Microsized Electrochemical Energy Storage Devices and Their Fabrication Techniques For Portable Applications
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.
Bibliographic record
Abstract
Abstract Over the last decade, Lab‐on‐chip (LOC) technology has been thriving to support the ever‐increasing demand of high‐throughput, fast, accurate, and reliable analysis in an extensive variety of miniaturized systems for medical, chemical, and biological applications. Furthermore, portable electronics and consumer devices such as cell phones, tablets, smart watches, point‐of‐care devices, wireless sensor nodes, radio frequency identification, and other gadgets have witnessed a tremendous demand worldwide. These fast‐paced technologies have an intimate correlation with the booming research activity in micro‐supercapacitors (MSCs) and microbatteries (MBs); two energy storage devices which have claimed the lion's share in powering LOC components and other portable devices. In this review, MSCs and MBs are presented with highlights on their main components, structure, and types, as well as their state‐of‐the‐art performance capabilities. The recent efforts in fabrication strategies, mainly those compatible with device fabrication techniques, stating the advantages and limitations of each are also reviewed. The paper also emphasizes the need for a benchmarking standard upon which performance is compared, as scholarly work shows a discrepancy in the use of different performance metrics to describe the electrochemical performance of such devices.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it