Research data from a 2024 study investigating the mechanisms of mechanical fatigue versus toughness in elastomers. The dataset, authored by Gabriel Sanoja and hosted by the Texas Data Repository, likely contains quantified measurements of damage from polymer chain scission under cyclic and monotonic loading. The work aims to inform the engineering of fatigue-resistant elastomers and reduce the environmental footprint of the polymer industry.
Use Cases
- Modeling the relationship between reversible elasticity and fatigue resistance based on the described low/intermediate strain behavior.
- Analyzing the role of energy dissipation at high strains in controlling toughness, as mentioned in the description.
- Comparing damage spatial localization and fracture surface characteristics under cyclic versus monotonic loading conditions.
- Informing the design of double-network elastomers based on quantified sacrificial bond scission data.
Strengths
- Data is derived from a controlled experimental setup using mechanofluorescent probes to quantify damage.
- The study explicitly addresses a key gap in understanding fatigue crack propagation in elastomers experiencing 10-100 million cycles.
- Last updated on 2024 03 18, indicating recent availability.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and dataset scale are unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Texas Data Repository Harvested Dataverse
- Collection Method
- Experimental data from tagged double-network elastomers with mechanofluorescent probes under cyclic and monotonic loading.
- Time Range
- 2024
- Freshness
- Last updated 2024-03-18 11:26:16; freshness should be verified.
- Geography
- null