Abstract: Methods of forming and processing semiconductor devices are described. Certain embodiments related to electronic devices which comprise a dipole region having an interlayer dielectric, a high-? dielectric material, and a dipole layer. The dipole layer comprises one or more of titanium aluminum nitride (TiAlN), titanium tantalum nitride (TiTaN), titanium oxide (TiO), tantalum oxide (TaO), and titanium aluminum carbide (TiAlC).

Abstract: Provided is a method and system for normalizing catalog item data to create higher quality search results. In one example, the method may include receiving a record comprising an unstructured description of an object, identifying a type of the object from among a plurality of object types and identifying a predefined attribute of the identified type of object, extracting a value from the unstructured description corresponding to the predefined attribute and modifying the extracted value to generate a normalized attribute value, and storing a structured record of the object in a structured format comprising a plurality of values of a plurality of attributes of the object from the unstructured description including the normalized attribute value for the predefined attribute of the object.

Abstract: Disclosed is a method of synthesizing a (1R,2R)-nitroalcohol compound of formula (I), as shown in the following reaction scheme, including: subjecting a compound of formula (II) and a compound of formula (III) to a condensation reaction in an organic solvent in the presence of a copper complex generated in situ from a chiral (1S,2R)-amino alcohol ligand and a cupric salt to produce the (1R,2R)-nitroalcohol compound of formula (I), where R1 and R2 are defined in the same manner as that in the specification. The method involves mild reaction conditions, excellent diastereoselectivity and high chemical yield, and thus it is suitable for industrial applications.

Abstract: Aspects of the invention include systems and methods configured to provide simplified and efficient artificial intelligence (AI) model deployment. A non-limiting example computer-implemented method includes receiving an AI model deployment input having pre-process code, inference model code, and post-process code. The pre-process code is converted to a pre-process graph. The inference model and the post-process model are similarly converted to an inference graph and a post-process graph, respectively. A pipeline path is generated by connecting nodes in the pre-process graph, the inference graph, and the post-process graph. The pipeline path is deployed as a service for inference.

Abstract: Methods for pre-cleaning substrates having metal and dielectric surfaces are described. The substrate is exposed to a strong reductant to remove contaminants from the metal surface and damage the dielectric surface. The substrate is then exposed to an oxidation process to repair the damage to the dielectric surface and oxidize the metal surface. The substrate is then exposed to a weak reductant to reduce the metal oxide to a pure metal surface without substantially affecting the dielectric surface. Processing tools and computer readable media for practicing the method are also described.

Abstract: Methods for pre-cleaning substrates having metal and dielectric surfaces are described. The substrate is exposed to a strong reductant to remove contaminants from the metal surface and damage the dielectric surface. The substrate is then exposed to an oxidation process to repair the damage to the dielectric surface and oxidize the metal surface. The substrate is then exposed to a weak reductant to reduce the metal oxide to a pure metal surface without substantially affecting the dielectric surface. Processing tools and computer readable media for practicing the method are also described.

Abstract: Multi-level objectives improve efficiency of multi-objective automated machine learning. A hyperband framework is established with a kernel density estimator to shrink the search space based on evaluation of lower-level objectives. A Gaussian prior assumption directly shrinks the search space to find a main objective.

Abstract: A model parallel training technique for neural architecture search including the following operations: (i) receiving a plurality of ML (machine learning) models that can be substantially interchangeably applied to a computing task; (ii) for each given ML model of the plurality of ML models: (a) determining how the given ML model should be split for model parallel processing operations, and (b) computing a model parallelism score (MPS) for the given ML model, with the MPS being based on an assumption that the split for the given ML model will be used at runtime; and (iii) selecting a selected ML model based, at least in part, on the MPS scores of the ML models of the plurality of ML models.

Abstract: A method for optimizing a neural network architecture by estimating an inference time for each operator in the neural network architecture is provided. The method may include determining a benchmark time for at least one single-path architecture out of a plurality of single-path architectures associated with the neural network by sampling the at least one single-path architecture from the neural network, wherein the at least one single-path architecture comprises one or more operators. The method may further include, based on the benchmark time for the at least one single-path architecture, determining an estimated inference time for an operator, wherein determining the estimated inference time for the operator comprises, applying an operator function, wherein the operator function comprises a function based on a difference between the benchmark time associated with the at least one single-path architecture and the estimated latency of the neural network.

Abstract: Methods of forming and processing semiconductor devices are described. Certain embodiments related to electronic devices which comprise a dipole region having an interlayer dielectric, a high-K dielectric material, and a dipole layer. The dipole layer comprises one or more of titanium aluminum nitride (TiAIN), titanium tantalum nitride (TiTaN), titanium oxide (TiO), tantalum oxide (TaO), and titanium aluminum carbide (TiAIC).

