图书简介

Volume 1: Big Data Methods in Experimental Materials Discovery (Surya Kalidindi, Sergei V Kalinin and Turab Lookman): Preface (Ian Foster and Sergei V Kalinin); Preface (Surya Kalidindi, Sergei V Kalinin and Turab Lookman); High-Throughput Computational Studies in Catalysis and Materials Research, and their Impact on Rational Design (M A F Afzal and J Hachmann); Machine Learning Approaches for Extracting Process-Structure-Property Relationships from Experimental Data and Literature (Nils Persson, Michael McBride, Elsa Reichmanis, and Martha Grover); Materials Informatics and Data System for Polymer Nanocomposites Analysis and Design (Wei Chen, Linda Schadler, Cate Brinson, Yixing Wang, Yichi Zhang, Aditya Prasad, Xiaolin Li, and Akshay Iyer); Quantitative Multiscale Microscopy of Defects and Deformation for Application to Materials Modeling (Hojun Lim, Jay D Carroll, Douglas L Medlin, and Khalid Hattar); Data Analytics on Phase-Field Simulation Datasets (Yuksel C Yabansu and Surya R Kalidindi); Materials Image Informatics Using Deep Learning (Ankit Agrawal, Kasthurirangan Gopalakrishnan, and Alok Choudhary); Scanning Probe Microscopy in the Information Age (L Collins, S Somnath, SV Kalinin, and A Belianinov); Interpreting Force Fingerprints on the Nanoscale: Machine-Aided Approaches to Atomic Force Microscopy(Matteo Chiesa, Harry Apostoleris, and Chia-yun Lai); Big and Deep Data Methods in Scanning Probe Microscopy and Spectroscopy (Sergei V Kalinin, Evgheni Strelcov, Rama K Vasudevan, and Maxim Ziatdinov); Deep Learning in Electron and Scanning Probe Microscopy (A Maksov, S V Kalinin, R K Vasudevan, and M Ziatdinov); Controlling the Dose Distribution in Scanning Transmission Electron Microscope (STEM) Images by Sub-Sampling and Inpainting (N D Browning, A Stevens, L Kovarik, A Liyu, and B L Mehdi); Micro Computed Tomography in 3D Micro-structural Analysis: Basics, Challenges, Future Perspective (Sourav Mandal and Bikramjit Basu); Deep Learning and the Structural Imaging of Materials (N Laanait); Dictionary-Based Indexing of Large Scale Electron Back-Scatter Diffraction Data Sets (S Singh, F Ram, W Lenthe, and M De Graef); Algorithms in Diffraction Profile Analysis (Susheela P Singh, Alisa R Paterson, Laura J Wendelberger, Chris M Fancher, Brian J Reich, Ralph C Smith, Alyson G Wilson, and Jacob L Jones); Volume 2: Advanced Analysis Solutions for Leading Experimental Techniques (Kerstin Kleese Van Dam, Kevin Yager, Stuart Campbell, Richard Farnsworth, Maartje van Dam): Preface (Ian Foster and Sergei V Kalinin); Preface (Kerstin Kleese van Dam, Kevin Yage, Stuart Campbell, Richard Farnsworth and Maartje van Dam); Experimental Analysis of Powder Diffraction Data (Mark Spillman, Daniel Nicholls and Kenneth Shankland); Analysis Tools for Angle Resolved and X-ray Photoemission Spectroscopy (Andrew Walter); Multi-modal Synchrotron Characterization: Modern Techniques and Data Analysis (Y-c Karen Chen-Wiegart, Stuart Campbell, Kevin G Yager, Yijin Liu, Anatoly Frenkel, Lin Yang, Jianming Bai, Matt McCormick, Daniel Allan, and Mark Basham); Tomographic Reconstruction for Synchrotron Tomography (Dilworth Y Parkinson, Doga Gursoy, Daniël M Pelt, Singanallur Venkatakrishnan, Rick Archibald, K Aditya Mohan, Tekin Bicer, Matthias Vogelgesang, James Sethian, Nicola Wadeson, Mark Basham, and Tomáš Faragó); Next-Generation Information Technology Systems for Fast High-Resolution Detectors in Electron Microscopy (Dieter Weber, Alexander Clausen, and Rafal Dunin-Borkowski); X-Ray Photon Correlation Spectroscopy Data Reduction Using Virtualized Resources (Nicholas Schwarz, Faisal Khan, Collin Schmitz, Ben Pausma, Suresh Narayanan, and Alec Sandy); Machine-Learning Assisted Structure Determination of Metallic Nanoparticles: A Benchmark (Yuewei Lin, Mehmet Topsakala, Janis Timoshenko, Deyu Lu, Shinjae Yoo, and Anatoly I Frenkel); Accelerated Computing for X-ray Ptychography at NSLS-II (Yao-Lung L Fang, Sungsoo Ha, Xiaojing Huang, Hanfei Yan, Zhihua Dong, Yong S Chu, Stuart I Campbell, Wei Xu, and Meifeng Lin); Visual Analytics for Scientific Data in NSLS II (Wei Xu, Sungsoo Ha, Wen Zhong, Shenghui Cheng, Hanfei Yan, Kevin Yager, Xiaojing Huang, Klaus Mueller, and Yong S Chu); Psocake: GUI for Making Data Analysis a Piece of Cake (Chun Hong Yoon); Cross Cutting Software Solutions in Support of Experimental Analysis Challenges at National Scattering Facilities (Thomas Proffen and Garrett E Granroth); Building Mathematics, Algorithms, and Software for Experimental Facilities: The Center for Advanced Mathematics for Energy Research Applications (H Chang, J J Donatelli, P Enfedaque, G Freychet, M Haranczyk, A Hexemer, Z Hu, O Jain, H Krishnan, D Kumar, X Li, L Lin, M MacNeil, S Marchesini, X Mo, M Noack, K Pande, R Pandol, D Parkinson, D M Pelt, T Perciano, D A Shapiro, D Ushizima, C Yang, P H Zwart, and J A Sethian); Autonomous Experimental Design and Execution (Kristofer G Reyes, Francis J Alexander); Optimal Bounds for Nonlinear Partial Differential Equations (Michael McKerns, Francis Alexander, K Hickmann, T J Sullivan, and D Vaughan); Provenance as a Method for Reproducible, Multi-Modal X-Ray Experiments (Huub Van Dam, Eli Stavitski, Simon Billinge, Christopher (CJ) Wright, and Line Pouchard); Cyberinfrastructure and System Software for Online Analysis of Large-Scale Data: Challenges and Design Choices (Rajkumar Kettimuthu, Zhengchun Liu, Tekin Bicer, and Ian Foster); Superfacility: The Convergence of Data, Compute, Networking, Analytics and Software (Katie Antypas, Shane Canon, Eli Dart, Kjiersten Fagnan, Lisa Gerhardt, Doug Jacobsen, Glenn K Lockwood, Inder Monga, Peter Nugent, Lavanya Ramakrishnan, Cory Snavely, Dilworth Parkinson, Alexander Hexemer, and Craig Tull); Policy Considerations when Federating Facilities for Experimental and Observational Data Analysis (Mallikarjun Shankar, Suhas Somnath, Sadaf Alam, Derek Feichtinger, Leonardo Sala, and Jack Wells);

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