Recent Advances in the Unconventional Design of Electrochemical Energy Storage and Conversion Devices
Bibliographic record
Abstract
Abstract As the world works to move away from traditional energy sources, effective efficient energy storage devices have become a key factor for success. The emergence of unconventional electrochemical energy storage devices, including hybrid batteries, hybrid redox flow cells and bacterial batteries, is part of the solution. These alternative electrochemical cell configurations provide materials and operating condition flexibility while offering high-energy conversion efficiency and modularity of design-to-design devices. The power of these diverse devices ranges from a few milliwatts to several megawatts. Manufacturing durable electronic and point-of-care devices is possible due to the development of all-solid-state batteries with efficient electrodes for long cycling and high energy density. New batteries made of earth-abundant metal ions are approaching the capacity of lithium-ion batteries. Costs are being reduced with the advent of flow batteries with engineered redox molecules for high energy density and membrane-free power generating electrochemical cells, which utilize liquid dynamics and interfaces (solid, liquid, and gaseous) for electrolyte separation. These batteries support electrode regeneration strategies for chemical and bio-batteries reducing battery energy costs. Other batteries have different benefits, e.g., carbon-neutral Li-CO2batteries consume CO2and generate power, offering dual-purpose energy storage and carbon sequestration. This work considers the recent technological advances of energy storage devices. Their transition from conventional to unconventional battery designs is examined to identify operational flexibilities, overall energy storage/conversion efficiency and application compatibility. Finally, a list of facilities for large-scale deployment of major electrochemical energy storage routes is provided. Graphical abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".