Abstract: A dissolution determination apparatus and an operating method thereof are provided. The dissolution determination apparatus may include: a dissolution determination apparatus may include: a reader configured to read identification information of a container that accommodates a target sample; a driving module including at least one body, the at least one body of the driving module configured to open the container and move the container to a capturing position; an image obtaining module configured to obtain, at the capturing position, at least one image of the target sample while the container is open; and at least one processor configured to automatically determine whether the target sample is dissolved by analyzing the at least one image of the target sample based on the identification information of the container.

Abstract: A system for formulating a semiconductor material includes a dispenser configured to dispense a target sample for the semiconductor material into a vial tray based on a formulation ratio, an agitator configured to perform a dissolution of the target sample, a solubility measurement device configured to determine whether the target sample is dissolved, and a controller configured to obtain a solubility of the target sample from the solubility measurement device and control the agitator based on the solubility.

Abstract: A neural network apparatus for generating a new chemical structure may receive a structure input of a chemical structure; generate, based on the structure input, a negative attention vector that indicates a respective probability of presence of each of a plurality of blacklists in the structure input; generate a structure expression by encoding the structure input; generate a final reverse blacklist vector that does not include the plurality of blacklists, based on the negative attention vector and the structure expression; and generate the new chemical structure by decoding the final reverse blacklist vector.

Abstract: A material synthesis apparatus includes: at least one device configured to synthesize a material; a user interface configured to obtain information on a target product; and a processor, wherein the processor is configured to: determine synthesis conditions for preparing the target product using a pretrained synthesis prediction model; calculate a first synthesis method for preparing the target product based on the synthesis conditions; and control the at least one device based on the first synthesis method.

Abstract: A material synthesis apparatus includes: at least one device configured to synthesize a material; a user interface configured to obtain information on a target product; and a processor, wherein the processor is configured to: determine synthesis conditions for preparing the target product using a pretrained synthesis prediction model; calculate a first synthesis method for preparing the target product based on the synthesis conditions; and control the at least one device based on the first synthesis method.

Abstract: A method performed by at least one processor, includes receiving a query comprising at least one of a product, a reactant, a reagent, and a reaction condition; generating a query embedding vector corresponding to the query by inputting the query into a neural network model; extracting a candidate embedding vector from among a plurality of embedding vectors based on a similarity between the query embedding vector and the plurality of embedding vectors corresponding to reaction records stored in a database; and outputting a synthesis recipe corresponding to the query by retrieving a candidate reaction record corresponding to the candidate embedding vector in the database.

Abstract: An apparatus for generating a target product by using a neural network is configured to: predict candidate reactant combinations for generating the target product by using a pre-trained retrosynthesis prediction model; predict a prediction product with respect to each of the candidate reactant combinations by using a pre-trained reaction prediction model; and determine an experimental priority order of the candidate reactant combinations based on a result of comparing the target product with the prediction product.

Abstract: A method of optimizing synthetic conditions includes receiving a graph-type descriptor comprising at least one of structural information of at least one reactant and structural information of a target product to be synthesized by the reactant; determining combinations of synthetic conditions for generating the target product by applying the graph-type descriptor to a prediction neural network model; selecting at least one initial condition combination from among the combinations based on a first confidence corresponding to a yield of the combinations; updating the prediction neural network model based on a ground-truth yield obtained from a result of an experiment with the initial condition combination; determining a priority of the combinations based on the updated prediction neural network model; and determining subsequent combinations of synthetic conditions based on the determined priority.

Abstract: An automated material reaction system includes a material storage, which stores store at least one material, a dispensing module, which dispenses, to a reaction container, the at least one material stored in the material storage, a reaction module, which causes a reaction of the at least one material dispensed to the reaction container, a purification module, which extracts a target product from a product produced by the reaction module and purifies the target product, and a transport device, which transports the target product to the dispensing module such that the target product is used as a reactant.

