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Polymer dielectrics are essential for advanced electrical and electronic power systems due to their ultrafast charge–discharge rate. However, a long‐standing challenge is to maintain their dielectric performance at high temperatures. Here, a layered barium titanate/polyamideimide nanocomposite reinforced with rationally designed interfaces is reported for high‐temperature high‐energy‐density dielectrics. Nanocoatings composed of 2D montmorillonite nanosheets with anisotropic conductivities are interposed at two kinds of macroscopic interfaces: 1) the interfaces between adjacent layers in the nanocomposites (inside) and 2) the interfaces between the surface of the nanocomposite and the electrode (outside). By revealing the charge transport behavior with Kelvin probe force microscope, surface potential decay, and finite element simulation, it is demonstrated that the outside nanocoatings are observed to diminish charge injection from the electrode, while the inside nanocoatings can suppress the kinetic energy of hot carriers by redirecting their transport. In this interface‐reinforced nanocomposite, an ultrahigh energy density of 2.48 J cm−3, as well as a remarkable charge–discharge efficiency >80%, is achieved at 200 °C, six times higher than that of the nanocomposite without interfacial nanocoatings. This research unveils a novel approach for the structural design of polymer nanocomposites based on engineered interfaces to achieve high‐efficient and high‐temperature capacitive energy storage.

A Lewis base promoted deprotonative pronucleophile addition to silyl acetals has been developed and applied to the iridium-catalyzed reductive Horner-Wadsworth-Emmons (HWE) olefination of esters and the chemoselective reduction of the resulting enoates. Lewis base activation of silyl acetals generates putative pentacoordinate silicate acetals, which fragment into aldehydes, silanes, and alkoxides in situ. Subsequent deprotonative metalation of phosphonate esters followed by HWE with aldehydes furnishes enoates. This operationally convenient, mechanistically unique protocol converts the traditionally challenging aryl, alkenyl, and alkynyl esters to homologated enoates at room temperature within a single vessel.

Cost Function Networks (aka Weighted CSP) allow to model a variety of problems, such as optimization of deterministic and stochastic graphical models including Markov random Fields and Bayesian Networks. Solving cost function networks is thus an important problem for deterministic and probabilistic reasoning. This paper focuses on local consistencies which define essential tools to simplify Cost Function Networks, and provide lower bounds on their optimal solution cost. To strengthen arc consistency bounds, we follow the idea of triangle-based domain consistencies for hard constraint networks (path inverse consistency, restricted or max-restricted path consistencies), describe their systematic extension to cost function networks, study their relative strengths, define enforcing algorithms, and experiment with them on a large set of benchmark problems. On some of these problems, our improved lower bounds seem necessary to solve them. Keywords Cost function networks ⋅ Weighted CSP ⋅ Constraint optimization problems ⋅ High order consistencies ⋅ Restricted path consistency ⋅ Path inverse consistency ⋅ Max-restricted path consistency