ACS Combinatorial Science最新文献

ACS Combinatorial Science: January, 1999–December, 2020 ACS组合科学:1999年1月- 2020年12月

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-12-14 DOI: 10.1021/acscombsci.0c00181

M. G. Finn*

引用次数: 0

Aldol Reactions of Biorenewable Triacetic Acid Lactone Precursor Evaluated Using Desorption Electrospray Ionization Mass Spectrometry High-Throughput Experimentation and Validated by Continuous Flow Synthesis 生物可再生三乙酸内酯前体醛醇反应的解吸电喷雾质谱高通量实验及连续流合成验证

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-19 DOI: 10.1021/acscombsci.0c00119

H. Samuel Ewan, Shruti A. Biyani, Jaycie DiDomenico, David Logsdon, Tiago J. P. Sobreira, Larisa Avramova, R. Graham Cooks, David H. Thompson*

{"title":"Aldol Reactions of Biorenewable Triacetic Acid Lactone Precursor Evaluated Using Desorption Electrospray Ionization Mass Spectrometry High-Throughput Experimentation and Validated by Continuous Flow Synthesis","authors":"H. Samuel Ewan, Shruti A. Biyani, Jaycie DiDomenico, David Logsdon, Tiago J. P. Sobreira, Larisa Avramova, R. Graham Cooks, David H. Thompson*","doi":"10.1021/acscombsci.0c00119","DOIUrl":"https://doi.org/10.1021/acscombsci.0c00119","url":null,"abstract":"Desorption electrospray ionization-mass spectrometry (DESI-MS) was used as a high-throughput experimentation (HTE) tool to rapidly identify derivatives of the biobased platform molecule triacetic acid lactone (TAL). TAL is a platform molecule capable of conversion to a wide range of useful commodity chemicals, agrochemicals, and advanced pharmaceutical intermediates. In the present study, a diverse family of aldol reaction mixtures were prepared in high-density microtiter plates with a liquid handling robot, then printed with a pin tool onto a PTFE surface for analysis by DESI-MS. Our DESI-MS results indicate that aldol products of TAL were obtained for each substrate tested, in good agreement with previously reported TAL reactivity. These HTE experiments also revealed solvent-dependent reactivity trends that facilitated reaction scale up. Our findings suggest that DESI-MS analysis can rapidly inform the selection of optimal reaction conditions from a wide variety of conditions for scale up using continuous synthesis conditions.","PeriodicalId":14,"journal":{"name":"ACS Combinatorial Science","volume":null,"pages":null},"PeriodicalIF":3.784,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.0c00119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"1174552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Fe3O4@[email protected]: A Magnetic Metal–Organic Framework as a Recoverable Catalyst for the Hydration of Nitriles and Reduction of Isothiocyanates, Isocyanates, and Isocyanides Fe3O4@[email protected]:一种磁性金属-有机骨架作为可回收催化剂用于硝基水化和还原异硫氰酸酯、异氰酸酯和异氰酸酯

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-13 DOI: 10.1021/acscombsci.0c00178

Arash Ghorbani-Choghamarani*, Zahra Taherinia*

引用次数: 10

Expanding the Chemical Diversity of Genetically Encoded Libraries 扩大基因编码文库的化学多样性

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-09 DOI: 10.1021/acscombsci.0c00179

Sabrina E. Iskandar, Victoria A. Haberman, Albert A. Bowers*

引用次数: 15

High Throughput Synthesis and Screening of Oxygen Reduction Catalysts in the MTiO3 (M = Ca, Sr, Ba) Perovskite Phase Diagram MTiO3 (M = Ca, Sr, Ba)钙钛矿相图中氧还原催化剂的高通量合成与筛选

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-05 DOI: 10.1021/acscombsci.0c00094

Alexandra R. Groves, Thomas E. Ashton, Jawwad A. Darr*

引用次数: 2

High-Throughput Characterization of (FexCo1–x)3O4 Thin-Film Composition Spreads (FexCo1-x)3O4薄膜组成膜的高通量表征

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-05 DOI: 10.1021/acscombsci.0c00126

Tobias H. Piotrowiak, Xiao Wang, Lars Banko, Swati Kumari, Suchismita Sarker, Apurva Mehta, Alfred Ludwig*