Abstract: Methods of forming and processing semiconductor devices are described. Certain embodiments related to electronic devices which comprise a dipole region having an interlayer dielectric, a high-? dielectric material, and a dipole layer. The dipole layer comprises one or more of titanium lanthanum nitride (TiLaN), titanium yttrium nitride (TiYN), titanium strontium nitride (TiSrN), titanium magnesium nitride (TiMgN, titanium aluminum nitride (TiAlN), titanium tantalum nitride (TiTaN), hafnium carbide (HfC), hafnium nitride (HfN), hafnium oxynitride (HfON), hafnium oxycarbide (HfOC), hafnium carbide aluminum (HfCAl), hafnium aluminum nitride (HfAlN), or hafnium carbonitride (HfCN).

Abstract: Methods of forming and processing semiconductor devices are described. Certain embodiments related to electronic devices which comprise a dipole region having an interlayer dielectric, a high-? dielectric material, and a dipole layer. The dipole layer comprises one or more of titanium aluminum nitride (TiAlN), titanium tantalum nitride (TiTaN), titanium oxide (TiO), tantalum oxide (TaO), and titanium aluminum carbide (TiAlC).

Abstract: Provided is a method and system for normalizing catalog item data to create higher quality search results. In one example, the method may include receiving a record comprising an unstructured description of an object, identifying a type of the object from among a plurality of object types and identifying a predefined attribute of the identified type of object, extracting a value from the unstructured description corresponding to the predefined attribute and modifying the extracted value to generate a normalized attribute value, and storing a structured record of the object in a structured format comprising a plurality of values of a plurality of attributes of the object from the unstructured description including the normalized attribute value for the predefined attribute of the object.

Abstract: Methods of forming and processing semiconductor devices are described. Certain embodiments related to electronic devices which comprise a dipole region having an interlayer dielectric, a high-? dielectric material, and a dipole layer. The dipole layer comprises one or more of titanium lanthanum nitride (TiLaN), titanium yttrium nitride (TiYN), titanium strontium nitride (TiSrN), titanium magnesium nitride (TiMgN, titanium aluminum nitride (TiAlN), titanium tantalum nitride (TiTaN), hafnium carbide (HfC), hafnium nitride (HfN), hafnium oxynitride (HfON), hafnium oxycarbide (HfOC), hafnium carbide aluminum (HfCAl), hafnium aluminum nitride (HfAlN), or hafnium carbonitride (HfCN).

Abstract: Aspects of the invention include systems and methods to obtain meta features of a dataset for training in a deep learning application. A method includes selecting an initial search space that defines a type of deep learning architecture representation that specifies hyperparameters for two or more neural network architectures. The method also includes applying a search strategy to the initial search space. One of the two or more neural network architectures are selected based on a result of an evaluation according to the search strategy. A new search space is generated with new hyperparameters using an evolutionary algorithm and a mutation type that defines one or more changes in the hyperparameters specified by the initial search space, and, based on the mutation type, the new hyperparameters are applied to the one of the two or more neural networks or the search strategy is applied to the new search space.

Abstract: Provided is a method and system for normalizing catalog item data to create higher quality search results. In one example, the method may include receiving a record comprising an unstructured description of an object, identifying a type of the object from among a plurality of object types and identifying a predefined attribute of the identified type of object, extracting a value from the unstructured description corresponding to the predefined attribute and modifying the extracted value to generate a normalized attribute value, and storing a structured record of the object in a structured format comprising a plurality of values of a plurality of attributes of the object from the unstructured description including the normalized attribute value for the predefined attribute of the object.

Abstract: Methods for pre-cleaning substrates having metal and dielectric surfaces are described. The substrate is exposed to a strong reductant to remove contaminants from the metal surface and damage the dielectric surface. The substrate is then exposed to an oxidation process to repair the damage to the dielectric surface and oxidize the metal surface. The substrate is then exposed to a weak reductant to reduce the metal oxide to a pure metal surface without substantially affecting the dielectric surface. Processing tools and computer readable media for practicing the method are also described.

Abstract: Methods and apparatus for forming a semiconductor structure such as an NMOS gate electrode are described. Methods may include depositing a first capping layer having a first surface atop a first surface of a high-k dielectric layer; and depositing at least one metal layer having a first surface atop the first surface of the first capping layer, wherein the at least one metal layer includes titanium aluminum silicide material. Some methods include removing an oxide layer from the first surface of the first capping layer by contacting the first capping layer with metal chloride in an amount sufficient to remove an oxide layer. Some methods for depositing a titanium aluminum silicide material are performed by an atomic layer deposition process performed at a temperature of 350 to 400 degrees Celsius.