Publications by authors named "Jaime A Benavides"
Article Synopsis
- Emerging machine learning techniques, specifically deep learning, are being utilized to enhance Raman spectroscopy for the identification of minerals, focusing on complex polymorph structures.
- A new framework employing Convolutional Neural Networks and Long Short-Term Memory networks was developed and validated using the RRUFF spectral database and synthesized TiO polymorphs.
- The results indicate that the model can accurately identify different TiO structures, including pure and defect-rich variants, which may lead to increased efficiency and reduced costs in mineral analysis.
We report significantly improved silicon nanowire/TiO n-n heterojunction solar cells prepared by sol-gel synthesis of TiO thin film atop vertically aligned silicon nanowire arrays obtained by facile metal-assisted wet electroless chemical etching of a bulk highly doped n-type silicon wafer. As we show here, chemical treatment of the nanowire arrays prior to depositing the sol-gel precursor has dramatic consequences on the device performance. While hydrofluoric treatment to remove the native oxide already improves significantly the device performances, hydrobromic (HBr) treatment consistently yields by far the best device performances with power conversion efficiencies ranging between 4.
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