ReviewAdvanced materials (Deerfield Beach, Fla.)2019
Multiscale Design of Graphyne-Based Materials for High-Performance Separation Membranes.
Review in Advanced materials (Deerfield Beach, Fla.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- A cutting-edge neural network approach for predicting the thermoelectric efficiency of defective gamma-graphyne nanoribbons.Scientific reports · 2025Article
- Recent advances on graphyne and its family members as membrane materials for water purification and desalination.Frontiers in chemistry · 2023Review
- Cross-Linked Networks of 1,6-Hexanedithiol with Gold Nanoparticles to Improve Permeation Flux of Polyethersulfone Membrane.Membranes · 2022Article
- Helium Isotopes Quantum Sieving through Graphtriyne Membranes.Nanomaterials (Basel, Switzerland) · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
By varying the number of acetylenic linkages connecting aromatic rings, a new family of atomically thin graph-n-yne materials can be designed and synthesized. Generating immense scientific interest due to its structural diversity and excellent physical properties, graph-n-yne has opened new avenues toward numerous promising engineering applications, especially for separation membranes with precise pore sizes. Having these tunable pore sizes in combination with their excellent mechanical strength to withstand high pressures, free-standing graph-n-yne is theoretically posited to be an outstanding membrane material for separating or purifying mixtures of either gases or liquids, rivaling or even dramatically exceeding the capabilities of current, state-of-art separation membranes. Computational modeling and simulations play an integral role in the bottom-up design and characterization of these graph-n-yne materials. Thus, here, the state of the art in modeling α-, β-, γ-, δ-, and 6,6,12-graphyne nanosheets for synthesizing graph-2-yne materials and 3D architectures thereof is discussed. Different synthesis methods are described and a broad overview of computational characterizations of graph-n-yne's electrical, chemical, and thermal properties is provided. Furthermore, a series of in-depth computational studies that delve into the specifics of graph-n-yne's mechanical strength and porosity, which confer superior performance for separation and desalination membranes, are reviewed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.