Synthesis parameter effect detection using quantitative representations and high dimensional distribution distances

TL;DR

This paper introduces a novel method combining copula theory, high-dimensional distribution distances, and permutation tests to detect synthesis parameter effects on material microstructure, validated on plutonium oxide synthesis.

Contribution

It presents a new analytical approach for effect detection in materials synthesis experiments using advanced statistical techniques.

Findings

Detected effects of strike order and oxalic acid feed on microstructure

Identified bivariate effects between acid concentration, strike order, and temperature

Results align with existing literature

Abstract

Detection of effects of the parameters of the synthetic process on the microstructure of materials is an important, yet elusive goal of materials science. We develop a method for detecting effects based on copula theory, high dimensional distribution distances, and permutational statistics to analyze a designed experiment synthesizing plutonium oxide from Pu(III) Oxalate. We detect effects of strike order and oxalic acid feed on the microstructure of the resulting plutonium oxide, which match the literature well. We also detect excess bivariate effects between the pairs of acid concentration, strike order and precipitation temperature.