HAL (France)
open access
Machine Learning‐Assisted Optimization of Iodide Electrolytes for Efficient Indoor Dye‐Sensitized Solar Cells with Engineered Photoanodes
Although dye‐sensitized solar cells (DSSCs) have lower power conversion efficiencies than other emerging photovoltaic technologies under standard test conditions, they perform remarkably well under low light or artificial lighting. This makes them particularly well suited to indoor photovoltaics (IP
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Successive ionic layer adsorption and reaction (SILAR) -driven cobalt oxide integration on pencil graphite for efficient electrochemical oxygen evolution reaction in alkaline medium.#415475
- ECLectic. WP2 Electrochemiluminescence Mechanism Performance Optimisation. T2.1 Optimization Reagents#271154
- Pyrophosphate Na 2 CoP 2 O 7 Polymorphs as Efficient Bifunctional Oxygen Electrocatalysts for Zinc–Air Batteries#156329
- Electrolyte Color Manipulation Enables a New Paradigm of a Color-Gated Organic Photoelectrochemical Transistor#664977
- A machine learning quest to design benzodithiophene-based organic solar cell heterojunction layers with promising molecular packing#658800
Record · ID 1166388
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive