Process design optimization strategy to develop energy and cost correlations of CO2 capture processes

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Power exhaust is a crucial issue for future fusion reactors. Divertor detachment and the required power dissipation fractions of about 95% are foreseen to be achieved by impurity seeding. In a tokamak, at high seeding levels the radiation often concentrate ...

The production of aluminium largely depends on the use of fossil fuels, resulting in the emission of significant amounts of greenhouse gases. As the aluminium industry is working towards decreasing its environmental burdens, the elimination of direct emiss ...

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 ...

Renewable energy sources offer a promising solution for mitigating sustainability and CO2 emissions-related issues due to their vast energy generation capacity. They enable hydrogen production via water electrolysis, as well as carbon capture and utilizati ...

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 ...

We report the detailed background for the discovery and development of the synthesis of homopropargylic azides by the azidoalkynylation of alkenes. Initially, a strategy involving SOMOphilic alkynes was adopted, but only resulted in a 29% yield of the desi ...

Membranes based on a porous two-dimensional selective layer offer the potential to achieve exceptional performance to improve energy efficiency and reduce the cost for carbon capture. So far, separation from two-dimensional pores has exploited differences ...

The aluminium sector relies on natural gas for the conversion of recycled scrap into new feedstock, which results in substantial atmospheric emissions. Hydric resources are also impacted, as they serve as heat sinks for the waste heat generated during the ...

This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a hig ...

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 ...

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 ...

Industrial chemistry heavily relies on traditional separation methods which are both energy-demanding and environmentally detrimental. This thesis addresses critical separation challenges, specifically carbon capture applications and the separation of ethy ...

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 ...

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

Solar photovoltaics (PV) is one of the most competitive renewable energy technologies in order to meet the increasing global energy demand and decrease CO2 emissions by competing effectively with fossil fuels. One of the important applications of PV energy ...

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

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 ...

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 ...

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 ...

Process design optimization strategy to develop energy and cost correlations of CO2 capture processes

Chattez avec Graph Search

X-point radiation: From discovery to potential application in a future reactor

CO2 Capture and Management Strategies for Decarbonizing Secondary Aluminium Production

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

Tailoring nanocatalysts and reaction interfaces for water- and CO2-electrolysis

Scalable constrained optimization

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

Graphene membranes with pyridinic nitrogen at pore edges for high-performance CO2 capture

Renewable energy integration and waste heat valorization in aluminum remelting for co-producing kerosene and methanol

Deep learning-based recommendation system for metal-organic frameworks (MOFs)

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

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

Harnessing Porous Materials for Efficient Gas Capture: A Computational Exploration of Structure, Function, and Workflow Automation

Efficient and insightful descriptors for representing molecular and material space

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Reliability and Long-term Performance of Building Integrated Photovoltaic (BIPV) Modules

A diversity-driven discovery of potential nanoporous materials for energy-related applications

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

Modeling and optimization of PCB coils for inductive power transfer systems

Robot Learning using Tensor Networks