Abstract: A method, computer system, and a computer program product are provided. A neural network that includes multiple layers and multiple nodes in each layer is trained with training data. The nodes are sparsely connected to each other and not fully connected. After the training occurs for one or more epochs, a respective flow rate of the multiple nodes is determined. The flow rate indicates a probability that information flows through the respective layer through a respective node of that respective layer. A number of bits used for weights of the nodes is scaled based on the determined flow rates. A larger number of bits is used for the nodes with a larger information flow and a smaller number of bits is used for the nodes with a smaller information flow. Additional training of the neural network is performed using the respective scaled number of bits for the multiple nodes.

Abstract: Systems, methods, and computer program products for adaptive node removal during training of an artificial neural network are described herein. A method comprises normalizing each weight of an artificial neural network; determining an entropy value for each node in the artificial neural network based on the weights of that node's connections; identifying a set of candidate nodes, the candidate nodes having the highest entropy value of their respective layers; selecting a subset of the set of candidate nodes; and removing, from the artificial neural network, each candidate node of the subset.

Abstract: A semiconductor device includes a plurality of seed structures disposed in a dielectric layer. The plurality of seed structures are spaced apart from each other. Respective ones of the plurality of seed structures have a tapered shape with a decreasing width from an upper surface of the dielectric layer, and include semiconductor crystalline material.

Abstract: A process includes providing a reactor containing a compound of the formula SiOx, wherein 0?x?2, and receiving, at the reactor, fluorinated gas. The process also includes obtaining a gaseous mixture formed at an elevated temperature in the reactor and removing silicon tetrafluoride from the gaseous mixture. An apparatus includes a reactor containing a compound of the formula SiOx, wherein 0?x?2, a component for receiving fluorinated gas at the reactor, a heating element for heating the compound of the formula SiOx and the fluorinated gas in the reactor, and a separation component for removing silicon tetrafluoride from a gaseous mixture formed in the reactor. A process of semiconductor manufacturing includes defluorinating exhaust gas using the process. A system for semiconductor manufacturing includes a set of components for carrying out the process.

Abstract: A method, system, and computer program product are disclosed. The method includes generating simulation instances and particle site identifiers from a particle-based simulation. The method also includes providing an order metric for the particle-based simulation. Information is embedded in the particle-based simulation by mapping local order values of the order metric to characters of an input message.

Abstract: Aspects of the disclosure include a method for separating selected ions in water, a purified water sample, and a controller for a high pressure press. One embodiment of the method may comprise transforming a sample of water into a plastic ice VII block and physically separating a bottom portion of the plastic ice VII block from a top portion of the plastic ice VII block.

Abstract: A data set is received for training a machine learning model to perform a recognition task. Optimization is performed during training of the machine learning model. The optimization includes at least searching for a minimum value of a loss function, responsive to finding a local minimum, adding an additional term to the loss function, continuing to find another local minimum until a criterion is met, and identifying a global minimum having the lowest minimum value among the found local minima. The machine learning model can be updated with parameters identified at the global minimum.

Abstract: The present inventive concept provides for a method of microfluid cooling for a non-uniform heatmap. The method includes identifying a plurality of zones of a microelectronic device. A local temperature measurement is obtained for one or more zones of the plurality of zones of the microelectronic device. A voltage is applied to a microfluid in at least a portion of the one or more zones based on the obtained local temperature measurement.

Abstract: A system may include a chamber with a main sub-chamber and a first porous membrane separating a first sub-chamber from the main sub-chamber. The system may include a fluid in the chamber and an input directing inflow into main sub-chamber proximate an entry end of the chamber. The system may include a first output permitting outflow from the first sub-chamber proximate an exit end of the chamber wherein a molecule entering at the entry end must traverse a length of the chamber to exit at the exit end.

Abstract: A system may include a chamber with a main sub-chamber and a first porous membrane separating a first sub-chamber from the main sub-chamber. The system may include a fluid in the chamber and an input directing inflow into main sub-chamber proximate an entry end of the chamber. The system may include a first output permitting outflow from the first sub-chamber proximate an exit end of the chamber wherein a molecule entering at the entry end must traverse a length of the chamber to exit at the exit end.

Abstract: A sparse topology for a feedforward neural network is generated, where connectivity is based on a substantially hyperuniform topology. The feedforward neural network with the sparse topology is trained using a set of training data and a processing task is performed using the trained feedforward neural network.

Abstract: A gas capture system is configured to purify gas streams. The gas capture system includes a first capture system including a plurality of first chambers interconnected by a first path. Each first chamber includes a first adsorbent. The gas capture system further includes a second capture system including a plurality of second chambers interconnected by a second path. Each second chamber includes a second adsorbent. The gas capture system further includes a third path connecting each first chamber to the second path such that a first output of the first capture system is input into the second capture system. The gas capture system further includes a fourth path connecting each second chamber to the first path such that a second output of the second capture system is input into the first capture system.

Abstract: A gas capture system is configured to purify gas streams. The gas capture system includes a first capture system including a plurality of first chambers interconnected by a first path. Each first chamber includes a first adsorbent. The gas capture system further includes a second capture system including a plurality of second chambers interconnected by a second path. Each second chamber includes a second adsorbent. The gas capture system further includes a third path connecting each first chamber to the second path such that a first output of the first capture system is input into the second capture system. The gas capture system further includes a fourth path connecting each second chamber to the first path such that a second output of the second capture system is input into the first capture system.

Abstract: A method, system, and computer program product are disclosed. The method includes generating simulation instances and particle site identifiers from a particle-based simulation. The method also includes providing an order metric for the particle-based simulation. Information is embedded in the particle-based simulation by mapping local order values of the order metric to characters of an input message.

Abstract: Optimizing a processes for the manufacture of amorphous silicon by generating molecular dynamics simulations of amorphous silicon across a range of manufacturing conditions, applying a local order metric algorithm to each of the simulations to detect formation of crystalline structures within each of the simulations based on a local order metric determined by the algorithm, determining material quality for each simulation as a function of the local order metric and the detected crystalline structures, modifying manufacturing conditions according to a desired material quality and applying the modified manufacturing conditions to the manufacturing process of amorphous silicon.

Abstract: A material screening process of generating input features for each material of a subset of materials to be screened, generating target properties for each material of the subset of materials, inputting screening conditions, the input features, and the target properties into a material screening artificial intelligence model and training the material screening artificial intelligence model based on the inputs. Once the model is trained, inputting a dataset of materials to be screened into the trained material screening artificial intelligence model, the dataset of materials includes the subset of materials used to train the model, screening the dataset of materials on the trained material screening artificial intelligence model using the screening conditions and ranking the materials of the dataset based on predicted target properties obtained from the screening.

Abstract: A system may include a chamber with a main sub-chamber and a first porous membrane separating a first sub-chamber from the main sub-chamber. The system may include a fluid in the chamber and an input directing inflow into main sub-chamber proximate an entry end of the chamber. The system may include a first output permitting outflow from the first sub-chamber proximate an exit end of the chamber wherein a molecule entering at the entry end must traverse a length of the chamber to exit at the exit end.