Table · dataset · 2026
Data for A non-destructive method to infer the bulk lifetime in high quality silicon wafers
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The bulk lifetime (τbulk) of high-quality silicon wafers is becoming ever more important as the efficiency of the solar cells increases (i.e. >27 %).
Description
As such there is a growing necessity to measure τbulk directly. In this work, we showcase a non-destructive technique to infer τbulk of high-quality wafers, termed the Charge Decoupling Method.
This method is very simple and only requires atomic layer deposited (ALD) aluminium oxide (Al2O3)—or any other highly charged film (e.g. >1012 q cm−2)—and corona charging. By measuring the decay in the effective lifetime as the net negative charge decreases—due to the sequential deposition of positive corona charges—we can quantify the shape of the curve—analogous to the fill factor for a solar cell—and from this, determine the injection-dependent τbulk and surface recombination velocity S. To experimentally verify the method, we apply the charge decoupling method to Al2O3 passivated Czochralski-grown 5 Ω cm, n-type, 150 μm thick silicon wafers.
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From this we obtain a τbulk of ∼30 ms and a corresponding S of 0.2 cm−1 at an injection level of ∼1015 cm−3. Mathematically, we demonstrate that the charge decoupling method depends solely on the ratio of surface to bulk recombination and thus does not depend on the doping type, resistivity, charge density, wafer thickness, interface defect density and the injection-dependent bulk lifetime.<br><br>Measurements of bulk lifetime (tau_bulk) of high-quality silicon wafers in solar cells.
This data supports a publication showcasing the Charge Decoupling Method of non-destructively inferring tau_bulk.
Links
Where it is published
- DOI doi.org/10.82444/warw.33909466.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
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- Astronomy & Astrophysics · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science
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- Electronics, sensors and digital hardware 69%
Provenance · 1 source records, 17 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/33909466 | 12 d ago | JSON v1 |
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