Graphene-Wrapped Silicon Nanoparticles for All-Solid-State Lithium-Ion Batteries
Bibliographic record
Abstract
Current lithium-ion batteries consist of a graphite anode and a metal oxide cathode. Due to their relatively high energy density and rechargeability, they have enabled various applications over the past few decades. However, significant improvements to battery cost, performance, and safety for applications such as vehicle electrification require a shift to next-generation materials, such as silicon as an anode which offers higher capacity, as well as solid-state electrolytes (SSEs) which are non-flammable. Both of these technologies currently suffer challenges which have prevented their widespread adoption. Silicon suffers low conductivity, and large volume change on each cycle, subsequently causing loss in electrical contact and the formation of an unstable solid electrolyte interface (SEI) each cycle. This project aims to solve these challenges by wrapping silicon nanoparticles and a sacrificial spacing material with crumpled graphene sheets using a scalable, spray drying method, and coupling it with a solid electrolyte. The graphene shell provides electrical contact with the silicon and space for its expansion during lithiation. The solid electrolyte provides a safer alternative to liquid electrolytes, and further reduces the SEI formation which, with a liquid electrolyte, can leak into such crumpled structures. In this work we will present our initial results concerning the engineering of void space within the shell’s core while simultaneously improving its conductivity to maximize the achievable capacity and cycle life. We will explore different spacing material candidates such as chitosan which, upon heat treatment of the sample, would not only provide space for the expansion of silicon, but the residual nitrogen-doped carbon would also act as a conductive filler inside the crumpled structure. We will also present our initial work involving the solid electrolyte synthesis including an investigation of the effect of solvents on the structure of the electrolyte as well as powder mixing and solution infiltration methods to introduce high conductivity SSEs and their performance when coupled to the graphene-wrapped silicon anode structures.
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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 | 0.000 |
| 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".