Improved Scaling of Molecular Network Calculations: The Emergence of Molecular Domains.

The design of materials needed for the storage, delivery, and conversion of (re)useable energy is still hindered by the lack of new, hierarchical molecular screening methodologies that encode information on more than one length scale. Using a molecular network theory as a foundation, we show that to describe charge transport in disordered materials the network methodology must be scaled-up. We detail the scale-up through the use of adjacency lists and depth first search algorithms for during operations on the adjacency matrix. We consider two types of electronic acceptors, perylenediimide (PDI) and the fullerene derivative phenyl-C61-butyric acid methyl ester (PCBM), and we demonstrate that the method is scalable to length scales relevant to grain boundary and trap formations. Such boundaries lead to a decrease in the percolation ratio of PDI with system size, while the ratio for PCBM remains constant, further quantifying the stable, diverse transport pathways of PCBM and its success as a charge-accepting material.

[1]  M. Ratner,et al.  A n-vector model for charge transport in molecular semiconductors. , 2016, The Journal of chemical physics.

[2]  Ankit Agrawal,et al.  Predictive analytics for crystalline materials: bulk modulus , 2016 .

[3]  R. Friend,et al.  What Controls the Rate of Ultrafast Charge Transfer and Charge Separation Efficiency in Organic Photovoltaic Blends. , 2016, Journal of the American Chemical Society.

[4]  Alok Choudhary,et al.  A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials , 2016 .

[5]  S. Darling,et al.  Charge generation in organic photovoltaics: a review of theory and computation , 2016 .

[6]  B. Meredig,et al.  Materials science with large-scale data and informatics: Unlocking new opportunities , 2016 .

[7]  H. Sirringhaus,et al.  Reducing dynamic disorder in small-molecule organic semiconductors by suppressing large-amplitude thermal motions , 2016, Nature Communications.

[8]  J. Idé,et al.  Electron transport in crystalline PCBM-like fullerene derivatives: a comparative computational study , 2014 .

[9]  Mark A. Ratner,et al.  Mesoscale molecular network formation in amorphous organic materials , 2014, Proceedings of the National Academy of Sciences.

[10]  Jae Hyun Kim,et al.  Measurements of branching fractions of τ lepton decays with one or more KS0 , 2014, 1402.5213.

[11]  H. Sirringhaus,et al.  Measurement of molecular motion in organic semiconductors by thermal diffuse electron scattering. , 2013, Nature materials.

[12]  J. Brédas,et al.  Rubrene-based single-crystal organic semiconductors: Synthesis, electronic structure, and charge-transport properties , 2013 .

[13]  Mark A Ratner,et al.  Simple Analytic Description of Collection Efficiency in Organic Photovoltaics. , 2013, The journal of physical chemistry letters.

[14]  G. Schatz,et al.  Controlling Orientational Order in 1-D Assemblies of Multivalent Triangular Prisms. , 2013, The journal of physical chemistry letters.

[15]  Wei-keng Liao,et al.  Fast Algorithms for the Maximum Clique Problem on Massive Sparse Graphs , 2012, WAW.

[16]  Olga Wodo,et al.  A graph-based formulation for computational characterization of bulk heterojunction morphology , 2012 .

[17]  Mikael Östling,et al.  Threshold of hierarchical percolating systems. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Itaru Osaka,et al.  Thienoacene‐Based Organic Semiconductors , 2011, Advanced materials.

[19]  Alán Aspuru-Guzik,et al.  The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid , 2011 .

[20]  S. Forrest,et al.  Molecular and morphological influences on the open circuit voltages of organic photovoltaic devices. , 2009, Journal of the American Chemical Society.

[21]  Nicolas L. Fawzi,et al.  Protofibril assemblies of the arctic, Dutch, and Flemish mutants of the Alzheimer's Abeta1-40 peptide. , 2008, Biophysical journal.

[22]  R. García-Domenech,et al.  Some new trends in chemical graph theory. , 2008, Chemical reviews.

[23]  Christoph J. Brabec,et al.  Design Rules for Donors in Bulk‐Heterojunction Solar Cells—Towards 10 % Energy‐Conversion Efficiency , 2006 .

[24]  A. Usman,et al.  Review of Storage Techniques for Sparse Matrices , 2005, 2005 Pakistan Section Multitopic Conference.

[25]  Valentin D. Mihailetchi,et al.  Device model for the operation of polymer/fullerene bulk heterojunction solar cells , 2005 .

[26]  Jean-Luc Brédas,et al.  Transport Properties in the Rubrene Crystal: Electronic Coupling and Vibrational Reorganization Energy , 2005 .

[27]  Roger Guimerà,et al.  Cartography of complex networks: modules and universal roles , 2005, Journal of statistical mechanics.

[28]  B. Mamedov,et al.  Evaluation of overlap integrals with integer and noninteger n Slater-type orbitals using auxiliary functions , 2002, Journal of molecular modeling.

[29]  Ernesto Estrada,et al.  Physicochemical Interpretation of Molecular Connectivity Indices , 2002 .

[30]  L. Pogliani From molecular connectivity indices to semiempirical connectivity terms: recent trends in graph theoretical descriptors. , 2000, Chemical reviews.

[31]  I. Guseinov,et al.  Computation of overlap integrals over Slater‐type orbitals using auxiliary functions , 1998 .

[32]  Alexandru T. Balaban,et al.  Applications of graph theory in chemistry , 1985, J. Chem. Inf. Comput. Sci..