Comparative evaluation of catalyst materials using a binary choice model

TL;DR

This paper introduces a binary choice model to evaluate catalyst materials based on consumer preferences, balancing physical properties with market adoption factors to promote green material dissemination.

Contribution

It presents a novel binary choice model combining physical and economic factors to guide catalyst material design and policy for increased societal adoption.

Findings

Model predicts consumer choices based on turnover rates and prices.

Simulations show how pricing policies can influence market share.

Framework aids in balancing material properties with production costs.

Abstract

Advances in algorithms and hardware have enabled computers to design new materials atom-by-atom. However, in order for these computer-generated materials to truly address problems of societal importance, such as clean energy generation, it is not enough for them to have superior physical properties. It is also important for them to be adopted by as many users as possible. In this paper, we present a simple binary choice model for comparing catalyst materials on the basis of consumer preferences. This model considers a population of utility maximisers who select one of two materials by comparing catalytic turnover rates with sales prices. Through a mixture of numerical simulation and analytic theorems, we characterise the predictions of the model in a variety of regimes of consumer behavior. We also show how the model can be used as a guide for crafting policies for lowering catalyst prices in order to improve their market shares. This work represents a first step towards understanding how material properties should be balanced against production costs and consumer demand when designing new materials, an intellectual advance which may facilitate the spread of green materials in society.