The invention provides a method for controlling an automated chemistry platform using synthetic procedures written in natural language. The method uses natural language processing (NLP) techniques to interpret a synthetic procedure written in natural scientific language and extracts a machine-readable instruction set comprising the distinct operations necessary for carrying out the synthesis on an automated chemical synthesis platform. The method optionall also includes the step of executing the machine-readable instruction set on an automated chemical synthesis platform.

The invention provides a method for controlling an automated chemistry platform using synthetic procedures written in natural language. The method uses natural language processing (NLP) techniques to interpret a synthetic procedure written in natural scientific language and extracts a machine-readable instruction set comprising the distinct operations necessary for carrying out the synthesis on an automated chemical synthesis platform. The method optionall also includes the step of executing the machine-readable instruction set on an automated chemical synthesis platform.

The invention is a system for predicting emissions of pollutants from a vehicle equipped with an engine using processors (3) to determine emission of pollutants. The processors include a first group of processors (1) for carrying out calculations of chemical kinetics for determining the amounts of chemical compounds present in a chemical reaction in the engine and a second group of processors (2) for carrying out calculations of emission of pollutants simultaneously with the calculation of chemical kinetics, allowing determination of the emission of pollutants from the calculated amounts of chemical compounds. The first group of processors (1) has a global supervisor processor (4) allowing storing data required for the calculations and to distribute the calculations to clusters (5) of processors.

The invention relates to a volatile liquid chemical compound physical parameter database construction method; a fragrance physical composition evolution prediction method and corresponding systems.

The invention relates to a volatile liquid chemical compound physical parameter database construction method; a fragrance physical composition evolution prediction method and corresponding systems.

In a method of molecular scaffold hopping an interface of a scheduler computer sends instructions, prepared by the scheduler computer, to a job runner computer to perform a plurality of separate computational tasks. Each of the separate computational tasks includes calculating one or more chemical properties for a query molecule or molecules in a library of molecules. One or more of the plurality of separate computational tasks performed on the job runner computer are preemptible computing instances. Status indicators sent from the job runner computer are received by the interface for each of the plurality of separate computational tasks. The indicators are one of: incomplete, completed, or failed computing instances. The interface resends the instructions to the job runner computer that correspond to the separate computational tasks having the failed computing instance indicator to increase fault-tolerance against the separate computational tasks not attaining the completed computing instance indicator.

A method for managing flow of particles into an array of pairwise-point-interaction-module includes receiving a first set of particles into a first queue. The first set is a proper subset of a second set of particles that comprises all particles that are to be passed into an array of pairwise-point-interaction-modules during a current time period. Prior to having received all particles from the second set, particles from the first set are allowed to pass from the first queue into the array.

A method for managing flow of particles into an array of pairwise-point-interaction-module includes receiving a first set of particles into a first queue. The first set is a proper subset of a second set of particles that comprises all particles that are to be passed into an array of pairwise-point-interaction-modules during a current time period. Prior to having received all particles from the second set, particles from the first set are allowed to pass from the first queue into the array.

Direct measurement and simulation of real-time production rates of chemical products in complex chemical plants is complex. A predictive model developed based on machine learning algorithms using historical sensor data and production data provides accurate real-time prediction of production rates of chemical products in chemical plants. An optimization model based on machine learning algorithms using clustered historical sensor data and production data provides optimal values for controllable parameters for production maximization.

Direct measurement and simulation of real-time production rates of chemical products in complex chemical plants is complex. A predictive model developed based on machine learning algorithms using historical sensor data and production data provides accurate real-time prediction of production rates of chemical products in chemical plants. An optimization model based on machine learning algorithms using clustered historical sensor data and production data provides optimal values for controllable parameters for production maximization.