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This work presents a physics-informed neural operator approach for estimating frequency-dependent surface admittance directly from near-field measurements of sound pressure and particle velocity. A deep operator network is employed to learn the mapping from measurement data, spatial coordinates, and frequency to acoustic field quantities, while simultaneously inferring a globally consistent surface admittance spectrum without requiring repeated evaluations of an explicit numerical forward model during inversion. The governing acoustic relations, including the Helmholtz equation, the linearized momentum equation, and Robin boundary conditions, are embedded into the training process as physics-based regularization, enabling physically consistent and noise-robust predictions. The method is validated using synthetically generated data from a simulation model for two planar porous absorbers under semi free-field conditions across a broad frequency range. Results demonstrate accurate reconstruction of both real and imaginary admittance components and reliable prediction of acoustic field quantities. Parameter studies confirm improved robustness to noise and sparse sampling compared to purely data-driven approaches, highlighting the potential of physics-informed neural operators for in situ acoustic material characterization.<\/jats:p>","DOI":"10.1121\/10.0046667","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T12:02:12Z","timestamp":1790856132000},"page":"2845-2858","update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Physics-informed neural operators for the\n                    <i>in situ<\/i>\n                    characterization of locally reacting sound absorbers"],"prefix":"10.1121","volume":"160","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7520-2529","authenticated-orcid":false,"given":"Jonas M.","family":"Schmid","sequence":"first","affiliation":[{"name":"Chair of Vibroacoustics of Vehicles and Machines, Technical University of Munich 1 , Garching, 85748,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7106-2407","authenticated-orcid":false,"given":"Johannes D.","family":"Schmid","sequence":"additional","affiliation":[{"name":"Chair of Vibroacoustics of Vehicles and Machines, Technical University of Munich 1 , Garching, 85748,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8839-9826","authenticated-orcid":false,"given":"Martin","family":"Eser","sequence":"additional","affiliation":[{"name":"Independent Researcher 2 , Munich 81377,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6464-8015","authenticated-orcid":false,"given":"Steffen","family":"Marburg","sequence":"additional","affiliation":[{"name":"Chair of Vibroacoustics of Vehicles and Machines, Technical University of Munich 1 , Garching, 85748,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"231","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"issue":"3","key":"2026100108020837800_c1","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.1121\/1.4788978","article-title":"Computer simulations in room acoustics: Concepts and uncertainties","volume":"133","year":"2013","journal-title":"J. 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