{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T13:11:32Z","timestamp":1789996292670,"version":"4.0.1"},"reference-count":91,"publisher":"AIP Publishing","issue":"9","content-domain":{"domain":["pubs.aip.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:p>Laser-Induced Breakdown Spectroscopy (LIBS) is an atomic emission technique that is proven to be a versatile tool for fast multi-elemental analysis in various scientific and industrial applications. It offers a number of major advantages, such as minimal sample preparation requirements and real-time detection capability, including the detection of solids, liquids, gases, and aerosols; but its analytical performance is currently limited by low sensitivity, fluctuations in the spectra, matrix effects, and relatively high limits of detection (LOD). To address these challenges, significant progress has been made in developing LIBS enhancement strategies and optimizing experimental parameters. This Review covers key LIBS signal improvement strategies, such as double-pulse LIBS, nanoparticle-enhanced LIBS, magnetic field-assisted LIBS, electric field-assisted LIBS, and methods involving changes to the atmosphere\/ambient conditions. Moreover, the systematic effect of essential experimental parameters, such as laser pulse energy, laser pulse duration, repetition rate, gate delay, and integration time, is critically discussed. The physical principles behind the plasma formation, excitation processes, and emission characteristics are discussed to illustrate their contribution to signal enhancement and analytical capabilities. Finally, recent challenges and future research prospects are presented, focusing on introducing hybrid LIBS setups, developing AI-driven optimization, and creating portable high sensitivity sensors for ultra-trace detection. This Review aims to provide a unified understanding of LIBS enhancement methodologies and guide future developments toward improved sensitivity, stability, and quantitative reliability.<\/jats:p>","DOI":"10.1063\/5.0346085","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:42:34Z","timestamp":1789994554000},"update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Signal enhancement in laser-induced breakdown spectroscopy for improved sensitivity and detection limits: Mechanisms and prospects"],"prefix":"10.1063","volume":"97","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0179-7279","authenticated-orcid":false,"given":"Muhammad","family":"Faheem","sequence":"first","affiliation":[{"name":"Laser Spectroscopy Lab, Department of Physics, University of Agriculture , Faisalabad 38090,","place":["Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9015-4381","authenticated-orcid":false,"given":"Faisal","family":"Hayat","sequence":"additional","affiliation":[{"name":"Laser Spectroscopy Lab, Department of Physics, University of Agriculture , Faisalabad 38090,","place":["Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9799-3233","authenticated-orcid":false,"given":"Ghulam Rasool","family":"Sani","sequence":"additional","affiliation":[{"name":"Laser Spectroscopy Lab, Department of Physics, University of Agriculture , Faisalabad 38090,","place":["Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5903-0835","authenticated-orcid":false,"given":"Yasir","family":"Jamil","sequence":"additional","affiliation":[{"name":"Laser Spectroscopy Lab, Department of Physics, University of Agriculture , Faisalabad 38090,","place":["Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"317","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"issue":"January","key":"2026092108411137700_c1","doi-asserted-by":"publisher","first-page":"128073","DOI":"10.1016\/j.talanta.2025.128073","article-title":"Machine learning assisted LIBS classification of burnt and unburnt paper samples: A forensic perspective","volume":"293","year":"2025","journal-title":"Talanta"},{"key":"2026092108411137700_c2","doi-asserted-by":"publisher","first-page":"015187","DOI":"10.1007\/s13369-025-09977-z","article-title":"Predictive insights from machine learning-assisted laser-induced breakdown spectroscopy of lanthanum substituted Bismuth Ferrite","volume":"50","year":"2025","journal-title":"Arab. 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