Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Miki, Yasuo
Toba, Makoto
Yoshimura, Yuji
and
Murata, Kazuhisa
2007.
Compositional Analysis of GTL and BTL Diesel Oils.
Journal of the Japan Petroleum Institute,
Vol. 50,
Issue. 2,
p.
108.
Webb-Robertson, Bobbie-Jo M.
Ferris, Kim F.
and
Jones, Dumont M.
2008.
Design Rules for Ce-Activated Scintillating Radiation Detection Materials: Compromises Between Luminosity and Stopping Power.
IEEE Transactions on Nuclear Science,
Vol. 55,
Issue. 3,
p.
1210.
Ferris, Kim F.
Webb-Robertson, Bobbie-Jo M.
Jordan, David V.
and
Jones, Dumont M.
2008.
Data-Driven Exploration of the Ionization-Phonon Partitioning in Scintillating Radiation Detector Materials.
IEEE Transactions on Nuclear Science,
Vol. 55,
Issue. 3,
p.
1042.
Yu, Gang
and
Chen, Jingzhong
2009.
Integration Materials Data between Heterogeneous Databases Based on Data Warehouse Technologies.
p.
233.
Yu, Gang
Chen, Jingzhong
and
Zhu, Li
2009.
Data Mining Techniques for Materials Informatics: Datasets Preparing and Applications.
p.
189.
McCluskey, Patrick J.
and
Vlassak, Joost J.
2010.
Combinatorial nanocalorimetry.
Journal of Materials Research,
Vol. 25,
Issue. 11,
p.
2086.
2010.
Waste Immobilization in Glass and Ceramic Based Hosts.
p.
57.
Doreswamy
Hemanth, K. S.
Vastrad, Channabasayya M.
and
Nagaraju, S.
2011.
Advances in Computer Science and Information Technology.
Vol. 131,
Issue. ,
p.
512.
Ogunseitan, Oladele A.
and
Schoenung, Julie M.
2012.
Human health and ecotoxicological considerations in materials selection for sustainable product development.
MRS Bulletin,
Vol. 37,
Issue. 4,
p.
356.
2012.
Molecular Modeling for the Design of Novel Performance Chemicals and Materials.
p.
1.
Freiman, Stephen
and
Rumble, John
2012.
A Perspective on Materials Databases.
Data Science Journal,
Vol. 11,
Issue. 0,
p.
ASMD7.
Saad, Yousef
Gao, Da
Ngo, Thanh
Bobbitt, Scotty
Chelikowsky, James R.
and
Andreoni, Wanda
2012.
Data mining for materials: Computational experiments withABcompounds.
Physical Review B,
Vol. 85,
Issue. 10,
Gautham, B. P.
Singh, Amarendra K.
Ghaisas, Smita S.
Reddy, Sreedhar S.
and
Mistree, Farrokh
2013.
ICoRD'13.
p.
1301.
Wang, Zhuo
Yang, Xiaoyu
Zheng, Yufei
Yong, Qilong
Su, Hang
and
Yang, Caifu
2014.
Integrated materials design and informatics platform within the materials genome framework.
Chinese Science Bulletin,
Vol. 59,
Issue. 15,
p.
1755.
Abuomar, O.
Nouranian, S.
King, R.
Ricks, T.M.
and
Lacy, T.E.
2015.
Comprehensive mechanical property classification of vapor-grown carbon nanofiber/vinyl ester nanocomposites using support vector machines.
Computational Materials Science,
Vol. 99,
Issue. ,
p.
316.
Liu, Ruoqian
Yabansu, Yuksel C.
Agrawal, Ankit
Kalidindi, Surya R.
and
Choudhary, Alok N.
2015.
Machine learning approaches for elastic localization linkages in high-contrast composite materials.
Integrating Materials and Manufacturing Innovation,
Vol. 4,
Issue. 1,
p.
192.
Chowdhury, Aritra
Kautz, Elizabeth
Yener, Bülent
and
Lewis, Daniel
2016.
Image driven machine learning methods for microstructure recognition.
Computational Materials Science,
Vol. 123,
Issue. ,
p.
176.
Erkimbaev, A. O.
Zitserman, V. Yu.
and
Kobzev, G. A.
2017.
The intensive use of digital data in modern natural science.
Automatic Documentation and Mathematical Linguistics,
Vol. 51,
Issue. 5,
p.
201.
Ubaru, Shashanka
Międlar, Agnieszka
Saad, Yousef
and
Chelikowsky, James R.
2017.
Formation enthalpies for transition metal alloys using machine learning.
Physical Review B,
Vol. 95,
Issue. 21,
Geilhufe, R. Matthias
Bouhon, Adrien
Borysov, Stanislav S.
and
Balatsky, Alexander V.
2017.
Three-dimensional organic Dirac-line materials due to nonsymmorphic symmetry: A data mining approach.
Physical Review B,
Vol. 95,
Issue. 4,