Design of a full-profile-matching solution for high-throughput analysis of multiphase samples through powder X-ray diffraction.
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[1] Pedro Serna,et al. Combining high-throughput experimentation, advanced data modeling and fundamental knowledge to develop catalysts for the epoxidation of large olefins and fatty esters , 2008 .
[2] A. Corma,et al. Synthesis methodology, stability, acidity, and catalytic behavior of the 18×10 member ring pores ITQ-33 zeolite , 2008 .
[3] I. Takeuchi,et al. Rapid structural mapping of ternary metallic alloy systems using the combinatorial approach and cluster analysis. , 2007, The Review of scientific instruments.
[4] Manuel Moliner,et al. Prediction of ITQ-21 Zeolite Phase Crystallinity: Parametric Versus Non-parametric Strategies , 2007 .
[5] Manuel Moliner,et al. High-throughput synthesis and catalytic properties of a molecular sieve with 18- and 10-member rings , 2006, Nature.
[6] Frédéric Clerc,et al. High throughput experimentation in oxidation catalysis: Higher integration and “intelligent” software , 2006 .
[7] José M. Serra,et al. A New Mapping/Exploration Approach for HT Synthesis of Zeolites , 2006 .
[8] J. M. Serra,et al. Support vector machines for predictive modeling in heterogeneous catalysis: a comprehensive introduction and overfitting investigation based on two real applications. , 2006, Journal of combinatorial chemistry.
[9] Niko Beerenwinkel,et al. A mutagenetic tree hidden Markov model for longitudinal clonal HIV sequence data. , 2006, Biostatistics.
[10] Manuel Moliner,et al. Rational design and HT techniques allow the synthesis of new IWR zeolite polymorphs. , 2006, Journal of the American Chemical Society.
[11] Laurent A Baumes,et al. MAP: an iterative experimental design methodology for the optimization of catalytic search space structure modeling. , 2006, Journal of combinatorial chemistry.
[12] Christian J. Long,et al. Data management and visualization of x-ray diffraction spectra from thin film ternary composition spreads , 2005 .
[13] Claude Mirodatos,et al. Design of Discovery Libraries for Solids Based on QSAR Models , 2005 .
[14] Wei Dong,et al. High-throughput powder diffraction. IV. Cluster validation using silhouettes and fuzzy clustering , 2004 .
[15] Claude Mirodatos,et al. Using Artificial Neural Networks to Boost High‐throughput Discovery in Heterogeneous Catalysis , 2004 .
[16] Claude Mirodatos,et al. The development of descriptors for solids: teaching "catalytic intuition" to a computer. , 2004, Angewandte Chemie.
[17] Wei Dong,et al. PolySNAP: a computer program for analysing high-throughput powder diffraction data , 2004 .
[18] Wei Dong,et al. High-throughput powder diffraction. II. Applications of clustering methods and multivariate data analysis , 2004 .
[19] Jonathan Paisley,et al. High-throughput powder diffraction. I. A new approach to qualitative and quantitative powder diffraction pattern analysis using full pattern profiles , 2004 .
[20] Dimitrios Gunopulos,et al. Iterative Incremental Clustering of Time Series , 2004, EDBT.
[21] Robert Docherty,et al. Automation of Solid form Screening Procedures in the Pharmaceutical Industry—How to Avoid the Bottlenecks , 2004 .
[22] Claude Mirodatos,et al. How to Design Diverse Libraries of Solid Catalysts , 2003 .
[23] Stacey I. Zones,et al. A combustion-free methodology for synthesizing zeolites and zeolite-like materials , 2003, Nature.
[24] Eamonn J. Keogh,et al. Probabilistic discovery of time series motifs , 2003, KDD '03.
[25] José M. Serra,et al. Styrene from toluene by combinatorial catalysis , 2003 .
[26] Avelino Corma,et al. State of the art and future challenges of zeolites as catalysts , 2003 .
[27] Eamonn J. Keogh,et al. Exact indexing of dynamic time warping , 2002, Knowledge and Information Systems.
[28] Jordi Rius,et al. A large-cavity zeolite with wide pore windows and potential as an oil refining catalyst , 2002, Nature.
[29] Lothar M. Schmitt,et al. Theory of genetic algorithms , 2001, Theor. Comput. Sci..
[30] J. Buhler,et al. Finding motifs using random projections , 2001, RECOMB.
[31] Heikki Mannila,et al. Global partial orders from sequential data , 2000, KDD '00.
[32] Eamonn J. Keogh,et al. Scaling up dynamic time warping for datamining applications , 2000, KDD '00.
[33] Mohammed J. Zaki,et al. Scalable Feature Mining for Sequential Data , 2000, IEEE Intell. Syst..
[34] Panu Somervuo,et al. Self-Organizing Maps and Learning Vector Quantization for Feature Sequences , 1999, Neural Processing Letters.
[35] D. Bish,et al. Multireflection RIR and intensity normalizations for quantitative analyses: Applications to feldspars and zeolites , 1995, Powder Diffraction.
[36] D. Bish,et al. Quantitative phase analysis using the Rietveld method , 1988 .
[37] S. Chiba,et al. Dynamic programming algorithm optimization for spoken word recognition , 1978 .
[38] F. Chung,et al. Quantitative interpretation of X-ray diffraction patterns of mixtures. I. Matrix-flushing method for quantitative multicomponent analysis , 1974 .
[39] Jose Manuel Serra,et al. Zeolite synthesis modelling with support vector machines: a combinatorial approach. , 2007, Combinatorial chemistry & high throughput screening.
[40] Arne Karlsson,et al. Combinatorial hydrothermal synthesis of titanium zinc silicates , 2004 .
[41] David E. Goldberg,et al. The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .
[42] M. Fransen. Faster X-ray powder diffraction measurements , 2002 .
[43] Eamonn J. Keogh,et al. Derivative Dynamic Time Warping , 2001, SDM.
[44] Ron Sun,et al. Sequence Learning - Paradigms, Algorithms, and Applications , 2001 .
[45] D. Bish,et al. Accuracy in quantitative x-ray powder diffraction analyses , 1994 .