Data · dataset · 2021
How latex film formation and adhesion at the nanoscale correlate to performance of pressure sensitive adhesives with cellulose nanocrystals
Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp2/zxb4ql
Description
Abstract
Emulsion polymerized latex-based pressure sensitive adhesives (PSAs) are more environmentally benign because they are synthesized in water but often underperform compared to their solution polymerized counterparts. Studies have shown a simultaneous improvement in the tack, and peel and shear strength of various acrylic PSAs upon the addition of cellulose nanocrystals (CNCs). This work uses atomic force microscopy (AFM) to examine the role of CNCs in (i) the coalescence of hydrophobic 2‐ethyl hexyl acrylate/n‐butyl acrylate/methyl methacrylate (EHA/BA/MMA) latex films, and (ii) as adhesion modifiers over multiple length scales.
Read the rest (5 more)
EHA/BA/MMA. Thin films with varying solids content and CNC loading were prepared by spin coating. AFM revealed that CNCs lowered the solids content threshold for latex particle coalescence during film formation.
This improved the cohesive strength of the films, which was directly reflected in the increased shear strength of the EHA/BA/MMA PSAs with increasing CNC loading. Colloidal probe AFM indicated that the nano-adhesion of thicker continuous latex films increased with CNC loading when measured over small contact areas where the effect of surface roughness was negligible. Conversely, the beneficial effects of the CNCs on macroscopic PSA tack and peel strength were outweighed by the effects of increased surface roughness with increasing CNC loading over larger surface areas.
This highlights that CNCs can improve both cohesive and adhesive PSA properties, however, the effects are most pronounced when the CNCs interact favorably with the latex polymer and are uniformly dispersed throughout the adhesive film.
Methods
MFP-3D Atomic Force Microscope (Asylum Research – Oxford Instruments, Santa Barbara, CA, USA) Igor Pro 6.0 running Asylum Research AFM software (version 13.17)
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP2%2FZXB4QL ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp2/zxb4ql ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP2%2… ↗
metadata API · from borealisdata ca
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Macromolecular and materials chemistry 72% · Microscopy 75%
Provenance · 2 source records, 21 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP2/ZXB4QL | 12 d ago | JSON v1 |
| Agri-environmental Research Data Dataverse | doi:10.5683/SP2/ZXB4QL | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3403 | enrichment · borealisdata ca | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].dataverse_subject:other | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].dataverse_subject:other | source · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[modality].local:modality:microscopy | enrichment · borealisdata ca | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |