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Page 4 of 21 Chen et al. J Mater Inf 2022;2:19 https://dx.doi.org/10.20517/jmi.2022.23

In this review, we summarize the current HT techniques on the synthesis, characterization and performance
testing used in the discovery of new HEA catalysts. Based on the achieved database, some ML models have
been developed to analyze the structure-activity relationships and predict the catalytic activity of HEA
catalysts for various catalytic reactions, such as the HER, OER/ORR, CO RR and ammonia decomposition
2
or synthesis. After an overview of the application of HT techniques and ML models in HEA catalysts, we
focus on the challenges, opportunities and prospects in the development of HEA catalysts.

HT RESEARCH FOR HEAS
HT techniques are essential for scientists to efficiently generate large databases and the subsequent
information extraction [33,34] . For HEAs with huge composition space, HT techniques can be used to great
[35]
effect for the discovery and development of HEAs . HT techniques make HEA research more automatic,
[36]
parallel and efficient . The application of HT techniques in the development of HEA catalysts is
summarized from two aspects, namely, HT theoretical calculations and HT experimental approaches.

HT theoretical calculations
With the rapid development of high-performance computing and theoretical calculation methods, HT
theoretical calculations have become more efficient in generating material databases compared to
[37]
experiments . Both DFT and semi-empirical calculations of phase diagrams (CALPHAD) have shown to
be viable and popular approaches for investigating the atomistic and thermodynamic mechanisms of
[38]
existing HEA systems, as well as for new HEA catalyst design .

The first step of a theoretical calculation is to build a HEA model, which is necessary for targeted and rapid
[39]
HEA discovery and application . Currently, the most widely used method to build HEA structures is the
special quasi-random structure (SQS) generation approach, which combines the cluster expansion
technique and Monte Carlo algorithms through several codes (ICET, ATAT, MCSQS and Supercell) [40-43] .
The designed SQSs can model disordered alloys with atomic resolution and the radial distribution function
[44]
of a random system is a quintessential concept for the generation of realistic random structures .
Moreover, by combining artificial neural networks (ANNs) and evolutionary algorithms, our group
proposed a neural evolution structure (NES) generation methodology for HEA structure generation
[45]
[Figure 2] . According to pair distribution functions and atomic properties, a model is first trained on
smaller unit cells and then the larger unit cell is generated by the inverse design approach. Compared to
SQSs, the computational cost and time can be dramatically reduced (i.e., ~1000 times faster) for NESs and
consequently large structures (over 400,00 atoms) can be generated in a few hours. Another advantage of
NESs is that multiple structures with the same fractional composition can be generated by the same model.

Surface energies and work functions are directly related to adsorption performance and can therefore be
[28,46,47]
used as descriptors of catalytic activity . Duong et al. calculated the surface energies and work functions
[48]
of Co-Cr-Fe-Mn-Mo-Ni alloys using HT DFT calculations . In this work, low-order FCC alloys (up to
quaternary) with different alloy compositions belonging to the senary Co-Cr-Fe-Mn-Mo-Ni system were
considered in calculating their surface energies and work functions. The CALPHAD methodology was
applied in the sub-regular solution model to analyze the populated first-principles data. CALPHAD models
allow smooth interpolations across the alloy composition domains, as well as extrapolations to higher-order
FCC HEAs, achieving more information with fewer data. In addition, considering the error of any models,
Bayesian statistics were adopted to quantify, to some extent, the uncertainties of the CALPHAD models.
Note that in this work, the achieved surface energies and work functions by HT calculations were used to
rank the inherent corrosion-resistance potential of various equiatomic and near-equiatomic FCC HEAs
belonging to the Co-Cr-Fe-Mn-Mo-Ni system, rather than their catalytic performance. We believe that HT