Machine learning for RNA secondary structure prediction: a review of current methods and challenges. [PDF]
Sacco G, Bussi G, Sanguinetti G.
europepmc +1 more source
Electrolyte Additive Strategies in Aqueous Zn‐Ion Batteries: Recent Advances and Prospects
This article provides a comprehensive overview of the current status and future development directions of AZIBs electrolyte additives in three aspects: stabilizing zinc anodes (uniform deposition, inhibition of dendritic crystals), protecting cathodes (structural stability, inhibition of dissolution), and enhancing electrolyte stability (wider ...
Yuanze Yu +7 more
wiley +1 more source
A one‐step, asymmetric reductive coupling of alkynes and oxa‐ and aza‐bicyclic olefins using a cobalt/photoredox catalytic system through desymmetrization. ABSTRACT Bicyclo[2.2.1]heptane frameworks represent a privileged structural motif prevalent in numerous natural products and bioactive molecules.
Subhankar Pradhan +5 more
wiley +1 more source
In-silico prediction of multi‑target mechanisms of Pinellia ternata phytochemicals in lung cancer: Evidence from a graph‑attention‑guided virtual screening and multi‑scale simulations. [PDF]
Bian G +9 more
europepmc +1 more source
ABSTRACT Hydrogen sulfide (H2S) can be transformed into hydrogen (H2) through several chemical and catalytic processes, offering a promising route for both waste treatment and clean H2 production. This colorless, flammable, and toxic gas is found abundantly in swamps, volcanoes, hot springs, sewages, other natural gas fields, and even in refineries and
Divyesh Cirikonda +4 more
wiley +1 more source
Navigating polymorph generation and distilled-potential development via entropy-symmetry landscapes for metal plasticity mechanisms. [PDF]
Li Z +10 more
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Development and evaluation of an effective solubility prediction model for pharmaceuticals in organic solvents using machine learning based on eXtreme Gradient Boosting. [PDF]
Valavi M +3 more
europepmc +1 more source
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren +8 more
wiley +1 more source

