Abstract: The method includes using known compositions to train the convolutional neural network, a loss function being minimized for the training; examining whether the value of a loss function meets a predefined criterion, the following steps being carried out selectively in the case where the criterion is not met—selecting a test composition from a set of predefined test compositions by an active learning module; activating a chemical apparatus for producing and examining compositions for paints, varnishes, printing inks, grinding resins, pigment concentrates or other coating substances for the purpose of producing and examining the selected test composition; training the convolutional neural network, using the selected test composition and the properties thereof detected by the apparatus; generating a prediction composition for paints, varnishes, printing inks, grinding resins, pigment concentrates or other coating substances by inputting an input vector into the convolutional neural network; and outputting the pre

Abstract: The invention relates to a laboratory system including at least one laboratory device which is designed to analyse and/or synthesise a chemical substance; at least one laboratory software module which is designed to process data obtained from the at least one laboratory device; a data processing device with control software that provides an interface for operating the at least one laboratory device and/or the at least one laboratory software module; and a portable device with a microphone, wherein the device is connected interoperably to the control software via a network, wherein the device is designed, in interoperation with the control software, to allow a user to operate the at least one laboratory device and/or the at least one laboratory software module without manual intervention, by speaking into the microphone.

Abstract: The method includes inputting a specification of a desired combination of a first component and a second component of a composition, wherein the components are a solid and a dispersant, via a user interface of a computer system; carrying out a database query with the desired combination of the first component and the second component as the search criterion, wherein in the case where the database query supplies a known composition that meets the search criterion, the known composition is output, wherein in the opposite case, a further database query of a composition including the first component and the second component, serving as the search criterion, is carried out to find a candidate composition that includes one of the two components as well as a substitute component instead of the other component; and carrying out further steps for generating the formulation and outputting the composition.

Abstract: The invention relates to a method for providing a coating composition-related prediction program, the method comprising: providing a database (204, 904) comprising associations of qualitative and/or quantitative characterizations of coating surfaces and one or more parameters; training a machine learning model for providing a predictive model (M2, M3) having learned to correlate qualitative and/or quantitative characterizations of one or more coating surfaces with one or more of the parameters; and providing a composition-quality-prediction program configured for using the predictive model (M2) for predicting the properties of a coating surface to be produced from one or more input parameters; and/or providing a composition-specification-prediction program configured for using the predictive model (M3) for predicting, based on an input specifying at least a desired coating surface characterization, one or more output parameters related to a coating composition predicted to generate a coating surface having

Abstract: A method for qualitative and/or quantitative characterization of a coating surface is provided, comprising: providing a program recognizing coating surface defect types; determining, by the program, whether a camera(s) coupled to the program is within a predefined distance range and/or within a predefined image acquisition angle range relative to a currently presented coating surface; depending on the determination: generating a feedback signal indicative of whether adjustment of the position of the camera(s) is within predefined distance range and/or within the predefined image acquisition angle range, and/or automatically adjusting the relative distance of the camera and and/or automatically adjusting the angle of the camera; enabling the camera to acquire an image of the coating surface only when the camera(s) is/are within the predefined distance range and/or image acquisition angle range; processing the digital image for recognizing coating surface defects; and outputting a characterization of the

Abstract: A method for detecting a phase separation of a waterborne or solvent-borne or solvent-free coating composition includes providing the coating composition in a receptacle; providing a measurement instrument for receiving the receptacle, the measurement instrument including a measurement probe; controlling the measurement instrument to a) displace the measurement probe through the coating composition along a predefined measurement path with a predefined speed profile, the predefined measurement path extending along a length axis of the receptacle, b) acquire a force-displacement profile by measuring a force exercised on the measurement probe while the probe is being displaced along the predefined measurement path with the predefined speed profile; processing the force-displacement profile for detecting at least one phase separation of the coating composition; and outputting a detection result.