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Record W4414056186 · doi:10.1016/j.rineng.2025.107168

Modification strategies of conductive polymers with advanced carbon materials for energy and environmental solutions

2025· article· en· W4414056186 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResults in Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Materials Science
Canadian institutionsnot available
FundersUniversity of Toronto MississaugaUniversiti Tenaga NasionalUniversiti Kebangsaan MalaysiaMinistry of Higher Education, MalaysiaTenaga Nasional Berhad
KeywordsEnvironmental remediationNanocompositePhotocatalysisHydrogen productionOxygen evolutionCarbon fibersEnergy storageGroundwater remediation

Abstract

fetched live from OpenAlex

• CP–CNS nanocomposites offer enhanced pollutant removal and water purification. • Photocatalytic H₂ production shows high efficiency with tailored nanostructures. • Functionalized composites show improved CO₂ capture and conversion to fuels. • CP–CNS hybrids achieve over 90 % degradation for dyes, metals, and drugs. Environmental remediation has become an urgent necessity, with water security emerging as a primary global concern. To address this challenge, the development of affordable and sustainable materials is essential, particularly for improving accessibility in remote regions. Among emerging candidates, Conductive Polymers (CPs) have gained significant attention due to their sustainable synthesis using mild chemicals and their ability to bypass energy-intensive processing routes. The delocalization of π-electrons along their conjugated backbones enables efficient charge transport, allowing them to function as photocatalysts while simultaneously adsorbing pollutants. This dual property not only supports environmental remediation but also extends their application to energy generation and storage technologies. Another promising class of materials, Carbon Nanostructures (CNS), offers excellent charge transfer rates and structural tunability. However, their high production cost often limits large-scale applications. To overcome these limitations, recent studies have explored the synergy between CPs and CNS, leading to the design of advanced composites through methods such as in situ polymerization, electrodeposition, and aerogelization. These hybrid materials have demonstrated superior photocatalytic performance, making them attractive for fabricating electrodes used in various remediation strategies. Such electrodes have been successfully applied in hydrogen and oxygen evolution reactions, carbon dioxide capture, dye degradation, and the removal of heavy metals and pharmaceuticals. Beyond environmental cleanup, processes like hydrogen and oxygen evolution also provide alternative energy pathways, thereby linking remediation with sustainable energy production. This review highlights recent developments, along with other innovative materials and waste valorization strategies, underscoring their potential in fostering a greener and more resilient ecology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.200
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it