Freestanding polyelectrolyte films as sensors for osmotic pressure.

Freestanding ultrathin polyelectrolyte-multilayer membranes, transferred to topographically structured polydimethylsiloxane (PDMS), are used as mechanical sensors. Due to the membranes' semipermeability, high-molecular-weight molecules can be either entrapped inside them or excluded, thus generating an osmotic pressure. This leads to a deformation. We investigate the deformation as a function of the osmotic pressure and present an analytical theory that fully describes the data. Thus, osmotic pressures can be determined quantitatively. The individual osmotic-sensitive elements have only microscopic dimensions, and arrays can be easily produced.     

Non-Convex Global Minimization and False Discovery Rate Control for the TREX

The TREX is a recently introduced method for performing sparse high-dimensional regression. Despite its statistical promise as an alternative to the lasso, square-root lasso, and scaled lasso, the TREX is computationally challenging in that it requires solving a nonconvex optimization problem. This article shows a remarkable result: despite the nonconvexity of the TREX problem, there exists a polynomial-time algorithm that is guaranteed to find the global minimum. This result adds the TREX to a very short list of nonconvex optimization problems that can be globally optimized (principal components analysis being a famous example). After deriving and developing this new approach, we demonstrate that (i) the ability of the preexisting TREX heuristic to reach the global minimum is strongly dependent on the difficulty of the underlying statistical problem, (ii) the new polynomial-time algorithm for TREX permits a novel variable ranking and selection scheme, (iii) this scheme can be incorporated into a rule that controls the false discovery rate (FDR) of included features in the model. To achieve this last aim, we provide an extension of the results of Barber and Candes to establish that the knockoff filter framework can be applied to the TREX. This investigation thus provides both a rare case study of a heuristic for nonconvex optimization and a novel way of exploiting nonconvexity for statistical inference.     

A simple surfactant‐free route for preparation of flower‐like crystals of CoS with hierarchitectures

Hierarchical cobalt sulfide crystals with flower‐like microstructures were successfully prepared by a simple one‐pot solvothermal route, employing CoCl₂·6H₂O as a cobalt precursor and KSCN as a sulfur source. The morphology of these microstructures can be easily controlled by adjusting the molar ratio of glycol to DMF in the solvent. The products were characterized by XRD and SEM. Possible formation mechanisms of CoS hierarchical microspheres are proposed. The influences of the nature of reaction media on the morphological evolution were also investigated and it was found that the ratio of DMF to glycol was of great importance for the formation of CoS morphology.     

Synthesis and characterization of strontium chloroborate whiskers

Single crystalline strontium chloroborate (Sr₂B₅O₉Cl) whiskers with uniform diameter have been synthesized by a facile route based on the calcination of precursor. The precursor was prepared by the sedimentation reaction between SrCl₂ and Na₂B₄O₇ aqueous solution. The products were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Fourier transform infrared spectrum (FT‐IR). An optimal synthesis temperature for preparing Sr₂B₅O₉Cl whiskers was obtained, and the possible formation process was also presented.     

A Confidence Region Approach to Tuning for Variable Selection

We develop an approach to tuning of penalized regression variable selection methods by calculating the sparsest estimator contained in a confidence region of a specified level. Because confidence intervals/regions are generally understood, tuning penalized regression methods in this way is intuitive and more easily understood by scientists and practitioners. More importantly, our work shows that tuning to a fixed confidence level often performs better than tuning via the common methods based on Akaike information criterion (AIC), Bayesian information criterion (BIC), or cross-validation (CV) over a wide range of sample sizes and levels of sparsity. Additionally, we prove that by tuning with a sequence of confidence levels converging to one, asymptotic selection consistency is obtained, and with a simple two-stage procedure, an oracle property is achieved. The confidence-region-based tuning parameter is easily calculated using output from existing penalized regression computer packages. Our work also shows how to map any penalty parameter to a corresponding confidence coefficient. This mapping facilitates comparisons of tuning parameter selection methods such as AIC, BIC, and CV, and reveals that the resulting tuning parameters correspond to confidence levels that are extremely low, and can vary greatly across datasets. Supplemental materials for the article are available online.     

Far Casting Cross-Validation

Cross-validation has long been used for choosing tuning parameters and other model selection tasks. It generally performs well provided the data are independent, or nearly so. Improvements have been suggested which address ordinary cross-validation’s (OCV) shortcomings in correlated data. Whereas these techniques have merit, they can still lead to poor model selection in correlated data or are not readily generalizable to high-dimensional data.

The proposed solution, far casting cross-validation (FCCV), addresses these problems. FCCV withholds correlated neighbors in every aspect of the cross-validation procedure. The result is a technique that stresses a fitted model’s ability to extrapolate rather than interpolate. This generally leads to better model selection in correlated datasets.

