Abstract:
Beschrieben wird ein strahlungsvernetzbarer Schmelzklebstoff, enthaltend mindestens ein strahlungsvernetzbares Poly(meth)acrylat, welches zu mindestens 60 Gew.% aus C1- bis C10- Alkyl(meth)acrylaten gebildet ist und mindestens ein Oligo(meth)acrylat, welches nicht-acrylische C-C-Doppelbindungen enthält und einen K-Wert von kleiner oder gleich 20 aufweist. Der Schmelzklebstoff enthält einen Fotoinitiator, welcher als nicht an das Poly(meth)acrylat oder und nicht das Oligo(meth)acrylat gebundenes Additiv vorliegen kann, in das Poly(meth)acrylat einpolymerisiert sein kann und/oder an das Oligo(meth)acrylat gebunden sein kann. Der Schmelzklebstoff kann zur Herstellung von Klebebändern verwendet werden.
Abstract:
Beschrieben wird eine Haftklebstoffdispersion, enthaltend ein in Wasser dispergiertes, durch Emulsionspolymerisation gebildetes Polymer P1. Das Polymer P1 ist gebildet aus einem Monomergemisch, enthaltend (a) mindestens 40 Gew.% C4 bis C20 Alkyl(meth)acrylate, welche, wenn sie als Homopolymere polymehsiert sind, eine Glasübergangstemperatur von -30 °C oder weniger aufweisen, (b) mindestens 0,05 Gew.% (Meth)acrylatmonomere mit einem Substituenten der Formel wobei X für CH 2 , O, NH oder NR steht und R für eine C1 bis C4-Alkylgruppe steht, (c) mindestens 0,1 Gew.% Säuremonomere. Das Polymer P1 ist durch Polymerisation in mindestens 2 Stufen hergestellt, wobei die Glasübergangstemperatur eines Polymers aus Monomeren der ersten Stufe um mindestens 20 °C niedriger liegt als die Glasübergangstemperatur eines Polymeren aus Monomeren einer späteren, zweiten Stufe.
Abstract:
The present teachings relate to a method comprising a plurality of sensors, and one or more functionally connected processing units, the method comprising: providing, at any of the one or more processing units, time-series residual data of a sensor object; the sensor object being a group of at least some of the sensors from the plurality of sensors, and wherein the residual data comprises, for each of the sensors of the sensor object, a residue signal which is a difference between the sensor's measured output and the sensor's expected output, monitoring, via any of the one or more processing units, a level signal; wherein the level signal is indicative of a collective time-based variation of the time-series residual data, monitoring, via any of the one or more processing units, an association signal; wherein the association signal is indicative of the variation and/or association structure of the time-series residual data, generating, via any of the one or more processing units, an anomaly event signal when at a given time a value of the level signal and/or a value of the association signal changes from an expected value of the respective signal at or around that time. The present teachings also relate to a monitoring and/or control system for a plant comprising a plurality of sensors, wherein the system comprises one or more processing units configured to perform the method steps of any of the steps herein disclosed, and a computer software product.
Abstract:
The present invention relates to a hardenable polymer composition containing at least one acrylate compound, at least one silyl-terminated polymer and at least one photoinitiator, to the use of the polymer composition as or in an adhesive, a sealant, gasket, knifing filler or coating composition, and to an adhesive composition, a sealant composition, a gasket composition, a knifing filler composition or a coating composition comprising the polymer composition.
Abstract:
The present invention generally relates to digital farming. In order to facilitate the provision of sensor data with a high spatial coverage, a computer-implemented method (100) is provided for training a data-driven model for measuring a concentration of a physicochemical parameter from a target field, the method comprising: a) providing (110) historical satellite imagery data collected from at least one field over a period of time; b) providing (120) historical sensor data collected from the at least one field, wherein the historical sensor data provides a measurement or an estimation of the concentration of the physicochemical parameter over the period of time; and c) training (130) the data-driven model with a training dataset based on the provided historical satellite imagery data and the historical sensor data, wherein the trained data-driven model is usable as a soft-sensor for measuring a concentration of the physicochemical parameter from the target field based on satellite imagery data acquired from the target field.
Abstract:
The invention relates to a contact adhesive dispersion, containing a polymer P1 which can be dispersed in water and is formed by emulsion polymerization. The polymer P1 is formed from a monomer mixture, containing (a) at least 40% by weight C4 to C20 alkyl(meth)acrylates which have a glass transition temperature of -30ºC or less if they are polymerized as homopolymers, (b) at least 0.05% by weight (meth)acrylate monomers containing a substituent of the formula, where X denotes CH 2 , O, NH or NR and R denotes a C1 to C4 alkyl group, and (c) at least 0.1% by weight acid monomers. The polymer P1 is produced by means of polymerization in at least two stages, wherein the glass transition temperature of a polymer made of monomers of the first stage is at least 20ºC lower than the glass transition temperature of a polymer made of monomers of a later, second stage.