In contrast, a generative model seeks to exploit the joint probability of a chemical species with target characteristics. Mathematically, discriminative models are defined by learning the probability distribution function of properties given the molecular or material structure. From a machine learning viewpoint, the inverse design problem can be addressed through so-called generative modeling. Therefore, inverse design methods aim to start from the desired property and optimize a corresponding chemical structure. Traditional computational approaches to design chemical species are limited by the need to compute properties for a vast number of candidates, e.g., by discriminative modeling. At room temperature, this cis-configured dioxo species rapidly isomerizes to a more stable trans configuration through the release of one of the alkoxide ligands from the complex, which then goes on to form the isolated uranyl trimer complex. Analysis of the mechanism of this photochemical oxidation via density functional theory (DFT) calculations indicates that the formation of this uranyl trimer occurs through a fleeting uranium cis-dioxo intermediate. This uranium(V) bis-alkoxide can then be reduced with KC8 to form a uranium(IV) complex, which upon exposure to UV light, in solution, releases 9,10-diphenylanthracene to generate a cyclic uranyl trimer through formal two-electron photooxidation. This reaction proceeds via an isolable, alkoxide-bridged diuranium(IV/IV) species, implying that the oxidative addition occurs in two sequential, single-electron oxidations of the metal center, including rebound of a terminal oxygen radical. Herein, we describe the peroxide O–O bond cleavage of 9,10-diphenylanthracene-9,10-endoperoxide in nonaqueous media, mediated by a uranium(III) precursor to generate a stable uranium(V) bis-alkoxide complex, namely. In stark contrast, reports concerning the ability of a uranium complex to activate the O–O bond of an organic peroxide are exceedingly rare. The activation of chalcogen–chalcogen bonds using organometallic uranium complexes has been well documented for S–S, Se–Se, and Te–Te bonds. Our results shed light on previously underappreciated solvent-dependent chain conformation effects and their role in governing pathway complexity in aqueous media. In contrast, the decreased capability of the TEG chains to effectively shield larger hydrophobic cores (OPE3 and OPE4) enables different types of solvent quality-dependent conformations (extended, partly back-folded and back-folded), which in turn induce various controllable aggregation pathways with distinct morphologies and mechanisms. The relatively small hydrophobic component of OPE2 can be readily shielded by the TEG chains, leading to only one aggregation pathway. Strikingly, detailed self-assembly studies in aqueous media disclose a different tendency of the TEG chains to fold back and enwrap the hydrophobic molecular component depending on both the size of the core and the volume fraction of the co-solvent (THF). ![]() To this end, we have designed a series of oligo(phenylene ethynylene) (OPE)-based bolaamphiphilic Pt(II) complexes OPE2–4 bearing solubilizing triethylene glycol (TEG) chains of equal length on both molecule ends, but a different size of the hydrophobic aromatic scaffold. Herein, we unravel the role of solute–solvent interactions in controlling chain conformation effects, allowing energy landscape modulation and pathway selection in aqueous supramolecular polymerization. ![]() However, to date, solute–solvent effects remain poorly understood in the context of complex self-assembly energy landscapes and pathway complexity. Within the growing field of supramolecular polymer science, these interactions have been recognized as an important driving force for (entropically driven) intermolecular association, particularly in aqueous media. ![]() Solute–solvent interactions play a critical role in multiple fields, including biology, materials science, and (physical) organic, polymer, and supramolecular chemistry.
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