Enabling Green Fabrication of Li-Ion Battery Electrodes by Electrophoretic Deposition: Growth of Thick Binder-Free Mesoporous TiO<sub>2</sub>-Carbon Anode Films
Bibliographic record
Abstract
In this work the potential of employing electrophoretic deposition (EPD) for fabricating Li-ion battery electrodes without using binders and in particular eliminating volatile and toxic organic solvents such as n-methyl 2-pyrrolidone (NMP) is demonstrated. The paper in particular describes the successful application of the EPD method to fabrication of thick ( > 20 μm) nano-TiO 2 /carbon Li-ion intercalation anodes. The EPD system involves deposition of commercial P25 TiO 2 nanoparticles and carbon black on aluminum foil from an isopropanol bath without making use of charging agents or other additives. Hetero-coagulation of TiO 2 and C particles in the isopropanol medium enabled their 80 V DC cathodic deposition into a well-adhered film with effective intermixing of active and conductive components. Electrochemical testing of the newly binder-free EPD-built electrodes revealed comparable film conductivity, polarization and charge storage capacity properties with the standard binder-based PVDF/NMP electrodes. Most importantly, the charge storage, cycling, and rate properties of the EPD-built electrodes were greatly enhanced by post-EPD sintering of the film at 450°C. The combined EPD-sintering route resulted in a superior conductive percolating network by promoting nanoscale film composition uniformity, inter-particle necking, and favorable porous structure for enhanced interfacing with the liquid electrolyte. The sintered EPD-built electrode exhibited almost 50% higher capacity retention than that of the standard binder-based electrode upon cycling. EPD with its inherent self-assembling functionality and its overall operational simplicity provides an advantageous and green Li-ion electrode fabrication alternative.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".