PATENT CLAIM ANALYSIS

Application Number: 16092130
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-05
Patent Classification: ["423", "447100"]

Abstract:
Discrete, individualized carbon nanotubes having targeted, or selective, oxidation levels and/or content on the interior and exterior of the tube walls are claimed. Such carbon nanotubes can have little to no inner tube surface oxidation, or differing amounts and/or types of oxidation between the tubes' inner and outer surfaces. These new discrete carbon nanotubes are useful in plasticizers, which can then be used as an additive in compounding and formulation of elastomeric, thermoplastic and thermoset composite for improvement of mechanical, electrical and thermal properties.

Claim (Index 1):
A composition comprising a plurality of discrete carbon nanotubes, wherein the discrete carbon nanotubes comprise an interior and exterior surface, the interior surface comprising an interior surface oxidized species content and the exterior surface comprising an exterior surface oxidized species content, wherein the interior surface oxidized species content comprises from about 0.01 to less than about 1 percent relative to carbon nanotube weight and the exterior surface oxidized species content comprises more than about 1 to about 3 percent relative to carbon nanotube weight.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 97.0
- Lexical Diversity: 1.46154
- Patent Class: 423.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15730284', '15778444', '14628248', '15166931', '15840174']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7450955830176006
- 35 USC 102 Novelty (BERT): 0.5579686378475368
- Combined Prediction Score: 0.7263828885005942
- Mean Citation Score: 296.0907820000001
- Max Citation Score: 423.49106
- Similarity Product: 335.9261152246702

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test