{"title":"High-Throughput Characterization of (FexCo1–x)3O4 Thin-Film Composition Spreads","authors":"Tobias H. Piotrowiak, Xiao Wang, Lars Banko, Swati Kumari, Suchismita Sarker, Apurva Mehta, Alfred Ludwig*","doi":"10.1021/acscombsci.0c00126","DOIUrl":"https://doi.org/10.1021/acscombsci.0c00126","url":null,"abstract":"Thin-film continuous composition spreads of Fe–Co–O were fabricated by reactive cosputtering from elemental Fe and Co targets in reactive Ar/O2 atmosphere using deposition temperatures ranging from 300 to 700 °C. Fused silica and platinized Si/SiO2 strips were used as substrates. Ti and Ta were investigated as adhesion layer for Pt and the fabrication of the Fe–Co–O films. The thin-film composition spreads were characterized by high-throughput electron-dispersive X-ray spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, atomic force microscopy, scanning electron microscopy, and optical transmission spectroscopy. The Fe-content ranged from 28 to 72 at. %. The spinel phases Fe2CoO4 and FeCo2O4 could be synthesized and stabilized at all deposition temperatures with a continuous variation in spinel composition in between. The dependence of the film surface microstructure on the deposition temperature and the composition was mapped. Moreover, the band gap values, ranging from 2.41 eV for FeCo2O4 to 2.74 eV for Fe2CoO4, show a continuous variation with the composition.","PeriodicalId":14,"journal":{"name":"ACS Combinatorial Science","volume":null,"pages":null},"PeriodicalIF":3.784,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.0c00126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"1237908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Ni-Nitrilotriacetic Acid Affinity SELEX Method for Selection of DNA Aptamers Specific to the N-Cadherin Protein Ni-Nitrilotriacetic Acid Affinity SELEX方法选择N-Cadherin蛋白特异性DNA适体

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00165

Luyan Yang, Tian Gao, Wenjing Li, Yu Luo, Salim Ullah, Xiaona Fang, Yanwei Cao*, Renjun Pei*

引用次数: 7

Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence 基于人工智能的类风湿性关节炎小分子抑制剂活性预测

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00169

Guomeng Xing, Li Liang, Chenglong Deng, Yi Hua, Xingye Chen, Yan Yang, Haichun Liu, Tao Lu, Yadong Chen*, Yanmin Zhang*

{"title":"Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence","authors":"Guomeng Xing, Li Liang, Chenglong Deng, Yi Hua, Xingye Chen, Yan Yang, Haichun Liu, Tao Lu, Yadong Chen*, Yanmin Zhang*","doi":"10.1021/acscombsci.0c00169","DOIUrl":"https://doi.org/10.1021/acscombsci.0c00169","url":null,"abstract":"Rheumatoid arthritis (RA) is a chronic autoimmune disease, which is compared to “immortal cancer” in industry. Currently, SYK, BTK, and JAK are the three major targets of protein tyrosine kinase for this disease. According to existing research, marketed and research drugs for RA are mostly based on single target, which limits their efficacy. Therefore, designing multitarget or dual-target inhibitors provide new insights for the treatment of RA regarding of the specific association between SYK, BTK, and JAK from two signal transduction pathways. In this study, machine learning (XGBoost, SVM) and deep learning (DNN) models were combined for the first time to build a powerful integrated model for SYK, BTK, and JAK. The predictive power of the integrated model was proved to be superior to that of a single classifier. In order to accurately assess the generalization ability of the integrated model, comprehensive similarity analysis was performed on the training and the test set, and the prediction accuracy of the integrated model was specifically analyzed under different similarity thresholds. External validation was conducted using single-target and dual-target inhibitors, respectively. Results showed that our model not only obtained a high recall rate (97%) in single-target prediction, but also achieved a favorable yield (54.4%) in dual-target prediction. Furthermore, by clustering dual-target inhibitors, the prediction performance of model in various classes were proved, evaluating the applicability domain of the model in the dual-target drug screening. In summary, the integrated model proposed is promising to screen dual-target inhibitors of SYK/JAK or BTK/JAK as RA drugs, which is beneficial for the clinical treatment of rheumatoid arthritis.","PeriodicalId":14,"journal":{"name":"ACS Combinatorial Science","volume":null,"pages":null},"PeriodicalIF":3.784,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.0c00169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"1234589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Exploring the First High-Entropy Thin Film Libraries: Composition Spread-Controlled Crystalline Structure 探索第一个高熵薄膜库:组成扩散控制的晶体结构

