Abstract: A method for executing multiple chemical experiments in parallel may be provided. The method comprises receiving a list of actions to be performed for synthesizing a chemical product. Thereby, the actions correspond to at least two chemical partial reactions and the list comprises a delimiter symbol separating two chemical partial reactions, determining identical chemical partial reactions, and building a reaction commonality tree (RCT) of the chemical reactions. Furthermore, the method comprises executing a plurality of the identical chemical partial reactions independent of a sequence of chemical partial reactions of the reaction commonality tree only once. Each of the identical chemical partial reactions is executed in a different chemical reactor and each resulting intermediate product has a quantity of the sum of the related identical chemical partial reactions.

Abstract: Disclosed is a method for predicting at least one aspect of an enzymatically catalyzed chemical reaction. The method comprises providing a trained machine learning model, and inputting one or two input strings into the training model. Each input string is selected from a group of strings consisting of: a string representation of at least one educts of the chemical reaction, a string representation of at least one product of the chemical reaction, and/or a string representation of amino acids of an enzyme which is supposed to transform the educts into the products in the reaction. The trained machine learning model predicts at least the one or more strings which were not provided as input and the prediction is performed as a function of the one or two strings provided as input. The method outputting the prediction result for predicting or optimizing the chemical reaction.

Abstract: A computer-implemented method for generating an organic synthesis procedure from a simplified molecular-input line-entry system (SMILES) string may be provided. The method includes receiving a plurality of SMILES strings describing a desired chemical product and required reactants, and predicting procedure steps for an organic synthesis procedure for producing the desired chemical product by a deep machine-learning model system trained with sets of SMILES strings describing respective desired chemical products, reactants and related procedure steps as training data. The sets can be extracted from a corpus of associated chemical documents, and the predicted procedure steps are human readable. The method includes further receiving a modification signal for a modification to the predicting procedure steps, storing the plurality of received SMILES strings, the predicted procedure steps and the modification of the predicting procedure steps.

Abstract: A method for executing multiple chemical programs in parallel in an array of chemical reactors using a single array of substance containers may be provided. The method includes receiving a plurality of chemical programs, building a plurality of records comprising each a chemical program. Thereby, each record includes a key and a data field, wherein the key is indicative of the reactants required for the respective chemical reaction, and wherein the data field includes the chemical program. The method further includes creating an ordered data structure of the data records based on the keys, selecting a next record from the ordered data structure, assigning the selected next record to selected ones of the array of chemical reactors, repeating the steps of selecting and assigning until, as a maximum, each chemical reactor has a defined record assigned to it, and executing the chemical programs according to their defined records in parallel.

Abstract: A method for executing multiple chemical experiments in parallel may be provided. The method comprises receiving a list of actions to be performed for synthesizing a chemical product. Thereby, the actions correspond to at least two chemical partial reactions and the list comprises a delimiter symbol separating two chemical partial reactions, determining identical chemical partial reactions, and building a reaction commonality tree (RCT) of the chemical reactions. Furthermore, the method comprises executing a plurality of the identical chemical partial reactions independent of a sequence of chemical partial reactions of the reaction commonality tree only once. Each of the identical chemical partial reactions is executed in a different chemical reactor and each resulting intermediate product has a quantity of the sum of the related identical chemical partial reactions.

Abstract: A computer-implemented method of performing class-dependent, machine learning based inferences includes accessing a test input and N class identifiers, wherein each class identifier of the N class identifiers identifies a respective class among M possible classes; forming N test input data structures, wherein each test input data structure of the N test input data structures is formed by aggregating the test input with a different one of the N class identifiers; performing an inference for each of the N test input data structures using a machine learning model that is trained using examples associating example input data structures with respective example outputs, wherein each respective example input data structure is formed by aggregating an example input with a different one of the N class identifiers; and returning a class-dependent inference result for each respective test input data structure based on the inference obtained for each respective test input data structure.

Abstract: Electrochemical energy storage devices are provided comprising an anode, a cathode and a solid-state electrolyte adapted for Na-ion conduction between the anode and cathode. The solid-state electrolyte includes, for example, a solid solution of doped NaAlO2 having a composition defined by one of Dx(NaAlO2)1-x in which D is at least one of GeO2, SnO2, TiO2, ZrO2 and HfO2, and Dx/2(NaAlO2)1-x in which D is PAlO4, where 0<x?0.5. Other solid-state electrolyte compositions are also disclosed.

Abstract: An electrochemical energy storage device is provided. The device may include a solid-state anode layer. The device may comprise a solid-state electrolyte layer. Further, the device may comprise a solid-state cathode layer. At least two adjacent ones out of the solid-state anode layer, the solid-state electrolyte layer, and the solid-state cathode layer may form a solid-state single-crystal with varying chemical compositions between the related layers. The solid-state electrolyte layer may have an ionic conductivity at room temperature higher than 10?6 S/cm.

Abstract: Querying a knowledge graph database in which entity data characterizes entities represented by nodes, interconnected by edges, of a knowledge graph, and each edge represents one of a set of relationships between entities which is applicable to the entities represented by nodes interconnected by that edge. A graphical user interface for display by a user computer enables definition, in response to user input, of an atomic query which is associated with a floating graphical query object in the interface. The atomic query defines an input set of said nodes for the query, a relationship and an output set of nodes for the query. Graphical connector and graphical logical-operator objects in the interface are manipulatable by a user in relation to a plurality of the query objects to define a complex query by constructing a graphical representation of a desired logical combination of the query objects.

