A multi-step and multi-level approach for computer aided molecular design

Harper, Peter Mathias; Gani, Rafiqul

doi:10.1016/s0098-1354(00)00410-5

Cited by 188 publications

(86 citation statements)

References 7 publications

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“…The CAMD technique (macro-meso scale) used in this work (Sataynarayana et al, 2009) involves three main steps: problem formulation, repeat unit identification and result analysis, similar to the algorithms proposed by Harper and Gani (2000) and Gani et al (1991). Note that many other CAMD techniques proposed by others (Maranas, 1996, Venkatasubramanian et al, 1994 could, in principle, have also been employed.…”

Section: The Camd Technique For Polymer Repeat-unit Designmentioning

confidence: 99%

“…The adopted multi-level approach of Harper and Gani (2000) has been employed (Sataynarayana et al, 2009). For the polymer repeat-unit design problem, which uses the GC + model (Sataynarayana et al, 2007) for predicting the properties of the generated repeat-unit structures, polymer repeat-units are generated in successive hierarchical steps and are screened against a corresponding set of property constraints.…”

Section: Repeat-unit Identification and Screening (Macroand Meso-scales)mentioning

confidence: 99%

“…Different types have been proposed for homo-polymer repeat-unit structure identification for a specified (desired) set of properties: techniques based on mixed integer linear programming (MILP) using group contribution property models by Maranas (1996); a genetic algorithm based technique also employing group contribution property models by Venkatasubramanian et al (1994); and the multistep group contribution-atom connectivity based technique, adopted from the multi-step, the multilevel hybrid CAMD algorithm of Harper and Gani (2000) for molecular design by Sataynarayana et al (2009). The latter, which suppresses the combinatorial explosion problem, has been modified to use the GC + models of Satyanarayana et al (2007) and has been further extended in this paper to add the micro-scale analysis option.…”

Section: Brazilian Journal Of Chemical Engineeringmentioning

confidence: 99%

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Computer aided polymer design using multi-scale modelling

Satyanarayana¹,

Abildskov²,

Gani³

et al. 2010

Braz. J. Chem. Eng.

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-The ability to predict the key physical and chemical properties of polymeric materials from their repeat-unit structure and chain-length architecture prior to synthesis is of great value for the design of polymerbased chemical products, with new functionalities and improved performance. Computer aided molecular design (CAMD) methods can expedite the design process by establishing input-output relations between the type and number of functional groups in a polymer repeat unit and the desired macroscopic properties. A multi-scale model-based approach that combines a CAMD technique based on group contribution plus models for predicting polymer repeat unit properties with atomistic simulations for providing first-principles arrangements of the repeat units and for predictions of physical properties of the chosen candidate polymer structures, has been developed and tested for design of polymers with desired properties. A case study is used to highlight the main features of this multi-scale model-based approach for the design of a polymer-based product.

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Section: The Camd Technique For Polymer Repeat-unit Designmentioning

confidence: 99%

Section: Repeat-unit Identification and Screening (Macroand Meso-scales)mentioning

confidence: 99%

Section: Brazilian Journal Of Chemical Engineeringmentioning

confidence: 99%

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Computer aided polymer design using multi-scale modelling

Satyanarayana¹,

Abildskov²,

Gani³

et al. 2010

Braz. J. Chem. Eng.

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“…Employing systematic algebraic techniques to design molecules based on GCM decreases the permutations of groups that need to be checked if they have a valid molecule hidden in them. Algorithms to identify the molecules that meet the process targets have been developed by many research groups, including Marcoulaki and Kokossis (1998), Harper et al (1999), Harper and Gani (2000), Eljack et al (2007) and Chemmangattuvalappil et al (2009). In this contribution, the focus is to introduce methods that improve the efficiency of solving the molecular design problem as part of the simultaneous solution of process and product design problems.…”

Section: Introductionmentioning

confidence: 99%

An algebraic approach for simultaneous solution of process and molecular design problems

Bommareddy

Chemmangattuvalappil

Solvason

et al. 2010

Braz. J. Chem. Eng.

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-The property integration framework has allowed for simultaneous representation of processes and products from a properties perspective and thereby established a link between molecular and process design problems. The simultaneous approach involves solving two reverse problems. The first reverse problem identifies the property targets corresponding to the desired process performance. The second reverse problem is the reverse of a property prediction problem, which identifies the molecular structures that match the targets identified in the first problem. Group Contribution Methods (GCM) are used to form molecular property operators that will be used to track properties. Earlier contributions in this area have worked to include higher order estimation of GCM for solving the molecular design problem. In this work, the accuracy of the property prediction is further enhanced by improving the techniques to enumerate higher order groups. Incorporation of these higher order enumeration techniques increases the efficiency of property prediction and thus the application range of the group contribution methods in molecular design problems. Successful tracking of properties is the key in applying the reverse problem formulation for integrated process and product design problems. An algebraic technique has been developed for solving process and molecular design problems simultaneously. Since both process and molecular property operators target the same optimum process performance, the set of inequality expressions can be solved simultaneously to identify the molecules that meet the desired process performance. Since this approach is based on an algebraic algorithm, any number of properties can be tracked simultaneously.

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“…Such a problem is a perfect match for the application of chemical product design especially computer aided molecular design (CAMD), where we try to find a chemical product that exhibits certain desirable or specified properties (Constantinou et al, 1996, Harper andGani, 2000). With successes among which the finding of new refrigerants in replacement of proscribed CFC components or the finding of solvent in separation processes, CAMD inverse methodology has shown that two kind of information must be handled: molecular information to describe the product and thermodynamic information that concerns the product property values under given operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Computer-aided aroma design. II. Quantitative structure–odour relationship

Korichi¹,

Gerbaud²,

Talou³

et al. 2008

Chemical Engineering and Processing: Process Intensification

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Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and their odour quality are definitely subjective or their odour intensity are partly subjective as stated in Rossitier's review (1996). The CAAD methodology and a novel molecular framework were presented in part I. Part II focuses on a classification methodology to characterize the odour quality of molecules based on Structure -Odour Relation (SOR). Using 2D and 3D molecular descriptors, Linear Discriminant Analysis (LDA) and Artificial Neural Network are compared in favour of LDA. The classification into balsamic / non balsamic quality was satisfactorily solved. The classification among five sub notes of the balsamic quality was less successful, partly due to the selection of the Aldrich's Catalog as the reference classification. For the second case, it is shown that the sweet sub note considered in Aldrich's Catalog is not a relevant sub note, confirming the alternative and popular classification of Jaubert et al., (1995), the field of odours.

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A multi-step and multi-level approach for computer aided molecular design

Cited by 188 publications

References 7 publications

Computer aided polymer design using multi-scale modelling

Computer aided polymer design using multi-scale modelling

An algebraic approach for simultaneous solution of process and molecular design problems

Computer-aided aroma design. II. Quantitative structure–odour relationship

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