Studies of Si-Fe-C Electrode Materials Prepared By Combinatorial Sputter Deposition
Bibliographic record
Abstract
Introduction Based on our previous studies (e.g. [1]) and other work [2], it is our opinion that silicon-based amorphous alloys are promising for use as a negative electrode. This is due to the fact that the volume expansion of amorphous silicon (a-Si) upon Li insertion is homogeneous and causes less pulverization as compared to the crystalline material. In addition to the homogenous expansion, the two-phase regions are inhibited once a-Si is used. Herein, a combinatorial study, on Si-Fe-C sputtered films covering a wide range of compositions is presented. The intention is to study the effect of both Fe and C within the electrode on the electrochemical performance. Carbon was added in the hope that some carbon would remain “free” and could transport intercalated Li effectively to the interior of the particles, whereas iron can form an inactive matrix that reduces the overall volume expansion. Experimental Four combinatorial libraries in the Si-Fe-C system were produced using a Corona Vacuum Coaters model V3-T multi-target sputtering system described in [3]. Different targets, two inches in diameter, were used: a Si target, an Fe target and a C target. The targets and a plasma scrubber were mounted on magnetrons. The desired deposition profile was be achieved by using different stationary masks placed over the targets. Figure 1 summarizes the produced compositions. X-ray diffraction was used to study the structure of these libraries and Mossbauer spectroscopy was employed to probe the atomic environment. Cyclic voltammetry measurements were performed using a multichannel pseudopotentiostat to study the behavior of these materials as negative electrodes for Li-ion batteries Results and Discussion Structural Studies: X-ray patterns obtained from all compositions produced in this study were amorphous or nanostructured and no Bragg peaks indicative of any crystalline phases. In order to understand the microstructure, as XRD measurements provide little detailed structural information, room temperature Mössbauer spectroscopy was performed on two libraries denoted by solid triangles and circles. The formation of Si-Fe phases were evident. Electrochemical Analysis: Figure 1(b) shows the potential versus capacity of the library denoted by the solid circles in Figure 1(a). Data for 64 electrode material are shown. Our combinatorial measurement setup allows for a simultaneous and rapid measurement. The impact of adding iron and carbon on the resulting capacity is illustrated clearly in Figure 1(b). Through a combined consideration of Mössbauer effect measurements and electrochemical data, the formation of nanoscale regions of inactive Si-Fe and SiC phases was evident.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".