Hetero-polycyclic aromatic systems: A data-driven investigation of structure–property relationships [PDF]
Polycyclic aromatic systems (PASs) are pervasive compounds that have a substantial impact in chemistry and materials science. Although their specific structure–property relationships hold the key to the design of new functional molecules, a detailed ...
Sabyasachi Chakraborty +2 more
doaj +3 more sources
Functional Dithienopyrazines – Structure-Property Relationships [PDF]
Dithienopyrazines are only scarcly used as building blocks in organic electronic materials. Here, we report efficient preparation and investigation of syn- and anti-dithienopyrazines, which were functionalized with triaraylamine units to provide ...
Elena, Mena-Osteritz +2 more
core +2 more sources
Viologen Hydrothermal Synthesis and Structure-Property Relationships for Redox Flow Battery Optimization [PDF]
Aqueous organic redox flow batteries (AORFBs) are an emerging technology for fire safe grid energy storage systems with sustainable material feedstocks.
HongHao, Liu +5 more
core +2 more sources
The Influence of molecular design on structure-property relationships of a supramolecular polymer prodrug [PDF]
Supramolecular self-assemblies of hydrophilic macromolecules functionalized with hydrophobic, structure-directing components have long been used for drug delivery.
Joakim, Engström +7 more
core +2 more sources
Quantitative Structure-Property Relationships (QSPR) to Predict Surface Tension and Electrical Conductivity of Ionic Liquid Propellants [PDF]
Quantitative structure property relationships (QSPR) mine data sets of experimentally measured properties to predict different material properties through mathematical regression and machine learning.
Steven D., Chambreau +4 more
core +1 more source
Interpretable Deep-Learning Unveils Structure-Property Relationships in Polybenzenoid Hydrocarbons [PDF]
In this work, interpretable deep learning was used to identify structure-property relationships governing the HOMO-LUMO gap and relative stability of polybenzenoid hydrocarbons (PBHs). To this end, a ring-based graph representation was used.
Alex M., Bronstein +3 more
core +2 more sources
Theoretical Understanding of Structure-Property Relationships in Luminescence of Carbon Dots
Carbon dots (CDs) have excellent luminescence characteristics, such as good light stability, high quantum yield (QY), long phosphorescence lifetime, and a wide emission wavelength range, resulting in CDs' great success in optical applications ...
Tang, Zhiyong +4 more
core +1 more source
Predicting Surface Tensions and Electrical Conductivities for High Molecular Weight Ionic Liquid Propellants Using Quantitative Structure-Property Relationships (QSPR) [PDF]
Quantitative Structure-Property Relationships (QSPR) take in existing experimental property data and output predicted properties using statistical analysis and linear regressions.
Steven D., Chambreau +4 more
core +1 more source
This dataset provides raw data to reproduce the structure-property relationships.
Atul Chauhan (11771060)
core +1 more source
Evaluating Polymer Representations via Quantifying Structure-Property Relationships [PDF]
Machine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly representing materials plays key roles.
zhiyu, liu +4 more
core +1 more source

