POLYMERS Vol.71 No.12
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COVER STORY
Maybe We Should Have Asked Earlier, But We Can Still Learn Statistics for Polymer Science
Machine learning has been tried in various field due to the rapid progress of artificial intelligence (AI). Simulation and deep learning, which allows you to easily analyze, evaluate, and predict large amounts of data, can be seen here and there. It can’t be ignored in the field of polymer science. Before relying on deep learning, which tends to obscure causality due to black boxes, it is necessary to understand the basic and easy-to-understand statistics that have been useful for polymer science. In the first place, polymers have a molecular weight distribution and have a wide range of characteristics. For composite materials, it is necessary to consider dispersion and interface. How can statistics be applied to such polymers? This special issue presents statistics for polymers from basic to practical approaches.
Editors: KIMURA-SUDA, IDA, IWASAKI, and OTOZAWA

Digest for English Readers
606

Hot Topics in Polymer Science in SPSJ
609
SPSJ PMF Poster Awards 2021

Commentary
An Encouragement to Learn Statistics Takahiro SATO
610

COVER STORY: Highlight Reviews
Statistical Treatment for Distributions of Stereosequence and Monomer Sequence in Vinyl (Co)polymers Tomohiro HIRANO
611
Statistical Mechanical Approach to Polymers Takashi UNEYAMA
614
Four Informatics in Material Science Yuma IWASAKI
617

PolyMANGA
620

COVER STORY: Topics and Products
Improvements of Rheological and Mechanical Properties of Semi-Crystalline Polymers by Controlling Molecular Weight Distribution Takumitsu KIDA
621
Data Analysis and Machine Learning with Small Data Considering Predictability and Applicability of Mathematical Models Hiromasa KANEKO
623
Bayesian Approach to Exploring Novel Materials Kenta HONGO
625
Development of Polymer Materials Using Coarse Grained Molecular Dynamics Simulation Tetsuo TOMINAGA, Kazuya MORISHITA
627

Polymer Science and I: A Personal Account
Crossing Borders and Disciplines Akimitsu NARITA
629

Messages: “Work and Life”
How Shall We Continue Basic Research in the Era of the 100 Year Time Period? Noboru KIKUCHI
630

Front-Line Polymer Science
Enzyme Function on DNA Nanostructure Eiji NAKATA, Takashi MORII
631

Messages from SPSJ
636
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