Teaching Structure–Property Relationships: Investigating Molecular Structure and Boiling Point

2007 ◽  
Vol 84 (1) ◽  
pp. 97 ◽  
Author(s):  
Peter M. Murphy
Keyword(s):  
Molecular Structure ◽  
Boiling Point ◽  
Structure Property ◽  
Structure Property Relationships

scholarly journals Identifying Structure-Property Relationships through SMILES Syntax Analysis With Self-Attention Mechanism

2018 ◽  
Author(s):  
Shuangjia Zheng ◽  
Xin Yan ◽  
Yuedong Yang ◽  
Jun Xu
Keyword(s):  
Molecular Structure ◽  
Attention Mechanism ◽  
Superior Performance ◽  
Data Sets ◽  
Structure Property ◽  
Structure Representation ◽  
Syntax Analysis ◽  
Structure Property Relationships ◽  
Connection Table ◽  
Structure Property Relationship

<p>Recognizing substructures and their relations embedded in a molecular structure representation is a key process for <a></a><a>structure-activity</a> or structure-property relationship (SAR/SPR) studies. A molecular structure can be either explicitly represented as a connection table (CT) or linear notation, such as SMILES, which is a language describing the connectivity of atoms in the molecular structure. Conventional SAR/SPR approaches rely on partitioning the CT into a set of predefined substructures as structural descriptors. In this work, we propose a new method to identifying SAR/SPR through linear notation (for example, SMILES) syntax analysis with self-attention mechanism, an interpretable deep learning architecture. The method has been evaluated by predicting chemical property, toxicology, and bioactivity from experimental data sets. Our results demonstrate that the method yields superior performance comparing with state-of-art methods. Moreover, the method can produce chemically interpretable results, which can be used for a chemist to design, and synthesize the activity/property improved compounds.</p>

Rational design of molecularly engineered biomimetic threshold scale inhibitors

2018 ◽  
Vol 6 (47) ◽  
pp. 24058-24065 ◽  
Author(s):  
Amir Sheikhi ◽  
Na Li ◽  
Søren Leth Mejlsøe ◽  
Enzo Bomal ◽  
Theo G. M. van de Ven ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Rational Design ◽  
Industrial Scale ◽  
Mechanistic Study ◽  
Optimum Structure ◽  
Structure Property ◽  
Structure Property Relationships

We have engineered the molecular structure of dendrimers/dendrons to provide the first mechanistic study on the structure–property relationships of macromolecular antiscalants based on which an optimum structure has been developed to prevail the performance of the most efficient industrial scale inhibitors.

Molecular Structure−Property Relationships for Electron-Transfer Rate Attenuation in Redox-Active Core Dendrimers

1999 ◽  
Vol 121 (43) ◽  
pp. 9958-9966 ◽  
Author(s):  
Christopher B. Gorman ◽  
Jennifer C. Smith ◽  
Michael W. Hager ◽  
Brandon L. Parkhurst ◽  
Hanna Sierzputowska-Gracz ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Electron Transfer ◽  
Transfer Rate ◽  
Structure Property ◽  
Electron Transfer Rate ◽  
Structure Property Relationships ◽  
Redox Active ◽  
Active Core

Structure-Performance Correlations in Electrochromic Behaviors of Terpyridine-Metal Hybrid Materials

2016 ◽  
Vol 852 ◽  
pp. 156-163 ◽  
Author(s):  
Jia Wei Yang ◽  
Xian Ge Xie ◽  
Xiao Mei Wang ◽  
Chang Qing Ye ◽  
Yu Yang Zhou
Keyword(s):  
Molecular Structure ◽  
Charge Transfer ◽  
Metal Ions ◽  
Structure Property ◽  
Reversible Change ◽  
Absorption Intensity ◽  
Coloration Efficiency ◽  
Structure Property Relationships ◽  
Ligand Charge Transfer ◽  
Terpyridine Ligands

