{"doi":"10.17615/2kvs-1s12","title":"Self-powered perovskite photon-counting detectors","abstract":"Metal-halide perovskites (MHPs) have been successfully exploited for converting photons to charges or vice versa in applications of solar cells, light-emitting diodes and solar fuels1–3, for which all these applications involve strong light. Here we show that self-powered polycrystalline perovskite photodetectors can rival the commercial silicon photomultipliers (SiPMs) for photon counting. The photon-counting capability of perovskite photon-counting detectors (PCDs) is mainly determined by shallow traps, despite that deep traps also limit charge-collection efficiency. Two shallow traps with energy depth of 5.8 ± 0.8 millielectronvolts (meV) and 57.2 ± 0.1 meV are identified in polycrystalline methylammonium lead triiodide, which mainly stay at grain boundaries and the surface, respectively. We show that these shallow traps can be reduced by grain-size enhancement and surface passivation using diphenyl sulfide, respectively. It greatly suppresses dark count rate (DCR) from >20,000 counts per second per square millimetre (cps mm−2) to 2 cps mm−2 at room temperature, enabling much better response to weak light than SiPMs. The perovskite PCDs can collect γ-ray spectra with better energy resolution than SiPMs and maintain performance at high temperatures up to 85 °C. The zero-bias operation of perovskite detectors enables no drift of noise and detection property. This study opens a new application of photon counting for perovskites that uses their unique defect properties.","journal":"UNC Libraries","year":2024,"id":499855,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9537,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1349004,"name":"Jianhua Huang","orcid":"0000-0001-5890-4297","position":1,"is_corresponding":false},{"id":1349297,"name":"Fei C","orcid":null,"position":2,"is_corresponding":false},{"id":1349005,"name":"Liang Zhao","orcid":"0000-0003-3846-505X","position":3,"is_corresponding":false},{"id":1349006,"name":"Ni Zhang","orcid":"0000-0002-3570-5452","position":4,"is_corresponding":false},{"id":1016619,"name":"Ying Zhou","orcid":"0000-0003-0252-8055","position":5,"is_corresponding":false},{"id":1349296,"name":"Uddin M.A","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:10:04.829419Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}