Whereas FCCV is less than optimal in the independence case, our improvement of OCV applies more generally to higher dimensional error processes and to both parametric and nonparametric model selection problems. To facilitate introduction, we consider only one application, namely estimating global bandwidths for curve estimation with local linear regression. We provide theoretical motivation and report some comparative results from a simulation experiment and on a time series of annual global temperature deviations. For such data, FCCV generally has lower average squared error when disturbances are correlated.

Supplementary materials are available online.     

Superhydrophobic 3D Microstructures Assembled From 1D Nanofibers of Polyaniline

Superhydrophobic dandelion‐like 3D microstructures self‐assembled from 1D nanofibers of PANI were prepared by a self‐assembly process in the presence of perfluorosebacic acid (PFSEA) as a dopant. The dandelion‐like microspheres (about 5 µm) are composed of uniform Y‐shaped junction nanofibers of about 210 nm average diameter and several micrometers in length, as measured by SEM. The dandelion‐like microstructure is coreless with a hollow cavity, and the shell thickness is about one third of the sphere diameter, as measured by TEM. Since PFESA dopant has a low surface energy perfluorinated carbon chain and two hydrophilic  COOH end groups, it has dopant, is a “soft‐template” and brings about superhydrophobic functions at the same time. Moreover, it is proposed that the self‐assembly of PANI 1D nanofibers, driven by a combined interaction of hydrogen bonding, π‐π stacking and hydrophobic interactions, leads to the formation of the 3D microstructures.

     

Photocontrolled Release of Chemicals from Nano‐ and Microparticle Containers

A benzoin‐derived diol linker was synthesized and used to generate biocompatible polyesters that can be fully decomposed on demand upon UV irradiation. Extensive structural optimization of the linker unit was performed to enable the defined encapsulation of diverse organic compounds in the polymeric structures and allow for a well‐controllable polymer cleavage process. Selective tracking of the release kinetics of encapsulated model compounds from the polymeric nano‐ and microparticle containers was performed by confocal laser scanning microscopy in a proof‐of‐principle study. The physicochemical properties of the incorporated and released model compounds ranged from fully hydrophilic to fully hydrophobic. The demonstrated biocompatibility of the utilized polyesters and degradation products enables their use in advanced applications, for example, for the smart packaging of UV‐sensitive pharmaceuticals, nutritional components, or even in the area of spatially selective self‐healing processes.     

Tuning the CO2 Hydrogenation Selectivity of Rhodium Single-Atom Catalysts on Zirconium Dioxide with Alkali Ions

Tuning the coordination environments of metal single atoms (M₁) in single-atom catalysts has shown large impacts on catalytic activity and stability but often barely on selectivity in thermocatalysis. Here, we report that simultaneously regulating both Rh₁ atoms and ZrO₂ support with alkali ions (e.g., Na) enables efficient switching of the reaction products from nearly 100 % CH₄ to above 99 % CO in CO₂ hydrogenation in a wide temperature range (240–440 °C) along with a record high activity of 9.4 mol_CO g_Rh⁻¹ h⁻¹ at 300 °C and long-term stability. In situ spectroscopic characterization and theoretical calculations unveil that alkali ions on ZrO₂ change the surface intermediate from formate to carboxy species during CO₂ activation, thus leading to exclusive CO formation. Meanwhile, alkali ions also reinforce the electronic Rh₁-support interactions, endowing the Rh₁ atoms more electron deficient, which improves the stability against sintering and inhibits deep hydrogenation of CO to CH₄.     

Increasing Reduction Potentials of Type 1 Copper Center and Catalytic Efficiency of Small Laccase from Streptomyces coelicolor through Secondary Coordination Sphere Mutations

The key to type 1 copper (T1Cu) function lies in the fine tuning of the Cu^II/I reduction potential (E°′_T1Cu) to match those of its redox partners, enabling efficient electron transfer in a wide range of biological systems. While the secondary coordination sphere (SCS) effects have been used to tune E°′_T1Cu in azurin over a wide range, these principles are yet to be generalized to other T1Cu-containing proteins to tune catalytic properties. To this end, we have examined the effects of Y229F, V290N and S292F mutations around the T1Cu of small laccase (SLAC) from Streptomyces coelicolor to match the high E°′_T1Cu of fungal laccases. Using ultraviolet-visible absorption and electron paramagnetic resonance spectroscopies, together with X-ray crystallography and redox titrations, we have probed the influence of SCS mutations on the T1Cu and corresponding E°′_T1Cu. While minimal and small E°′_T1Cu increases are observed in Y229F- and S292F-SLAC, the V290N mutant exhibits a major E°′_T1Cu increase. Moreover, the influence of these mutations on E°′_T1Cu is additive, culminating in a triple mutant Y229F/V290N/S292F-SLAC with the highest E°′_T1Cu of 556 mV vs. SHE reported to date. Further activity assays indicate that all mutants retain oxygen reduction reaction activity, and display improved catalytic efficiencies (k_cat/K_M) relative to WT-SLAC.