<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-08T08:51:16Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/136750" metadataPrefix="mods">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/136750</identifier><datestamp>2026-05-19T00:19:47Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_15</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Khaouani, Mohammed</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Sessa, Andrea</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>De Stefano, Sebastiano</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Rouigueb, Hichem</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Belbachir, Mohammed Anes</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Mazzotti, Adolfo</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Pelella, Aniello</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Durante, Ofelia</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Di Bartolomeo, Antonio</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>García Hemme, Eric</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2026-05-18T18:43:07Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2026-05-18T18:43:07Z</mods:dateAccessioned>
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      <mods:dateIssued encoding="iso8601">2026-05</mods:dateIssued>
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   <mods:identifier type="citation">Khaouani, Mohammed, et al. «Experiment and Simulation in Silicon PN-Junction Photodetectors: Insights into Electrical and Optical Transport». Physica B: Condensed Matter, vol. 730, mayo de 2026, p. 418479. DOI.org (Crossref), https://doi.org/10.1016/j.physb.2026.418479.</mods:identifier>
   <mods:identifier type="issn">0921-4526</mods:identifier>
   <mods:identifier type="doi">10.1016/j.physb.2026.418479</mods:identifier>
   <mods:identifier type="uri">https://hdl.handle.net/20.500.14352/136750</mods:identifier>
   <mods:identifier type="essn">1873-2135</mods:identifier>
   <mods:identifier type="officialurl">https://dx.doi.org/10.1016/j.physb.2026.418479</mods:identifier>
   <mods:identifier type="relatedurl">https://www.sciencedirect.com/science/article/pii/S0921452626002371</mods:identifier>
   <mods:abstract>Silicon PN junctions remain central to optoelectronic technologies due to their maturity and CMOS compatibility. We report the fabrication and comprehensive optoelectronic characterization of a silicon PN-junction photodiode demonstrating stable operation over a wide temperature range. The device exhibits excellent diode behavior, with a rectification ratio exceeding four orders of magnitude, an ideality factor close to unity above 0.3 V, and a series resistance below 100 Ω. Under white-light illumination, the photodiode shows a linear photocurrent response over broad optical power and temperature ranges, achieving an average responsivity of 0.3 A W−1. We implement a machine learning framework based on an Artificial Neural Network to perform global parameter estimation, demonstrating its effectiveness in generalizing across diverse experimental datasets. Moreover, we propose a comprehensive analytical model, validated by Atlas–Silvaco simulations, that successfully captures charge transport and photogeneration mechanisms. This integrated approach, combining experimental measurements, machine learning, numerical simulations and analytical modelling, provides a robust performance benchmark and deeper insights for optimizing silicon-based optoelectronic devices.</mods:abstract>
   <mods:language>
      <mods:languageTerm>eng</mods:languageTerm>
   </mods:language>
   <mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by/4.0/</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">open access</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">Attribution 4.0 International</mods:accessCondition>
   <mods:titleInfo>
      <mods:title>Experiment and simulation in silicon PN-junction photodetectors: insights into electrical and optical transport</mods:title>
   </mods:titleInfo>
   <mods:genre>journal article</mods:genre>
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