Elucidating the Impact of Li3InCl6-Coated LiNi0.8Co0.15Al0.05O2 on the Electro-Chemo-Mechanics of Li6PS5Cl-Based Solid-State Batteries.

Li6PS5Cl has attracted significant attention due to its high Li-ion conductivity and processability, facilitating large-scale solid-state battery applications. However, when paired with high-voltage cathodes, it experiences adverse side reactions. Li3InCl6 (LIC), known for its higher stability at high voltages and moderate Li-ion conductivity, is considered a catholyte to address the limitations of Li6PS5Cl. To extend the stability of Li6PS5Cl toward LiNi0.8Co0.15Al0.05O2 (NCA), we applied nanocrystalline LIC as a 180 nm-thick protective coating in a core-shell-like fashion (LIC@NCA) via mechanofusion. Solid-state batteries with LIC@NCA allow an initial discharge specific capacity of 148 mA h/g at 0.1C and 80% capacity retention for 200 cycles at 0.2C with a cutoff voltage of 4.2 V (vs Li/Li+), while cells without LIC coating suffers from low initial discharge capacity and poor retention. Using a wide spectrum of advanced characterization techniques, such as operando XRD, XPS, FIB-SEM, and TOF-SIMS, we reveal that the superior performance of solid-state batteries employing LIC@NCA is related to the suppression of detrimental interfacial reactions of NCA with Li6PS5Cl, delamination, and particle cracking compared to uncoated NCA.

Machine-learning reinforcement for optimizing multilayered thin films: applications in designing broadband antireflection coatings.

The design and fabrication of nanoscale multilayered thin films play an essential role in regulating the operation efficiency of sensitive optical sensors and filters. In this paper, we introduce a packaged tool that employs flexible electromagnetic calculation software with machine learning in order to find the optimized double-band antireflection coatings in intervals of wavelength from 3 to 5 µm and 8 to 12 µm. Instead of computing or modeling an extremely enormous set of thin film structures, this tool enhanced with machine learning can swiftly predict the optical properties of a given structure with >99.7% accuracy and a substantial reduction in computation costs. Furthermore, the tool includes two learning methods that can infer a global optimal structure or suitable local optimal ones. Specifically, these well-trained models provide the highest accurate double-band average transmission coefficient combined with the lowest number of layers or the thinnest total thickness starting from a reference multilayered structure. Finally, the more sophisticated enhancement method, called the double deep Q-learning network, exhibited the best performance in finding optimal antireflective multilayered structures with the highest double-band average transmission coefficient of about 98.95%.

A case of self-improving collodion ichthyosis in Vietnam.

Autosomal recessive congenital ichthyosis is a heterogeneous group of congenital disorders characterized by aberrant skin cornification and diffuse skin scaling. Some patients with this condition are born encased in a collodion membrane which is later shed, revealing the underlying skin disorder. Self-healing collodion baby (SHCB) is a less common phenotype of this disorder, accounting for about 10% of the patients, in which the membrane peels after several weeks, leaving no underlying skin aberration. Here, we report and discuss the diagnosis and management of an infant with SHCB in Vietnam due to compound heterozygous pathogenic mutations in TGM1.

Single cigar-shaped nanopores functionalized with amphoteric amino acid chains: experimental and theoretical characterization.

We present an experimental and theoretical characterization of single cigar-shaped nanopores with pH-responsive carboxylic acid and lysine chains functionalized on the pore surface. The nanopore characterization includes (i) optical images of the nanostructure obtained by FESEM; (ii) different chemical procedures for the nanopore preparation (etching time and functionalizations; pH and electrolyte concentration of the external solution) allowing externally tunable nanopore responses monitored by the current-voltage (I-V) curves; and (iii) transport simulations obtained with a multilayer nanopore model. We show that a single, approximately symmetric nanopore can be operated as a reconfigurable diode showing different rectifying behaviors by applying chemical and electrical signals. The remarkable characteristics of the new nanopore are the sharp response observed in the I-V curves, the improved tunability (with respect to previous designs of symmetric nanopores) which is achieved because of the direct external access to the nanostructure mouths, and the broad range of rectifying properties. The results concern both fundamental concepts useful for the understanding of transport processes in biological systems (ion channels) and applications relevant for tunable nanopore technology (information processing and drug controlled release).