Reinterpreting the Fate of Iridium(III) Photocatalysts─Screening a Combinatorial Library to Explore Light-Driven Side-Reactions

Harnessing Electro-Descriptors for Mechanistic and Machine Learning Analysis of Photocatalytic Organic Reactions

Photocatalysis has emerged as an effective tool for addressing the contemporary challenges in organic synthesis. However, the trial-and-error-based screening of feasible substrates and optimal reaction conditions remains time-consuming and potentially expensive in industrial practice. Here, we demonstrate an electrochemical-based data-acquisition approach that derives a simple set of redox-relevant electro-descriptors for effective mechanistic analysis and performance evaluation through machine learning (ML) in photocatalytic synthesis. These electro-descriptors correlate to the quantification of shifted charge transfer processes in response to the photoirradiation and enabled construction of reactivity diagram where high-yield reactive "hot zones" can reflect subtle changes of the reaction system. For the model reaction of photocatalytic deoxygenation reaction, the influence of varying carboxylic acids (substrate A, oxidation-intended) and alkenes (substrate B, reduction-intended) and varying reaction conditions on the reaction yield can be visualized, while mathematical analysis of the electro-descriptor patterns further revealed distinct mechanistic/kinetic impacts from different substrates and conditions. Additionally, in the application of ML algorithms, the experimentally derived electro-descriptors reflect an overall redox kinetic outcome contributed from vast reaction parameters, serving as a capable means to reduce the dimensionality in the case of complex multiparameter chemical space. As a result, utilization of electro-descriptors enabled efficient and robust quantitative evaluation of chemical reactivity, demonstrating promising potential of introducing operando-relevant experimental insights in the data-driven chemistry.

Predicting Emission Spectra of Heteroleptic Iridium Complexes Using Artificial Chemical Intelligence

We report a deep learning-based approach to accurately predict the emission spectra of phosphorescent heteroleptic [Ir(C ∧ N ${{\rm{C}}^\wedge {\rm{N}}}$ )2(N ∧ N ${{\rm{N}}^\wedge {\rm{N}}}$ )]+ complexes, enabling the rapid discovery of novel Ir(III) chromophores for diverse applications including organic light-emitting diodes and solar fuel cells. The deep learning models utilize graph neural networks and other chemical features in architectures that reflect the inherent structure of the heteroleptic complexes, composed ofC ∧ N ${{\rm{C}}^\wedge {\rm{N}}}$ andN ∧ N ${{\rm{N}}^\wedge {\rm{N}}}$ ligands, and are thus geared towards efficient training over the dataset. By leveraging experimental emission data, our models reliably predict the full emission spectra of these complexes across various emission profiles, surpassing the accuracy of conventional DFT and correlated wavefunction methods, while simultaneously achieving robustness to the presence of imperfect (noisy, low-quality) training spectra. We showcase the potential applications for these and related models for in silico prediction of complexes with tailored emission properties, as well as in "design of experiment" contexts to reduce the synthetic burden of high-throughput screening. In the latter case, we demonstrate that the models allow us to exploit a limited amount of experimental data to explore a wide range of chemical space, thus leveraging a modest synthetic effort.

A Semi-Automated, High-Throughput Approach for the Synthesis and Identification of Highly Photo-Cytotoxic Iridium Complexes

The discovery of new compounds with pharmacological properties is usually a lengthy, laborious and expensive process. Thus, there is increasing interest in developing workflows that allow for the rapid synthesis and evaluation of libraries of compounds with the aim of identifying leads for further drug development. Herein, we apply combinatorial synthesis to build a library of 90 iridium(III) complexes (81 of which are new) over two synthesise-and-test cycles, with the aim of identifying potential agents for photodynamic therapy. We demonstrate the power of this approach by identifying highly active complexes that are well-tolerated in the dark but display very low nM phototoxicity against cancer cells. To build a detailed structure-activity relationship for this class of compounds we have used density functional theory (DFT) calculations to determine some key electronic parameters and study correlations with the experimental data. Finally, we present an optimised semi-automated synthesise-and-test protocol to obtain multiplex data within 72 hours.

Lessons learnt in photocatalysis - the influence of solvent polarity and the photostability of the photocatalyst

Herein, we show that there is significant variation in both the triplet energies and redox properties of photocatalysts as a function of solvent based on a study of eight PCs in four solvents of varying polarity. A range of photocatalytic electron and energy transfer reactions were investigated using a subset of the PCs. For the photoredox reactions, the yields are not correlated with solvent polarity. Instead, when the PC could promote the formation of the target product, we observed photodegradation for all PCs across all solvents, something that is rarely investigated in the literature. This, therefore, makes it difficult to ascertain whether the parent PC and/or the photodegraded product is responsible for the photochemistry, or indeed, whether photodegradation is actually detrimental to the reaction yield. Conversely, the PCs were found to be photostable for energy transfer reactions; however, yields were not correlated to the triplet energies of the PCs, highlighting that triplet energies alone are not a suitable descriptor to discriminate the performance between PCs in photoinduced energy transfer processes.

