This website is closing down! Click here to access the new one! Yu Miyazaki, Ryo Nakayama, Nobuaki Yasuo, Yuki Watanabe, Ryota Shimizu, Daniel M. Packwood, Kazunori Nishio, Yasunobu Ando, Masakazu Sekijima, Taro Hitosugi. Bayesian statistics-based analysis of AC impedance spectra. AIP Adv. 10, 2020, 045231 Daniel M. Packwood and Pichaya Pattanasattayavong. Disorder-robust bands from anisotropic orbitals in a coordination polymer semiconductor. J. Phys. Condens. Matter. 32, 2020, 275701. Daniel M. Packwood. Exploring the configuration spaces of surface materials using time-dependent diffraction patterns and unsupervised learning. Sci. Rep. 10, 2020, 5868. Daniel M. Packwood. Nanomaterial design platform based on computation and machine learning. Kagakukougyou 71, 2020, 46 Daniel M. Packwood. Kernelized machine learning for a molecular self-assembly model. Bull. Jpn. Soc. Coord. Chem. 74, 2019, 62 Pichaya Pattanasattayavong, Daniel M. Packwood, and David J. Harding. Structural versatility and electronic structures of copper(I) thiocyanate (CuSCN)-ligand complexes. J. Mater. Chem. C. 7, 2019, 12907 Chayanit Wechwithayakhlung, Daniel M. Packwood, Jidapa Chaopaknam, Pimpisut Worakajit, Somlak Ittisanronnachai, Narong Chanlek, Vinich Promarak, Kanokwan Kongpatpanich, David J. Harding, and Pichaya Pattanasattayavong. Tin(II) Thiocyanate Sn(NSC)2 - a Wide Band Gap Coordination Polymer Semiconductor with 2D Structure. J. Mater. Chem. C. 7, 2019, 3452. Daniel M. Packwood. Structure prediction for bottom-up graphene nanoribbon assembly. Chem. NZ. 84, 2018, 182 (link) Xinqian Li and Daniel M. Packwood. Substrate-molecule decoupling induced by molecular self-assembly - implications for graphene nanoribbon fabrication. AIP Adv. 8, 2018, 045117. Gen Zhang, Masahiko Tsujimoto, Daniel M. Packwood, Nghia Tuan Duong, Yusuke Nishiyama, Kentaro Kadota, Susumu Kitagawa, and Satoshi Horike. Construction of a Hierarchical Architecture of Covalent Organic Frameworks via a Postsynthetic Approach. J. Am. Chem. Soc. 140, 2018, 2602. Daniel M. Packwood. Bayesian Optimization for Materials Science. SpringerBriefs in the Mathematics of Materials (volume 3). Springer, Singapore, 2017. Daniel M. Packwood and Taro Hitosugi. Rapid prediction of molecule arrangements on metal surfaces via Bayesian optimization. Appl. Phys. Express. 10, 2017, 065502 Daniel M. Packwood, Patrick Han, and Taro Hitosugi. Chemical and Entropic Control of the Molecular Self-Assembly Process. Nat .Commum. 8, 2017, 14463 Tomohiro Higashino, Yuma Kurumisawa, Ning Cai, Yamato Fujimori, Yukihiro Tsuji, Shimpei Nimura, Daniel M. Packwood, Jaehong Park, and Hiroshi Imahori. A hydroxamic acid anchoring group for durable dye-sensitized solar cells incorporating a cobalt redox shuttle. ChemSusChem 10, 2017, 3347 Daniel M. Packwood, Patrick Han, and Taro Hitosugi. State Space Reduction and Equivalence Class Sampling of a Molecular Self-Assembly Model. Roy. Soc. Open. Sci. 3, 2016, 150681 Daniel M. Packwood, Helmut G. Katzgraber, and Winfried Teizer. Stochastic Boltzmann Equation for Magnetic Relaxation in High-Spin Molecules. Proc. Roy. Soc. A. 472, 2016, 20150699 Daniel M. Packwood, Kazuaki Oniwa, Tienan Jin, and Naoki Asao. Charge Transport in Organic Crystals: Crucial Role of Correlated Fluctuations Unveiled by Analysis of Feynman Diagrams. J. Chem. Phys. 142, 2015, 144503 Taro Hitosugi, Daniel M. Packwood, Susumu Shiraki. Atomic collision effects during PLD processes: nonstoichiometry control in transparent superconductors. Proc. SPIE 8987, Oxide-based Materials and Devices V, 89870U (March 8 2014) Dimitri V. Louzguine-Luzgin, Daniel M. Packwood, G. Xie, A. Yu. Churyumov. On deformation behavior of a Ni-based bulk metallic glass produced by flux treatment. J. Alloys Compd. 561, 2013, 241 |