Redox-Induced Structural Change in Artificial Heterometallic-Oxide Cluster Mimicking the Photosynthetic Oxygen-Evolving Center

The oxygen-evolving center (OEC) in photosynthesis is a unique Mn₄CaO₅-cluster that catalyzes the water-splitting reaction in nature. Understanding its catalytic mechanism for the O=O bond formation is of great challenge and long-standing issue, which is severely restricted by the lack of precise structure and mechanism mimics of this heterometallic-oxide cluster. Herein, we report two synthetic (Mn₃XO₄)₂O-clusters (X=Sr²⁺, La³⁺) that closely mimic the heterometallic-oxide Mn₃XO₄ cubane and three different types of μ-oxide bridges (μ₂-O²⁻, μ₃-O²⁻, and μ₄-O²⁻) simultaneously as seen in the OEC. By resolving the crystal structures of both oxidized and reduced forms of the cluster, we have identified significant redox-induced structural changes that take place on the μ₂-oxide bridge, rather than the μ₄-oxide or μ₃-oxide bridges. Our results provide chemical insights into understanding the reactivity of three different types of oxide bridges in the biological Mn₄CaO₅-cluster in PSII.     

Tribochemically Controlled Atom Transfer Radical Polymerization Enabled by Contact Electrification

Traditional mechanochemically controlled reversible-deactivation radical polymerization (RDRP) utilizes ultrasound or ball milling to regenerate activators, which induce side reactions because of the high-energy and high-frequency stimuli. Here, we propose a facile approach for tribochemically controlled atom transfer radical polymerization (tribo-ATRP) that relies on contact-electro-catalysis (CEC) between titanium oxide (TiO₂) particles and CuBr₂/tris(2-pyridylmethylamine (TPMA), without any high-energy input. Under the friction induced by stirring, the TiO₂ particles are electrified, continuously reducing CuBr₂/TPMA into CuBr/TPMA, thereby conversing alkyl halides into active radicals to start ATRP. In addition, the effect of friction on the reaction was elucidated by theoretical simulation. The results indicated that increasing the frequency could reduce the energy barrier for the electron transfer from TiO₂ particles to CuBr₂/TPMA. In this study, the design of tribo-ATRP was successfully achieved, enabling CEC (ca. 10 Hz) access to a variety of polymers with predetermined molecular weights, low dispersity, and high chain-end fidelity.     

Artificial Mn4Ca Clusters with Exchangeable Solvent Molecules Mimicking the Oxygen‐Evolving Center in Photosynthesis

The natural Mn₄Ca cluster in photosystem II serves as a blueprint to develop artificial water‐splitting catalysts for the generation of solar fuel in artificial photosynthesis. Although significant advances have recently been achieved, it remains a great challenge to prepare robust artificial Mn₄Ca clusters that precisely mimic the structure and function of the biological catalyst. Herein, we report the isolation and structural characterization of two Mn₄CaO₄ complexes with polar solvent molecules, acetonitrile or N,N‐dimethylformamide, which closely mimics the two water molecules on the calcium ion, as well as the oxidation states of the four manganese ions and the main geometric structure of the natural Mn₄Ca cluster. These new artificial Mn₄Ca complexes provide important chemical clues to understand the structure and mechanism of the biological system.     

Nonparametric variable selection and its application to additive models

Variable selection for multivariate nonparametric regression models usually involves parameterized approximation for nonparametric functions in the objective function. However, this parameterized approximation often increases the number of parameters significantly, leading to the “curse of dimensionality” and inaccurate estimation. In this paper, we propose a novel and easily implemented approach to do variable selection in nonparametric models without parameterized approximation, enabling selection consistency to be achieved. The proposed method is applied to do variable selection for additive models. A two-stage procedure with selection and adaptive estimation is proposed, and the properties of this method are investigated. This two-stage algorithm is adaptive to the smoothness of the underlying components, and the estimation consistency can reach a parametric rate if the underlying model is really parametric. Simulation studies are conducted to examine the performance of the proposed method. Furthermore, a real data example is analyzed for illustration.

     

Diagnostic checking for multivariate regression models

Diagnostic checking for multivariate parametric models is investigated in this article. A nonparametric Monte Carlo Test (NMCT) procedure is proposed. This Monte Carlo approximation is easy to implement and can automatically make any test procedure scale-invariant even when the test statistic is not scale-invariant. With it we do not need plug-in estimation of the asymptotic covariance matrix that is used to normalize test statistic and then the power performance can be enhanced. The consistency of NMCT approximation is proved. For comparison, we also extend the score type test to one-dimensional cases. NMCT can also be applied to diverse problems such as a classical problem for which we test whether or not certain covariables in linear model has significant impact for response. Although the Wilks lambda, a likelihood ratio test, is a proven powerful test, NMCT outperforms it especially in non-normal cases. Simulations are carried out and an application to a real data set is illustrated.