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00159

Thi Xuyen Nguyen, Yen-Hsun Su, Jason Hattrick-Simpers, Howie Joress, Takahiro Nagata, Kao-Shuo Chang, Suchismita Sarker, Apurva Mehta, Jyh-Ming Ting*

{"title":"Exploring the First High-Entropy Thin Film Libraries: Composition Spread-Controlled Crystalline Structure","authors":"Thi Xuyen Nguyen, Yen-Hsun Su, Jason Hattrick-Simpers, Howie Joress, Takahiro Nagata, Kao-Shuo Chang, Suchismita Sarker, Apurva Mehta, Jyh-Ming Ting*","doi":"10.1021/acscombsci.0c00159","DOIUrl":"https://doi.org/10.1021/acscombsci.0c00159","url":null,"abstract":"Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)Ox, all the metals have a stable divalent oxidation state and similar cationic radii. In the second type of oxides, (CrFeMnCoNi)Ox, the metals are more diverse in the atomic radius and valence state, and have good solubility in their sub-binary and ternary oxide systems. The resulting HEO thin films were characterized using several high-throughput analytical techniques. The microstructure, composition, and electrical conductivity obtained on defined grid maps were obtained for the first time across large compositional ranges. The crystalline structure of the films was observed as a function of the metallic elements in the composition spreads, that is, the Mn and Zn in (MgZnMnCoNi)Ox and Mn and Ni in (CrFeMnCoNi)Ox. The (MgZnMnCoNi)Ox sample was observed to form two-phase structures, except single spinel structure was found in (MgZnMnCoNi)Ox over a range of Mn > 12 at. % and Zn < 44 at. %, while (CrFeMnCoNi)Ox was always observed to form two-phase structures. Composition-controlled crystalline structure is not only experimentally demonstrated but also supported by density function theory calculation.","PeriodicalId":14,"journal":{"name":"ACS Combinatorial Science","volume":null,"pages":null},"PeriodicalIF":3.784,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.0c00159","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"1237214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Identifying Optimal Strain in Bismuth Telluride Thermoelectric Film by Combinatorial Gradient Thermal Annealing and Machine Learning 基于组合梯度退火和机器学习的碲化铋热电薄膜最佳应变识别

IF 3.784 3区化学

ACS Combinatorial Science Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00112

Michiko Sasaki*, Shenghong Ju, Yibin Xu, Junichiro Shiomi, Masahiro Goto

{"title":"Identifying Optimal Strain in Bismuth Telluride Thermoelectric Film by Combinatorial Gradient Thermal Annealing and Machine Learning","authors":"Michiko Sasaki*, Shenghong Ju, Yibin Xu, Junichiro Shiomi, Masahiro Goto","doi":"10.1021/acscombsci.0c00112","DOIUrl":"https://doi.org/10.1021/acscombsci.0c00112","url":null,"abstract":"The thermoelectric properties of bismuth telluride thin film (BTTF) was tuned by inducing internal strain through a combination of combinatorial gradient thermal annealing (COGTAN) and machine learning. BTTFs were synthesized via magnetron sputter coating and then treated by COGTAN. The crystal structure and thermoelectric properties, namely Seebeck coefficient and thermal conductivity, of the treated samples were analyzed via micropoint X-ray diffraction and scanning thermal probe microimaging, respectively. The obtained combinatorial data reveals the correlation between internal strain and the thermoelectric properties. The Seebeck coefficient of BTTF exhibits largest sensitivity, where the value ranges from 7.9 to ?108 μV/K. To further explore the possibility to enhance Seebeck coefficient, the combinatorial data were subjected to machine learning. The trained model predicts that optimal strains of 3–4% and 1–2% along the a- and c-axis, respectively, significantly improve Seebeck coefficient. The technique demonstrated herein can be used to predict and enhance the performance of thermoelectric materials by inducing internal strain.","PeriodicalId":14,"journal":{"name":"ACS Combinatorial Science","volume":null,"pages":null},"PeriodicalIF":3.784,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.0c00112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"1237215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6