What is a recommendation system

Recommendation engines are a subclass of machine learning which generally deal with ranking or rating products/users. Recommender systems are algorithms aim at suggesting relevant items to users. They have been widely applied by many big name companies like Youtube, Amazon, Netflix and others to increase the engagement with users and the platform. Recommendation systems are employed since they can generate more profit when companies use efficient systems and help them stand out from competitors. There are many real life examples, YouTube uses recommendations to suggest you other videos similar to the ones you liked or... read more

Overview

The origin of cluster expansions can be traced back to the early 1950s, when Kikuchi developed an Ising model-based cluster variation method to study order-disorder phenomena. In 1984, Sanchez et al. developed a general formalism for the description of configurational cluster expansions in terms of a complete basis set expansion. In simple terms, CE decomposes the energy of a configuration into one-body, two-body, and higher-order interaction terms (‘clusters’), and each term has a corresponding weight called effective cluster interaction (ECI) analogous to the interaction strength. The energy can be exactly reproduced only if all clusters are included in the... read more

Introduction

Electrochemical reduction of CO₂ has attracted researchers’ attention as it has the potential to utilize the abundant greenhouse gas in the Earth’s atmosphere and store intermittent energy from solar panels and wind turbines in chemical bonds. Many metals show activities in reducing CO₂ in aqueous phase. However, with the competition of the hydrogen evolution reaction, the selectivity is poor towards valued chemicals. Also, the high overpotential needed to drive the reactions causes low efficiencies that inhibits the practical applications.

CO₂ cycle

Many metals show CO2₂ reduction activity

Current Knowledge and Focus

By using Bismuth... read more