Informatics-Based Uncertainty Quantification in the Design of Inorganic Scintillators

REFERENCES

• Kong , C.S. ; Rajan , K. Rational design of binary halide scintillators via data mining . Nuclear Instruments and Methods in Physics Research A 2012 , 680 , 145 – 154 .
   Web of Science ®Google Scholar
• Broderick , S.R. ; Rajan , K. Eigenvalue Decomposition of spectral features in density of states curves. Europhysics Letters 2011, 95, 57005.
   Google Scholar
• Balachandran , P.V. ; Broderick , S.R. ; Rajan , K. Identifying the ‘inorganic gene’ for high-temperature piezoelectric perovskites through statistical learning . Proceedings of the Royal Society A 2011 , 467 , 2271 – 2290 .
   Google Scholar
• Ericksson , L. ; Johansson , E. ; Kettaneh-Wold , N. ; Wold , S. Multi- and Megavariate Data Analysis: Principles and Applications ; UmetricsAb : Umea , 2001 .
   Google Scholar
• Witten , I.H. ; Frank , E. Data Mining, Practical Machine Learning Tools and Techniques with Java Implementations ; Morgan Kaufman : San Diego , CA , 2000 .
   Google Scholar
• Hall , M. ; Frank , E. ; Holmes , G. ; Pfahringer , B. ; Reutemann , P. ; Witten , I.H. The WEKA data mining software: An update . SIGKDD Explorations 2009 , 11 , 18 .
   Google Scholar
• Birowosuto , M.D. ; Dorenbos , P. ; van Eijk , C.W.E. ; Kramer , K.W. ; Gudel , H.U. Scintillation and luminescence properties of Ce3+ doped ternary cesiuma rare-earth halides . Physica Status Solidi A 2007 , 204 , 850 – 860 .
   Web of Science ®Google Scholar
• Dorenbos , P. The 4fn4fn-15d transitions of the trivalent lanthanides in halogenides and chalcogenides . Journal of Luminescence 2000 , 91 , 91 – 106 .
   Web of Science ®Google Scholar
• Dorenbos , P. 5d-level energies of Ce3+ and the crystalline environment, II: Chloride, bromide, and iodide compounds . Physical Review B 2000 , 62 , 15650 – 15659 .
   Web of Science ®Google Scholar
• Dorenbos , P. 5d-level energies of Ce3+ and the crystalline environment, III: Oxides containing ionic complexes . Physical Review B 2001 , 64 , 125117 .
   Web of Science ®Google Scholar
• Lempicki , A. ; Wojtowicz , A.J. Fundamental limitations of scintillators . Journal of Luminescence 1994 , 60–61 , 942 – 947 .
   Web of Science ®Google Scholar
• Lecoq , P. ; Annenkov , A. ; Gektin , A. ; Korzhik , M. ; Pedrini , C. In Inorganic Scintillators for Detector Systems: Physical Principles and Crystal Engineering ; Springer-Verlag : New York , 2006 .
   Google Scholar
• Dorenbos , P. Fundamental limitations in the performance of Ce3+, Pr3+, and Eu2+ activated scintillators . IEEE Transactions on Nuclear Science 2010 , 57 , 1162 – 1167 .
   Web of Science ®Google Scholar
• Bizarri , G. Scintillation mechanisms of inorganic materials: From crystal characteristics to scintillation properties . Journal of Crystal Growth 2010 , 312 , 1213 – 1215 .
   Web of Science ®Google Scholar
• Balcerzyk , M. ; Gontarz , Z. ; Moszynski , M. ; Kapusta , M. Future hosts for fast and high light output cerium-doped scintillator . Journal of Luminescence 2000 , 87–89 , 963 – 966 .
   Web of Science ®Google Scholar
• Glodo , J. ; van Loef , E.V.D. ; Higgins , W.M. ; Shah , K.S. Mixed lutetium iodide compounds . IEEE Transactions on Nuclear Science 2008 , 55 , 1496 – 1500 .
   Web of Science ®Google Scholar
• Pawlak , Z. Rough sets . International Journal of Computer and Information Sciences 1982 , 11 , 341 – 356 .
   Web of Science ®Google Scholar
• Pawlak , Z. Rough set approach to knowledge-based decision support . European Journal of Operational Research 1997 , 99 , 48 – 57 .
   Web of Science ®Google Scholar
• Zadeh , L.A. Fuzzy sets . Information and Control 1965 , 8 , 338 – 353 .
   Web of Science ®Google Scholar
• Vasudevan , M. ; Bhaduri , A.K. ; Raj , B. ; Rao , K.P. Genetic-algorithm-based computational models for optimizing the process parameters of A-TIG welding to achieve target bead geometry in type 304 L(N) and 316 L(N) stainless steels . Materials and Manufacturing Processes 2007 , 22 , 641 – 649 .
   Web of Science ®Google Scholar
• Miettinen , K. Using interactive multiobjective optimization in continuous casting of steel . Materials and Manufacturing Processes 2007 , 22 , 585 – 593 .
   Web of Science ®Google Scholar
• Saxen , H. ; Pettersson , F. ; Gunturu , K. Evolving nonlinear time-series models of the hot metal silicon content in the blast furnace . Materials and Manufacturing Processes 2007 , 22 , 577 – 584 .
   Web of Science ®Google Scholar
• Jackiewicz , J. Optimization of the performance of porous low-carbon steels by means of an evolution strategy . Materials and Manufacturing Processes 2007 , 22 , 623 – 633 .
   Web of Science ®Google Scholar
• Goldberg , D.E. Genetic Algorithms in Search, Optimization and Machine Learning ; Addison-Wesley Professional : New Delhi , 1989 .
   Google Scholar
• Mitchell , M. An Introduction to Genetic Algorithms (Complex Adaptive Systems) ; MIT Press : Cambridge , MA , 1998 .
   Google Scholar
• Goldberg , D.E. ; Thomas , A.L. Genetic Algorithms: A Bibliography 1962–1986 ; University of Alabama : Tuscaloosa , 1986 .
   Google Scholar
• Zhang , Q. ; Mahfouf , M. ; Yates , J.R. ; Pinna , C. ; Panoutsos , G. ; Boumaiza , S. ; Greene , R.J. ; de Leon , L. Modeling and optimal design of machining-induced residual stresses in aluminum alloys using a fast hierarchical multiobjective optimization algorithm . Materials and Manufacturing Processes 2011 , 26 , 508 – 520 .
   Web of Science ®Google Scholar
• Li , X. ; Petersen , L. ; Broderick , S. ; Narasimhan , B. ; Rajan , K. Identifying drug release mechanisms from combinatorial biomaterial libraries via hybrid data mining methods . ACS Combinatorial Science 2011 , 13 , 50 – 58 .
   PubMedGoogle Scholar