{"paper":{"title":"Physics-Aware Machine-Learning-Driven Inverse Design of Broadband Ultra-Open Acoustic Metamaterials","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"A physics-aware machine learning framework designs ultra-open acoustic silencers achieving over 830 Hz broadband bandwidth with 80 percent ventilation in ultra-thin profiles.","cross_cats":[],"primary_cat":"physics.app-ph","authors_text":"Ao Chen, Mengyu Li, Thomas G. Bifano, Xiaohang Xie, Xin Zhang, Zhiwei Yang","submitted_at":"2026-05-15T15:06:06Z","abstract_excerpt":"Ventilated acoustic silencers combing sound attenuation with high ventilation are pivotal for advanced noise control. However, balancing attenuation, bandwidth, openness, and thickness remains a high-dimensional challenge. Here, we report a physics-aware machine-learning-driven inverse design framework for ultra-open acoustic silencers (UAS). By leveraging Green's function-based parameterization, we physically decouple the design space into spectral and radial parameters, ensuring physical interpretability while reducing complexity. We introduce a two-stage forward prediction architecture that"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Results confirm a broadband bandwidth exceeding 830 Hz achieved with an ultra-thin profile (0.1-0.2λ) and 80% ventilation using the proposed UAS designs and parallel-composite architecture.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The Green's function-based parameterization physically decouples the design space into spectral and radial parameters, ensuring physical interpretability while reducing complexity (abstract, paragraph on framework).","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Physics-aware ML inverse design framework for ultra-open acoustic silencers that experimentally achieves over 830 Hz broadband attenuation with 80% ventilation in 0.1-0.2 wavelength thick monolithic and composite prototypes.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A physics-aware machine learning framework designs ultra-open acoustic silencers achieving over 830 Hz broadband bandwidth with 80 percent ventilation in ultra-thin profiles.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"3b540d4c59e5e663f11d4b8e529bc96ee10171c05d191875ce9fb00d801364c8"},"source":{"id":"2605.16031","kind":"arxiv","version":1},"verdict":{"id":"b3070566-98b5-41e0-95c0-6377cc0bd42e","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T17:20:43.049706Z","strongest_claim":"Results confirm a broadband bandwidth exceeding 830 Hz achieved with an ultra-thin profile (0.1-0.2λ) and 80% ventilation using the proposed UAS designs and parallel-composite architecture.","one_line_summary":"Physics-aware ML inverse design framework for ultra-open acoustic silencers that experimentally achieves over 830 Hz broadband attenuation with 80% ventilation in 0.1-0.2 wavelength thick monolithic and composite prototypes.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The Green's function-based parameterization physically decouples the design space into spectral and radial parameters, ensuring physical interpretability while reducing complexity (abstract, paragraph on framework).","pith_extraction_headline":"A physics-aware machine learning framework designs ultra-open acoustic silencers achieving over 830 Hz broadband bandwidth with 80 percent ventilation in ultra-thin profiles."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.16031/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:42.149284Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_title_agreement","ran_at":"2026-05-19T17:31:18.432464Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T17:26:19.283781Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T16:41:55.543161Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"560bfe88699a80bfe42340731fa2edc07d7322b93bcf406c750e96965f14faf5"},"references":{"count":58,"sample":[{"doi":"","year":2019,"title":"Noise pollution","work_id":"b0a5bcd8-7ec9-4dd4-ba4f-9caaa835fb8e","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2022,"title":"Thompson, R., Smith, R. B., Karim, Y. B., Shen, C., Drummond, K., Teng, C. & Toledano, M. B. Noise pollution and human cognition: An updated systematic review and meta- analysis of recent evidence. En","work_id":"df27b846-c594-41a7-9ee9-622f3033134f","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"& Wang, Y.- S","work_id":"563da16a-a05c-4c65-86c0-dc9196b632db","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2016,"title":"Ma, G. & Sheng, P. Acoustic metamaterials: From local resonances to broad horizons. Science Advances 2(2), e1501595 (2016)","work_id":"a6af6802-a213-4d94-a80c-0765212fcbec","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2016,"title":"Cummer, S. A., Christensen, J. & Alù, A. Controlling sound with acoustic metamaterials. Nature Reviews Materials 1(3), 1–13 (2016)","work_id":"6ee7a973-60a2-45c5-95aa-00b7c58729e5","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":58,"snapshot_sha256":"1f960a5c61ce718198a56dc4ce3e3f1b145fc7b040c85993aec1411a3473e795","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"3d468d2a8bf2f762cda65ecea3102502d6f6f79771cd24270eb1ee58fa18f9e2"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}