This paper studies the averaging GMM estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an infeasible optimal weight. We establish asymptotic theory on uniform approximation of the upper and lower bounds of the finite‐sample truncated risk difference between any two estimators, which is used to compare the averaging GMM estimator and the conservative GMM estimator. Under some sufficient conditions, we show that the asymptotic lower bound of the truncated risk difference between the averaging estimator and the conservative estimator is strictly less than zero, while the asymptotic upper bound is zero uniformly over any degree of misspecification. The results apply to quadratic loss functions. This uniform asymptotic dominance is established in non‐Gaussian semiparametric nonlinear models.

The structure and composition of nanofillers have a significant influence on polyamide nanofiltration (NF) membranes. In this work, an asymmetric organic nanobowl containing a concave cavity was synthesized and incorporated into a polyamide layer to prepare thin film nanocomposite (TFN) membranes via an interfacial polymerization process. Benefiting from the hydrophilicity, hollow cavity and charge property of the compatible organic nanobowls, the separation performance of the developed TFN membrane was significantly improved. The corresponding water fluxes increased to 119.44 ± 5.56, 141.82 ± 3.24 and 130.27 ± 2.05 L/(m²·h) toward Na₂SO₄, MgCl₂ and NaCl solutions, respectively, with higher rejections, compared with the control thin film composite (TFC) and commercial (CM) membranes. Besides this, the modified TFN membrane presented a satisfying purification performance toward tap water, municipal effluent and heavy metal wastewater. More importantly, a better antifouling property of the TFN membrane than TFC and CM membranes was achieved with the assistance of organic nanobowls. These results indicate that the separation performance of the TFN membrane can be elevated by the incorporation of organic nanobowls.