Synthesis and Structure of Titanium Imido Complexes With Bi‐ and Tridentate PN and PNP Ligands
The synthesis of PN and PNP supported titanium imido complexes is presented with a variety of alkyl and aryl imido donors on the titanium center, giving access to new potential precatalysts in hydroamination catalysis. We report the synthesis of alkyl and aryl imido titanium(IV) complexes supported by bi‐ or tridentate PNMes and PNP ligands (PNMes = (2‐
Philipp Boos +4 more
wiley +1 more source
Aluminum-derived nanotubes for lung cancer detection: a DFT inquisition. [PDF]
Rahman AU +4 more
europepmc +1 more source
Amorphous High Entropy Alloy Nanosheets Enabling Robust Li–S Batteries
Amorphous ultrathin FeCoNiMoW high entropy alloy nanosheets are incorporated into the polypropylene separator of lithium‐sulfur batteries, enhancing their capacity, rate performance, and cycling stability. Abstract High‐entropy alloys (HEAs) show great potential for catalyzing complex multi‐step reactions, but optimizing their parameters, i.e ...
Ren He +20 more
wiley +1 more source
Aluminum phosphide poisoning with Brugada ECG: a case report highlighting diagnostic challenges arising from patient nondisclosure. [PDF]
Sadeq MA +3 more
europepmc +1 more source
Fabrication of Nickel–Cobalt Bimetal Phosphide Nanocages for Enhanced Oxygen Evolution Catalysis
Bocheng Qiu +6 more
semanticscholar +1 more source
This review compares sulfide‐ and halide‐based solid electrolytes for all‐solid‐state lithium batteries (ASSBs), highlighting their ionic conductivity, chemical stability, manufacturability, and compatibility with lithium metal. Sulfides offer higher conductivity, while halides provide enhanced stability and scalability.
Mohamed Djihad Bouguern +5 more
wiley +1 more source
Full P<sub>4</sub> to P<sup>3-</sup> Reduction with a Redox-Active Metal Crown Complex. [PDF]
Maurer J +5 more
europepmc +1 more source
Does N-acetyl cysteine have protective effects in acute aluminum phosphide poisoning?
Samaneh Nakhaee +2 more
openalex +2 more sources
Inverse Design in Nanophotonics via Representation Learning
This review frames machine learning (ML) in nanophotonics through a classification based on where ML is applied. We categorize methods as either output‐side, which create differentiable surrogates for solving Maxwell's partial differential equations (PDEs), or input‐side, which learn compact representations of device geometry.
Reza Marzban +2 more
wiley +1 more source
Electrocardiographic Patterns as Predictors of Mortality in Aluminum Phosphide Poisoning: A Retrospective Cohort Single-Center Study. [PDF]
Hadi N +6 more
europepmc +1 more source

