ReviewJACS Au2024
Organic Semiconducting Polymers for Augmenting Biosynthesis and Bioconversion.
Review in JACS Au, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Organic Materials for Biohybrid Photocatalysis and Photoelectrochemical Devices.Chemical reviews · 2026Review
- Designing Microbe-Semiconductor Interfaces for Semibiological Photosynthesis.Chemical reviews · 2026Review
- Biointerface interaction regulation based on organic semiconducting polymers.Fundamental research · 2026Review
- Regulation of Calcium Ion Channels with Conjugated Molecules for Modulating Biological Functions.ACS central science · 2025Review
- Bulky Group Shaping Cyanine as an Efficient Photosensitizer: A Photo-Inducer for Photodynamic Immunotherapy.JACS Au · 2025Article
- Single-atom bridges across biotic-abiotic interfaces facilitate direct electron transfer for solar-to-chemical conversion.Nature communications · 2025Article
- Recent Progress in Designing Nanomaterial Biohybrids for Artificial Photosynthesis.Nanomaterials (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Solar-driven biosynthesis and bioconversion are essential for achieving sustainable resources and renewable energy. These processes harness solar energy to produce biomass, chemicals, and fuels. While they offer promising avenues, some challenges and limitations should be investigated and addressed for their improvement and widespread adoption. These include the low utilization of light energy, the inadequate selectivity of products, and the limited utilization of inorganic carbon/nitrogen sources. Organic semiconducting polymers offer a promising solution to these challenges by collaborating with natural microorganisms and developing artificial photosynthetic biohybrid systems. In this Perspective, we highlight the latest advancements in the use of appropriate organic semiconducting polymers to construct artificial photosynthetic biohybrid systems. We focus on how these systems can enhance the natural photosynthetic efficiency of photosynthetic organisms, create artificial photosynthesis capability of nonphotosynthetic organisms, and customize the value-added chemicals of photosynthetic synthesis. By examining the structure-activity relationships and emphasizing the mechanism of electron transfer based on organic semiconducting polymers in artificial photosynthetic biohybrid systems, we aim to shed light on the potential of this novel strategy for artificial photosynthetic biohybrid systems. Notably, these coupling strategies between organic semiconducting polymers and organisms during artificial photosynthetic biohybrid systems will pave the way for a more sustainable future with solar fuels and chemicals.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.