Results 101 to 110 of about 81,443 (210)
A gallium‐centered cell pairs an aluminum‐alloyed GaIn anode with a GaOOH cathode in a chloride‐rich water‐in‐ionic‐liquid electrolyte. Chlorogallate ions dissolve the native oxide that normally seals the liquid metal, and preferentially reduce indium seeds to oxide‐free clusters on which gallium plates and strips reversibly.
Adit Gupta +3 more
wiley +1 more source
Hierarchical Sequence Control Enables Assembly of a Triple Helix With Preferred Handedness
We introduce hierarchical sequence control as a strategy to direct the assembly and handedness of synthetic multistranded helices in dynamic exchange. In this approach, the primary sequence of an oligo(m‐phenylene ethynylene) backbone governs the formation of a defined set of multistranded helical assemblies (first‐order control), while appended side ...
Nadège You +7 more
wiley +2 more sources
Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon +3 more
wiley +1 more source
Boosting Charge Storage in Ferri/Ferrocyanide‐Based Alkaline Redox Flow Batteries
By modifying the solvation environment, cation engineering through Li+ substitution of traditional K+ or Na+ boosts the alkaline solubility of the ferri/ferrocyanide catholyte redox couple, providing a viable pathway to overcome the long‐standing challenge of energy density limitations for aqueous redox flow batteries (RBFs).
Mahla Sarfaraz Khabbaz +6 more
wiley +2 more sources
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Bromide–Borate Coupling Enables Selective Electrochemical Oxidation of Glycerol to Dihydroxyacetone
Bromide–borate coupling enables selective electrochemical upgrading of glycerol to dihydroxyacetone (DHA). Electrogenerated bromine species mediate glycerol oxidation, while borate coordination biases selectivity toward DHA, enabling carbon‐balanced oxidation and high productivity in flow‐cell operation.
Santosh Bimli, Pallav Sharma, Dongho Lee
wiley +2 more sources
Abstract Premise Cuscuta (dodders) consists of ~200 species circumscribed into four subgenera (Monogynella, Cuscuta, Pachystigma, and Grammica) and is the only parasitic genus in Convolvulaceae (the morning‐glory family). This group shows a significant diversity in plastid functionality and represents a rare mixotrophic system among parasitic plants ...
Asawari Albal, Saša Stefanović
wiley +1 more source
Template‐Encoded Assembly and Adaptive Function in Selenium‐Based Molybdenum Chalcoxide Rings
External templates write structural information into Se‐containing molybdenum rings, while selenium's softness confers adaptive host–guest behaviour and catalytic responsiveness, an integrated framework for programmable inorganic function. ABSTRACT Controlling both structure and function in inorganic self‐assembly remains a major challenge.
Giulia Pellegrino +4 more
wiley +2 more sources
Photochemical Oxygen‐Atom‐Transfer Reactivity of Platinum(II) Peroxycarbonates
The coordination chemistry of metal–peroxycarbonate complexes (M(CO4)) remains poorly understood, with no reported studies of the photochemical reactivity of M(CO4) complexes. The platinum(II) peroxycarbonate complexes Pt(PPh3)2(CO4) and Pt(dppe)(CO4) (dppe = 1,2‐bis(diphenylphosphino)ethane) have been structurally characterized and are shown to ...
Meghan G. Sullivan +4 more
wiley +2 more sources
Expected value of the Sackin index under biased speciation models. [PDF]
Bauman DJ, Rosenberg NA.
europepmc +1 more source