Exploring the structure-property relationships is a fundamental but significant work for the design of new molecular. Rationaly designing of electrochromic materials that can switch rapidly and durably requires sophisticated understanding of the correlations between molecular structure and the performance. This work presents four electro-polymerizable metallosupramolecular coordinations self-assembled from triphenylamine-based terpyridine ligands and metal ions (Fe2+, Ru2+). The polymerized metal complexes can exhibit reversible change of the metal-to-ligand charge transfer (MLCT) absorption intensity. Along with the increase of voltage, the intensity of MLCT absorption peaks gradually reduced to disappear. Structure/performance correlations in electrochromic performance, especially the influence of different ligands and metal ions upon the coloration efficiency have been discussed.

scholarly journals Progressions in reasoning about structure–property relationships

2018 ◽  
Vol 19 (4) ◽  
pp. 998-1009 ◽  
Author(s):  
Vicente Talanquer
Keyword(s):  
Molecular Structure ◽  
Chemical Composition ◽  
Chemistry Education ◽  
Traditional Instruction ◽  
Structure Property ◽  
Student Reasoning ◽  
Structure Property Relationships ◽  
And Behaviors

In this essay, findings from research in science and chemistry education are used to describe and discuss progression in students' structure–property reasoning through schooling. This work provides insights into the challenges that students face to master this important component of chemical thinking. The analysis reveals that student reasoning is often guided by nonnormative implicit schemas that are little affected by traditional instruction. These schemas prioritize chemical composition over molecular structure, and centralized causality over emergence in the explanation and prediction of the properties of substances. The types of components that students invoke to make sense of properties and phenomena may change with schooling, but the underlying reasoning persists. In general, learners assume that observed properties and behaviors are directly related to the types of atoms present in a system and determined by these individual atoms' inherent characteristics.

Investigating the impact of three-dimensional learning interventions on student understanding of structure–property relationships

2021 ◽  
Author(s):  
Sonia M. Underwood ◽  
Alex T. Kararo ◽  
Gabriela Gadia
Keyword(s):  
General Chemistry ◽  
Active Learning ◽  
Boiling Point ◽  
Three Dimensional ◽  
Intermolecular Forces ◽  
Control Group ◽  
Chemistry Curriculum ◽  
Structure Property ◽  
Structure Property Relationships ◽  
The Impact

The ability to predict macroscopic properties using a compound's chemical structure is an essential idea for chemistry as well as other disciplines such as biology. In this study we investigate how different levels of interventions impact the components of students’ explanations (claims, evidence, and reasoning) of structure–property relationships, particularly related to boiling point trends. These interventions, aligned with Three-Dimensional Learning (3DL), were investigated with four different cohorts of students: Cohort 1 – a control group of students enrolled in an active learning general chemistry course; Cohort 2 – students enrolled in the same active learning general chemistry course but given Intervention 1 (a 3DL worksheet administered during class time); Cohort 3 – students enrolled in the same active learning general chemistry course but given Intervention 1 and Intervention 2 (a 3DL course exam question administered after instruction); and Cohort 4 – a reference group of students enrolled in a transformed active learning general chemistry curriculum in which 3DL is an essential feature and includes Intervention 1 and Intervention 2 as part of the curriculum. We found that Cohort 2 students (with the 3DL worksheet intervention) were more likely than the control group (Cohort 1) to correctly predict the compound with a higher boiling point as well as incorporate ideas of strength of intermolecular forces into their explanations of boiling point differences. When a 3DL exam question was given as a follow up to the 3DL worksheet, students in Cohort 3 were more likely than Cohorts 1 and 2 to correctly identify the claim. Further comparison showed that Cohort 4 (transformed general chemistry curriculum) were more likely than Cohorts 1–3 to also include the ideas of energy needed to overcome stronger forces for a more sophisticated explanation (50% of Cohort 4 students compared to 17–33% for Cohorts 1–3). In addition, 80% of Cohort 4 students were able to construct a correct representation of hydrogen bonding as a non-covalent interaction compared to 13–57% for the other three cohorts.

Sign in / Sign up

Export Citation Format

Share Document