Reactivity of radiolytically and photochemically generated tertiary amine radicals towards a CO2 reduction catalyst

Homogeneous solar fuels photocatalytic systems often require several additives in solution with the catalyst to operate, such as a photosensitizer (PS), Brønsted acid/base, and a sacrificial electron donor (SED). Tertiary amines, in particular triethylamine (TEA) and triethanolamine (TEOA), are ubiquitously deployed in photocatalysis applications as SEDs and are capable of reductively quenching the PS's excited state. Upon oxidation, TEA and TEOA form TEA•+ and TEOA•+ radical cations, respectively, which decay by proton transfer to generate redox non-innocent transient radicals, TEA• and TEOA•, respectively, with redox potentials that allow them to participate in an additional electron transfer step, thus resulting in net one-photon/two-electron donation. However, the properties of the TEA• and TEOA• radicals are not well understood, including their reducing powers and kinetics of electron transfer to catalysts. Herein, we have used both pulse radiolysis and laser flash photolysis to generate TEA• and TEOA• radicals in CH3CN, and combined with UV/Vis transient absorption and time-resolved mid-infrared spectroscopies, we have probed the kinetics of reduction of the well-established CO2 reduction photocatalyst, fac-ReCl(bpy)(CO)3 (bpy = 2,2'-bipyridine), by these radicals [kTEA• = (4.4 ± 0.3) × 109 M-1 s-1 and kTEOA• = (9.3 ± 0.6) × 107 M-1 s-1]. The ∼50× smaller rate constant for TEOA• indicates, that in contrast to a previous assumption, TEA• is a more potent reductant than TEOA• (by ∼0.2 V, as estimated using the Marcus cross relation). This knowledge will aid in the design of photocatalytic systems involving SEDs. We also show that TEA can be a useful radiolytic solvent radical scavenger for pulse radiolysis experiments in CH3CN, effectively converting unwanted oxidizing radicals into useful reducing equivalents in the form of TEA• radicals.

Electron-Poor Acridones and Acridiniums as Super Photooxidants in Molecular Photoelectrochemistry by Unusual Mechanisms

Electron-deficient acridones and in situ generated acridinium salts are reported as potent, closed-shell photooxidants that undergo surprising mechanisms. When bridging acyclic triarylamine catalysts with a carbonyl group (acridones), this completely diverts their behavior away from open-shell, radical cationic, 'beyond diffusion' photocatalysis to closed-shell, neutral, diffusion-controlled photocatalysis. Brønsted acid activation of acridones dramatically increases excited state oxidation power (by +0.8 V). Upon reduction of protonated acridones, they transform to electron-deficient acridinium salts as even more potent photooxidants (*E1/2 =+2.56-3.05 V vs SCE). These oxidize even electron-deficient arenes where conventional acridinium salt photooxidants have thusfar been limited to electron-rich arenes. Surprisingly, upon photoexcitation these electron-deficient acridinium salts appear to undergo two electron reductive quenching to form acridinide anions, spectroscopically-detected as their protonated forms. This new behaviour is partly enabled by a catalyst preassembly with the arene, and contrasts to conventional SET reductive quenching of acridinium salts. Critically, this study illustrates how redox active chromophoric molecules initially considered photocatalysts can transform during the reaction to catalytically active species with completely different redox and spectroscopic properties.

Overcoming Photochemical Limitations in Metallaphotoredox Catalysis: Red-Light-Driven C-N Cross-Coupling

Aryl amination is an essential transformation for medicinal, process, and materials chemistry. In addition to classic Buchwald-Hartwig amination conditions, blue-light-driven metallaphotoredox catalysis has emerged as a valuable tool for C-N cross-coupling. However, blue light suffers from low penetration through reaction media, limiting its scalability for industrial purposes. In addition, blue light enhances unwanted side-product formation in metallaphotoredox catalysis, namely hydrodehalogenation. Low-energy light, such as deep red (DR) or near-infrared (NIR), offers a solution to this problem as it can provide enhanced penetration through reaction media as compared to higher-energy wavelengths. Herein, we show that low-energy light can also enhance the desired reactivity in metallaphotoredox catalysis by suppressing unwanted hydrodehalogenation. We hypothesize that the reduced side product is formed by direct photolysis of the aryl-nickel bond by the high-energy light, leading to the generation of aryl radicals. Using deep-red or near-infrared light and an osmium photocatalyst, we demonstrate an enhanced scope of (hetero)aryl bromides and amine-based nucleophiles with minimal formation of hydrodehalogenation byproducts.