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Literature reports have demonstrated that Schiff-base-type ligands can serve as robust platforms for the synthesis of heterobimetallic complexes containing transition metals and the uranyl dication (UO₂²⁺). However, efforts have not advanced to include either synthesis of complexes containing second- or third-row transition metals or measurement of the redox properties of the corresponding heterobimetallic complexes, despite the significance of actinide redox in studies of nuclear fuel reprocessing and separations. Here, metalloligands denoted [Ni], [Pd], and [Pt] that contain the corresponding Group 10 metals have been prepared and a synthetic strategy to access species incorporating the uranyl ion (UO₂²⁺) has been explored, toward the goal of understanding how the secondary metals could tune uranium-centered redox chemistry. The synthesis and redox characterization of the bimetallic complex [Ni,UO₂] was achieved, and factors that appear to govern extension of the chosen synthetic strategy to complexes with Pd and Pt are reported here. Infrared and solid-state structural data from X-ray diffraction analysis of the metalloligands [Pd] and [Pt] show that the metal centers in these complexes adopt the expected square planar geometries, while the structure of the bimetallic [Ni,UO₂] reveals that the uranyl moiety influences the coordination environment of Ni(II), including inducement of a puckering of the ligand backbone of the complex in which the phenyl rings fold around the nickel-containing core in an umbrella-shaped fashion. Cyclic voltammetric data collected on the heterobimetallic complexes of both Ni(II) and Pd(II) provide evidence for uranium-centered redox cycling, as well as for the accessibility of other reductions that could be associated with Ni(II) or the organic ligand backbone. Taken together, these results highlight the unique redox behaviors that can be observed in multimetallic systems and design concepts that could be useful for accessing tunable multimetallic complexes containing the uranyl dication.

 

Incorporation of secondary redox-inactive cations into heterobimetallic complexes is an attractive strategy for modulation of metal-centered redox chemistry, but quantification of the consequences of incorporating strongly Lewis acidic trivalent cations has received little attention. Here, a family of seven heterobimetallic complexes that pair a redox-active nickel center with La3+, Y3+, Lu3+, Sr2+, Ca2+, K+, and Na+ (in the form of their triflate salts) have been prepared on a heteroditopic ligand platform to understand how chemical behavior varies across the comprehensive series. Structural data from X-ray diffraction analysis demonstrate that the positions adopted by the secondary cations in the crown-ether-like site of the ligand relative to nickel are dependent primarily on the secondary cations’ ionic radii and that the triflate counteranions are bound to the cations in all cases. Electrochemical data, in concert with electron paramagnetic resonance studies, show that nickel(II)/nickel(I) redox is modulated by the secondary metals; the heterogeneous electron-transfer rate is diminished for the derivatives incorporating trivalent metals, an effect that is dependent on steric crowding about the nickel metal center and that was quantified here with a topographical free-volume analysis. As related analyses carried out here on previously reported systems bear out similar relationships, we conclude that the placement and identity of both the secondary metal cations and their associated counteranions can afford unique changes in the (electro)chemical behavior of heterobimetallic species. 

Obtaining useful insights from machine learning models trained on experimental datasets collected across different groups to improve the sustainability of chemical processes can be challenging due to the small size and heterogeneity of the dataset. Here we show that shallow learning models such as decision trees and random forest algorithms can be an effective tool for guiding experimental research in the sustainable chemistry field. This study trained four different machine learning algorithms (linear regression, decision tree, random forest, and multilayer perceptron) using different sized datasets containing up to 520 unique reaction conditions for the nitrogen reduction reaction (NRR) on heterogeneous electrocatalysts. Using the catalyst properties and experimental conditions as the features, we determined the ability of each model to regress the ammonia production rate and the faradaic efficiency. We observed that the shallow learning decision tree and random forest models had equal or better predictive power compared to the deep learning multilayer perceptron models and the simple linear regression models. Moreover, decision tree and random forest models enable the extraction of feature importance, which is a powerful tool in guiding experimental research. Analysis of the models showed the complex interaction between the applied potential and catalysts on the effective rate for the NRR. We also suggest some underexplored catalysts–electrolyte combinations to experimental researchers looking to improve both the rate and efficiency of the NRR reaction. 

Although crown ethers can selectively bind many metal cations, little is known regarding the solution properties of crown ether complexes of the uranyl dication, UO2 2+. Here, the synthesis and characterization of isolable complexes in which the uranyl dication is bound in an 18-crown-6-like moiety are reported. A tailored macrocyclic ligand, templated with a Pt(II) center, captures UO2 2+ in the crown moiety, as demonstrated by results from single-crystal X-ray diffraction analysis. The U(V) oxidation state becomes accessible at a quite positive potential (E1/2) of −0.18 V vs Fc+/0 upon complexation, representing the most positive UVI/UV potential yet reported for the UO2 n+ core. Isolation and characterization of the U(V) form of the crown complex are also reported here; there are no prior reports of reduced uranyl crown ether complexes, but U(V) is clearly stabilized by crown chelation. Joint computational studies show that the electronic structure of the U(V) form results in significant weakening of U−Ooxo bonding despite the quite positive reduction potential at which this species can be accessed, underscoring that crown-ligated uranyl species could demonstrate unique reactivity under only modestly reducing conditions. 

The 2,2′-bipyridyl-6,6′-dicarboxylate ligand (bdc) has been shown in prior work to effectively capture the uranyl(VI) ion, UO2 2+, from aqueous solutions. However, the redox properties of the uranyl complex of this ligand have not been addressed despite the relevance of uranium-centered reduction to the nuclear fuel cycle and the presence of a bipyridyl core in bdc, a motif long recognized for its ability to support redox chemistry. Here, the bdc complex of UO2 2+ (1-UO2) has been synthetically prepared and isolated under nonaqueous conditions for the study of its reductive chemical and electrochemical behavior. Spectrochemical titration data collected using decamethylcobaltocene (Cp*2Co) as the reductant demonstrate that 1e− reduction of 1-UO2 is accessible, and companion near-infrared and infrared spectroscopic data, along with theoretical findings from density functional theory, provide evidence that supports the accessibility of the U(V) oxidation state. Data obtained for control ruthenium complexes of bdc and related polypyridyl dicarboxylate ligands provide a counterpoint to these findings; ligand-centered reduction of bdc in these control compounds occurs at potentials more negative than those measured for reduction of 1-UO2, further supporting the generation of uranium(V) in 1-UO2. Taken together, these results underscore the usefulness of bdc as a ligand for actinyl ions and suggest that it could be useful for further studies of the reductive activation of these unique species. 

We shed light on the mechanism and rate-determining steps of the electrochemical carboxylation of acetophenone as a function of CO 2 concentration by using a robust finite element analysis model that incorporates each reaction step. Specifically, we show that the first electrochemical reduction of acetophenone is followed by the homogeneous chemical addition of CO 2 . The electrochemical reduction of the acetophenone-CO 2 adduct is more facile than that of acetophenone, resulting in an Electrochemical–Chemical–Electrochemical (ECE) reaction pathway that appears as a single voltammetric wave. These modeling results provide new fundamental insights into the complex microenvironment in CO 2 -rich media that produces an optimum electrochemical carboxylation rate as a function of CO 2 pressure.