AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning

Pentanuclear iron complex for water oxidation: spectroscopic analysis of reactive intermediates in solution and catalyst immobilization into the MOF-based photoanode

Photoelectrochemical water splitting can produce green hydrogen for industrial use and CO2-neutral transportation, ensuring the transition from fossil fuels to green, renewable energy sources. The iron-based electrocatalyst [FeII4FeIII(μ-3-O)(μ-L)6]3+ (LH = 3,5-bis(2-pyridyl)pyrazole) (1), discovered in 2016, is one of the fastest molecular water oxidation catalysts (WOC) based on earth-abundant elements. However, its water oxidation reaction mechanism has not been yet fully elucidated. Here, we present in situ X-ray spectroscopy and electron paramagnetic resonance (EPR) analysis of electrochemical water oxidation reaction (WOR) promoted by (1) in water-acetonitrile solution. We observed transient reactive intermediates during the in situ electrochemical WOR, consistent with a coordination sphere expansion prior to the onset of catalytic current. At a pre-catalytic (~+1.1 V vs. Ag/AgCl) potential, the distinct g~2.0 EPR signal assigned to FeIII/FeIV interaction was observed. Prolonged bulk electrolysis at catalytic (~+1.6 V vs. Ag/AgCl) potential leads to the further oxidation of Fe centers in (1). At the steady state achieved with such electrolysis, the formation of hypervalent FeV=O and FeIV=O catalytic intermediates was inferred with XANES and EXAFS fitting, detecting a short Fe=O bond at ~1.6 Å. (1) was embedded into MIL-126 MOF with the formation of (1)-MIL-126 composite. The latter was tested in photoelectrochemical WOR and demonstrated an improvement of electrocatalytic current upon visible light irradiation in acidic (pH=2) water solution. The presented spectroscopic analysis gives further insight into the catalytic pathways of multinuclear systems and should help the subsequent development of more energy- and cost-effective catalysts of water splitting based on earth-abundant metals. Photoelectrocatalytic activity of (1)-MIL-126 confirms the possibility of creating an assembly of (1) inside a solid support and boosting it with solar irradiation towards industrial applications of the catalyst.

The AXEAP2 program for Kβ X-ray emission spectra analysis using artificial intelligence

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant Kβ XES of 3d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 (AXEAP2), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3d electron spin state, 3d-3p electron exchange force and Kβ emission core-hole lifetime.