SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

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Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

The auxiliary power supply for medium voltage converters requires high insulation capability between the source and the load. Inductive power transfer technology, with an air gap between the primary and secondary coil, offers such high insulation capabilit ...

Atomic layer deposition (ALD) is one of the premier methods to synthesize ultra-thin materials on complex surfaces. The technique allows for precise control of the thickness down to single atomic layers, while at the same time providing uniform coverage ev ...

Sensing and imaging of light in the shortwave infrared (SWIR) range is increasingly used in various fields, including bio-imaging, remote sensing, and semiconductor process control. SWIR-sensitive organic photodetectors (OPDs) are promising because organic ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...

Artificial Intelligence (AI) techniques are considered the most advanced approaches for diagnosing faults in power transformers. Dissolved Gas Analysis (DGA) is the conventional approach widely adopted for diagnosing incipient faults in power transformers. ...

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

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Scalable constrained optimization

Mesh-based topology, shape and sizing optimization of ribbed plates

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Robot Learning using Tensor Networks

Efficient and insightful descriptors for representing molecular and material space

Modeling and optimization of PCB coils for inductive power transfer systems

Optimizing Atomic Layer Deposition Processes with Nanowire-Assisted TEM Analysis

Shortwave Infrared-Sensitive, Narrowband Organic Upconversion Devices with a Gain

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Adaptive projected variational quantum dynamics

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

Power Transformer Fault Diagnosis Using Neural Network Optimization Techniques

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

Computational conceptual design — typological exploration of spatial truss systems through optimization

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming