v.sylenko Lu Wang Matthew J.Rosseinsky Matthew S.Dyer Department of Chemistry University of LiverpoolLiverpool L697ZDUK Leverhulme Research Centre for Functional Materials Design Materials Innovation FactoryUniversity of LiverpoolLiverpool L73NYUK Department of Computer Science University of LiverpoolLiverpool L693BXUK Stephenson Institute for Renewable Energy University of LiverpoolLiverpool L697ZFUK

The application of machine learning models to predict material properties is determined by the availability of high-quality *** present an expert-curated dataset of lithium ion conductors and associated lithium ion conductivities measured by *** *** dataset has 820 entries collected from 214 sources;entries contain a chemical composition,an expert-assigned structural label,and ionic conductivity at a specific temperature(from 5 to 873°C).There are 403 unique chemical compositions with an associated ionic conductivity near room temperature(15–35°C).The materials contained in this dataset are placed in the context of compounds reported in the Inorganic Crystal Structure Database with unsupervised machine learning and the Element Movers *** dataset is used to train a CrabNet-based classifier to estimate whether a chemical composition has high or low ionic *** classifier is a practical tool to aid experimentalists in prioritizing candidates for further investigation as lithium ion conductors.

关键词： spectroscopy lithium classifier