Abstract: An optical monitoring device includes: a heating stirrer configured to generate at least one of thermal energy and vibration energy; a jig disposed on the heating stirrer and configured to fix, relative to the optical monitoring device, at least one of a container and a conduit; a light source arranged to emit light toward the at least one of the container and the conduit; a camera arranged and configured to obtain an image of the at least one of the container and the conduit; and an adjuster configured to adjust at least one of a position and an orientation of at least one of the light source and the camera.

Abstract: Provided are a condensed cyclic compound, an organic light-emitting device including the condensed cyclic compound, and an electronic device including the organic light-emitting device. The condensed cyclic compound is represented by Formula 1, wherein R12 is a group represented by Formula 2-1 and R13 is a group represented by Formula 2-2.

Abstract: Provided is a method of training a prediction model, the method including obtaining molecular descriptors of molecules based on a molecular database, pre-training a pre-training neural network based on the molecular descriptors, and adjusting the pre-training neural network such that the pre-training neural network matches a target task, by applying a training data set labeled corresponding to the target task to the pre-trained pre-training neural network.

Abstract: A sealing structure may include a lid including a first lid face, a second lid face opposite to the first lid face, and a fragile area between the first lid face and the second lid face, a cover including a first cover face facing the second lid face and covering the fragile area and a second cover face opposite to the first cover face, wherein a first distance between the second lid face and the first cover face is substantially equal to or less than a second distance between the first cover face and the second cover face, and a connector configured to connect the lid and the cover.

Abstract: A sealing structure may include a lid including a first lid face, a second lid face opposite to the first lid face, and a fragile area between the first lid face and the second lid face, a cover including a first cover face facing the second lid face and covering the fragile area and a second cover face opposite to the first cover face, wherein a first distance between the second lid face and the first cover face is substantially equal to or less than a second distance between the first cover face and the second cover face, and a connector configured to connect the lid and the cover.

Abstract: A heat exchanger is provided. The heat exchanger includes a target area that is a target for heat exchange; and a flow path structure. The flow path structure includes at least one inlet; at least one outlet; a first flow path connected to each of the at least one inlet and the at least one outlet, and extending along a first side of the target area; and a second flow path connected to each of the at least one inlet and the at least one outlet, and extending along a second side, different from the first side, of the target area.

Abstract: Disclosed are a compound represented by Chemical Formula 1, a film, a photoelectric diode, an organic sensor, and an electronic device. In Chemical Formula 1, Ar1 and Ar2, Z, L1, L2, and R1 to R6 are the same as defined in the detailed description.

Abstract: A method and apparatus for generating a new chemical structure using a chemical structure generation model are provided. The method includes receiving a first descriptor of a first chemical structure, encoding the first descriptor into a latent variable using an encoder of the chemical structure generation model, generating a second descriptor by decoding the latent variable using a decoder of the chemical structure generation model, generating the second chemical structure corresponding to the second descriptor.

Abstract: A method of predicting a synthetic path may include: receiving a target molecule descriptor corresponding to a target material, predicting one or more synthetic path descriptor candidates representing multi-step synthetic paths corresponding to the target molecule descriptor using a neural network-based predictive model, the neural network-based predictive model being trained based on a synthetic path descriptor in a form of a character string obtained by converting multi-step synthetic path data; and outputting the one or more synthetic path descriptor candidates.

Abstract: Generating a new chemical structure by using a neural network using an expression region that expresses a particular property in a descriptor or an image for a reference chemical structure. The new chemical structure may be generated by changing a partial structure in the reference chemical structure that corresponds to the expression region.

Abstract: An apparatus for optimizing experimental conditions by using a neural network may calculate a prediction yield and accuracy of the prediction yield by using a neural network-based experimental prediction model. The apparatus may optimize the experimental conditions by determining an experiment priority of a respective experiment condition combination based on the prediction yield and the prediction accuracy and receiving a feedback of results of experiments performed according to the experiment priority.