Abstract: An electrochemical energy storage device is provided. The device may include a solid-state anode layer. The device may comprise a solid-state electrolyte layer. Further, the device may comprise a solid-state cathode layer. At least two adjacent ones out of the solid-state anode layer, the solid-state electrolyte layer, and the solid-state cathode layer may form a solid-state single-crystal with varying chemical compositions between the related layers. The solid-state electrolyte layer may have an ionic conductivity at room temperature higher than 10?6 S/cm.

Abstract: Electrochemical energy storage devices are provided comprising an anode, a cathode and a solid-state electrolyte adapted for Na-ion conduction between the anode and cathode. The solid-state electrolyte includes, for example, a solid solution of doped NaAlO2 having a composition defined by one of Dx(NaAlO2)1-x in which D is at least one of GeO2, SnO2, TiO2, ZrO2 and HfO2, and Dx/2(NaAlO2)1-x in which D is PAlO4, where 0<x?0.5. Other solid-state electrolyte compositions are also disclosed.

Abstract: Querying a knowledge graph database in which entity data characterizes entities represented by nodes, interconnected by edges, of a knowledge graph, and each edge represents one of a set of relationships between entities which is applicable to the entities represented by nodes interconnected by that edge. A graphical user interface for display by a user computer enables definition, in response to user input, of an atomic query which is associated with a floating graphical query object in the interface. The atomic query defines an input set of said nodes for the query, a relationship and an output set of nodes for the query. Graphical connector and graphical logical-operator objects in the interface are manipulatable by a user in relation to a plurality of the query objects to define a complex query by constructing a graphical representation of a desired logical combination of the query objects.

Abstract: A solid-state conductor with sodium oxoferrate structure is disclosed. The conductor may be used in battery applications where it is preferable to avoid the use of a liquid electrolyte. The conductor may be produced from an initial NaFeO2 chemical composition. So as to add defects and allow for sodium ion mobility, Fe(IV), Si, Sn, Ti, Zr, V, P, or S can be added. For example, (1?x)(NaFeO2)+x(XO2) can be melted with the corresponding oxide XO2, where X is Fe(IV), Si, Sn, Ti, Zr, V, P, or S, and x is between 0.1 and 0.5. These dopants generally preserve the crystallographic structure while decreasing the ion mobility barrier.

Abstract: A solid-state conductor with sodium oxoferrate structure is disclosed. The conductor may be used in battery applications where it is preferable to avoid the use of a liquid electrolyte. The conductor may be produced from an initial NaFeO2 chemical composition. So as to add defects and allow for sodium ion mobility, Fe(IV), Si, Sn, Ti, Zr, V, P, or S can be added. For example, (1-x)(NaFeO2)+x(XO2) can be melted with the corresponding oxide XO2, where X is Fe(IV), Si, Sn, Ti, Zr, V, P, or S, and x is between 0.1 and 0.5. These dopants generally preserve the crystallographic structure while decreasing the ion mobility barrier.

Abstract: A solid-state conductor with sodium oxoferrate structure is disclosed. The conductor may be used in battery applications where it is preferable to avoid the use of a liquid electrolyte. The conductor may be produced from an initial NaFeO2 chemical composition. So as to add defects and allow for sodium ion mobility, Fe(IV), Si, Sn, Ti, Zr, V, P, or S can be added. For example, (1?x)(NaFeO2)+x(XO2) can be melted with the corresponding oxide XO2, where X is Fe(IV), Si, Sn, Ti, Zr, V, P, or S, and x is between 0.1 and 0.5. These dopants generally preserve the crystallographic structure while decreasing the ion mobility barrier.

Abstract: A solid-state conductor with sodium oxoferrate structure is disclosed. The conductor may be used in battery applications where it is preferable to avoid the use of a liquid electrolyte. The conductor may be produced from an initial NaFeO2 chemical composition. So as to add defects and allow for sodium ion mobility, Fe(IV), Si, Sn, Ti, Zr, V, P, or S can be added. For example, (1?x)(NaFeO2)+x(XO2) can be melted with the corresponding oxide XO2, where X is Fe(IV), Si, Sn, Ti, Zr, V, P, or S, and x is between 0.1 and 0.5. These dopants generally preserve the crystallographic structure while decreasing the ion mobility barrier.

Abstract: Embodiments include performing sparse matrix-matrix multiplication. Aspects include receiving a first matrix and a second matrix, providing a pseudo-space for the first and second matrices, and defining pseudo-space segments and assigning the pseudo-space segments to certain processes. Aspects also include assigning matrix elements of the first and second matrix to pseudo-space segments using a midpoint method thereby assigning the matrix elements to processes associated with the pseudo-space segments, assigning a result matrix element of a result matrix to a pseudo-space segment using a midpoint method thereby assigning the result matrix element to a further process associated with the pseudo-space segment and transmitting matrix elements of the first and second matrix required to establish a result matrix element to the further process which processes the result matrix element.

Abstract: Embodiments include performing sparse matrix-matrix multiplication. Aspects include receiving a first matrix and a second matrix, providing a pseudo-space for the first and second matrices, and defining pseudo-space segments and assigning the pseudo-space segments to certain processes. Aspects also include assigning matrix elements of the first and second matrix to pseudo-space segments using a midpoint method thereby assigning the matrix elements to processes associated with the pseudo-space segments, assigning a result matrix element of a result matrix to a pseudo-space segment using a midpoint method thereby assigning the result matrix element to a further process associated with the pseudo-space segment and transmitting matrix elements of the first and second matrix required to establish a result matrix element to the further process which processes the result matrix element.