Susilpa Bommareddy

Reverse problem formulation approach to molecular design using property operators based on signature descriptors

Abstract In this work, an algorithm has been developed for the solution of property based molecular design problems. The recently introduced concept of molecular signature descriptors has been used to design molecules that meet the property targets corresponding to a required process performance. It has been shown that a variety of topological indices (TI) of molecules can be represented in terms of molecular signatures. Signatures can be used to represent different molecular groups if the property targets can be calculated using group contribution models as well. Therefore, the developed algorithm has the ability to combine a variety of property models based on group contribution expressions and topological indices based QSAR/QSPRs to track different property targets in molecular design. This algorithm utilizes molecular property operators formed from signatures for solving the reverse problem of obtaining the molecular structures that satisfy the property targets estimated during the process design step. The principles of graph theory are incorporated to ensure that the design provides feasible molecular structures. Since the molecular operators are formed based on molecular signatures, property models based on different TIs can be represented on the same property platform. Techniques have been developed to describe all TIs with a single signature height. The accuracy of this method depends only on how well the actual property–TI relationships are estimated. Since many TIs can be used to describe each property, this algorithm generally provides reliable results. In addition to physical properties, a wide variety of biological activities can be tracked using the correlations with TIs. This contribution will illustrate the developed methods and highlight their use through a case study.

Simultaneous solution of process and molecular design problems using an algebraic approach

Abstract Traditionally process design and molecular design problems have been treated as two separate problems, with little or no feedback between them. Introduction of the property integration framework has allowed for simultaneous representation of processes and products from a property perspective and hence established a link between molecular and process design. The simultaneous approach involves solving two reverse problems. The first reverse problem identifies the input molecules’ 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 and these help in tracking properties. Earlier contributions in this area have tried to include higher order estimation of GCM for solving the molecular design problem. In this work, the accuracy of property prediction is 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 range of applicability of group contribution methods to molecular design problems. This method of generation enables the identification of structural isomers to some extent as it puts a check on the possibility of nonexistence of each higher order group in each combination. Property operator based techniques are used to track properties in both process and molecular design problems. The developed algorithm solves the set of inequality expressions of process and molecular design problems simultaneously to identify the molecules that meet the process performance and environmental restrictions defined in terms of properties. Since the algorithm should be able to solve for any number of properties, an algebraic approach is used to generate possible molecules within the required property range. This contribution will use a case study to highlight the principles of the developed methodology.

Combined property clustering and GC+ techniques for process and product design

Abstract Recent developments in the area of process and product integration have enabled the systematic identification of suitable candidate molecules to meet certain process performance. In this approach, the property targets for the input molecules corresponding to the optimum process performance have been identified in the first step and the molecules that have the target properties have been designed in the next step. The focus of this work is to develop a combined property clustering and GC + algorithm to identify molecules that meet the property targets identified during the process design stage. In our earlier works, a methodology was introduced for identifying molecules with a given set of properties by combining property clustering and group contribution methods. Yet, there are situations when the property contributions of some of the molecular groups of interest are not available in literature. To address this limitation, an algorithm has been developed to include the property contributions predicted by combined group contribution and connectivity indices methods into the cluster space. For the design of simple monofunctional molecules, a modified visual approach has been used, while for the design of more complicated structures an algebraic method has been developed. The applicability of the algebraic method has been increased by including the property contributions from second and third order groups.

A Systematic Approach to Determine Economic Potential and Environmental Impact of Biorefineries

Abstract The integrated biorefinery has the potential to provide a strong, self-dependent alternative to the use of fossil fuels for the production of chemicals and energy, but difficulties arise in measuring the potential economic and environmental benefit of the biorefinery. A myriad of products and production pathways are possible in this growing field of biorefining, and the production path with maximum value and minimum environmental impact cannot be determined on heuristics alone. A framework is needed to determine the most optimal route based on measures of economic and environmental performance. Gross profit and net present value are used as economic metrics in the short term and long term respectively, and environmental impact is measured using the WAR algorithm developed by Young and Cabezas [1999]. Top candidates in economic and environmental performance are then subject to process integration techniques in order to minimize mass and energy usage, and these integrated biorefineries are once again analyzed for optimal performance.

Computer Aided Flowsheet Design using Group Contribution Methods

Abstract In this paper, a systematic group contribution based framework is presented for synthesis of process flowsheets from a given set of input and output specifications. Analogous to the group contribution methods developed for molecular design, the framework employs process groups to represent different unit operations in the system. Feasible flowsheet configurations are generated using efficient combinatorial algorithms and the performance of each candidate flowsheet is evaluated using a set of flowsheet properties. A systematic notation system called SFILES is used to store the structural information of each flowsheet to minimize the computational load and information storage. The design variables for the selected flowsheet(s) are identified through a reverse simulation approach and are used as initial estimates for rigorous simulation to verify the feasibility and performance of the design.

Molecular Signature Descriptors for Integrated Flowsheet and Molecular Design

The reverse problem formulation is a technique for solution of integrated process and product design problems from a properties perspective. In this work, an algorithm is introduced for reverse problem formulations using property operators based on molecular signature descriptors. A general framework has been developed for the integration of flowsheet design techniques with the solution of combined process and molecular design problems.

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

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.

An Integrated Framework for Flowsheet Synthesis and Molecular Design

Abstract This paper highlights a novel hybrid method for Computer Aided Flowsheet Design (CAFD) and its effective integration with molecular design. Both CAFD and CAMD methodologies are based on Group Contribution (GC) approaches and hence the evaluation of solution alternatives for each is straightforward given the models and the group contributions. Also by integrating them, the effect of changes in the involved product on a process as well the effect of changes in the process on the product can be rapidly evaluated. Simple notation systems, SFILES and SMILES are employed for efficient storage and transfer of flowsheet and molecular information respectively. The design variables for the selected flowsheet(s) are identified through a reverse simulation approach. Once the design parameters of an optimal flowsheet alternative have been identified, rigorous simulation is used to verify the predicted performance.

Incorporating Molecular Signature Descriptors in Reverse Problem Formulations

Abstract The recently introduced concept of reverse problem formulation has been helpful for the solution of integrated process and product design problems from a properties perspective. A new algorithm has been developed that utilizes molecular property operators based on molecular signatures to obtain the molecular structures corresponding to the property targets estimated during the process design step. The algorithm allows property models based on different Topological indices (TI) and group contribution models to be represented on the same property platform.

Novel Molecular Design Technique Using Property Operators Based on Signature Descriptors

Abstract In this work, we are introducing an algorithm that uses molecular signature descriptors for reverse problem formulations. This algorithm utilizes molecular property operators based on signatures for solving the reverse problem of obtaining the molecular structures corresponding to the property targets estimated during the process design step. The algorithm allows property models based on different Topological indices (TI) and group contribution models to be represented on the same property platform.