Publication2026
Machine learning-guided design and electrochemical performance of bamboo-derived activated carbon/SrFe12O19 composite as high-performance supercapacitor electrode
The record
- Type
- Publication
- Date
- 1 October 2026
- Level
- International — held abroad
- Journal
- Journal of Materials Science
- Volume
- 61
- Issue
- 38
- Pages
- 29375-29396
- Published
- 1 October 2026
- DOI
- 10.1007/s10853-026-13465-6
- Scopus ID
- 105047020815
- ISSN
- 00222461
- Authors
- 8
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- IN, TW
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Machine learning-guided design of bamboo-derived activated carbon supercapacitor electrode advances energy storage materials innovation and research capacity
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
7.2 Substantially increase the share of renewable energy in the global energy mix
Supercapacitor development contributes to modern energy access and efficiency through improved energy storage technology
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-3.1 Research and development
Research develops novel energy storage materials supporting sustainable technology advancement and innovation capacity
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “Machine learning-guided design and electrochemical performance of bamboo-derived activated carbon/SrFe12O19 composite as high-performance supercapacitor electrode”. Kortex.