Jishan Wu, Yara Suleiman, Jinlong He, Minhao Xiao, Parisa Mahyari, Mingzhe Li, Lin Zhou, Yuanmiaoliang Chen, Hanqing Fan, N. A. Sreejith, Hariswaran Sitaraman, Marc Day, Ying Li, Jeffrey R. McCutcheon, Menachem Elimelech, Sina Shahbazmohamadi* and Eric M. V. Hoek*,
{"title":"基于ai分割增强的薄膜复合膜压实的无损操作成像","authors":"Jishan Wu, Yara Suleiman, Jinlong He, Minhao Xiao, Parisa Mahyari, Mingzhe Li, Lin Zhou, Yuanmiaoliang Chen, Hanqing Fan, N. A. Sreejith, Hariswaran Sitaraman, Marc Day, Ying Li, Jeffrey R. McCutcheon, Menachem Elimelech, Sina Shahbazmohamadi* and Eric M. V. Hoek*, ","doi":"10.1021/acs.estlett.5c00529","DOIUrl":null,"url":null,"abstract":"<p >Reverse osmosis (RO) membranes are essential for desalination and water reuse, yet their permeability declines in high-pressure applications due to membrane compaction. This study investigates the structural and functional responses of commercial brackish, seawater, and high-pressure RO membranes at applied pressures up to 120 bar using a multiscale, nondestructive <i>in operando</i> scanning electron microscopy (<i>i</i>SEM) imaging platform. The <i>i</i>SEM technique reveals progressive densification across the composite membrane structure, which correlates with observed declines in water and solute permeance. To quantify these structural changes with greater fidelity, we combined X-ray computed tomography with AI-based segmentation enabling precise analysis of pore size distribution and thickness of the polysulfone support layer. Compared to traditional thresholding, AI segmentation accurately delineates material phases and void spaces, enhancing the reproducibility and resolution of morphological assessments. The results demonstrate that compaction-induced reductions in porosity and thickness strongly impact membrane transport properties. These findings provide mechanistic insights into the compaction behavior of RO membranes and underscore the potential for advanced imaging and AI-driven data analysis to guide the design of next-generation membranes with improved mechanical resilience and operational longevity.</p>","PeriodicalId":37,"journal":{"name":"Environmental Science & Technology Letters Environ.","volume":"12 8","pages":"1069–1074"},"PeriodicalIF":8.8000,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nondestructive In Operando Imaging of Thin Film Composite Membrane Compaction Enhanced by AI-Based Segmentation\",\"authors\":\"Jishan Wu, Yara Suleiman, Jinlong He, Minhao Xiao, Parisa Mahyari, Mingzhe Li, Lin Zhou, Yuanmiaoliang Chen, Hanqing Fan, N. A. Sreejith, Hariswaran Sitaraman, Marc Day, Ying Li, Jeffrey R. McCutcheon, Menachem Elimelech, Sina Shahbazmohamadi* and Eric M. V. Hoek*, \",\"doi\":\"10.1021/acs.estlett.5c00529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Reverse osmosis (RO) membranes are essential for desalination and water reuse, yet their permeability declines in high-pressure applications due to membrane compaction. This study investigates the structural and functional responses of commercial brackish, seawater, and high-pressure RO membranes at applied pressures up to 120 bar using a multiscale, nondestructive <i>in operando</i> scanning electron microscopy (<i>i</i>SEM) imaging platform. The <i>i</i>SEM technique reveals progressive densification across the composite membrane structure, which correlates with observed declines in water and solute permeance. To quantify these structural changes with greater fidelity, we combined X-ray computed tomography with AI-based segmentation enabling precise analysis of pore size distribution and thickness of the polysulfone support layer. Compared to traditional thresholding, AI segmentation accurately delineates material phases and void spaces, enhancing the reproducibility and resolution of morphological assessments. The results demonstrate that compaction-induced reductions in porosity and thickness strongly impact membrane transport properties. These findings provide mechanistic insights into the compaction behavior of RO membranes and underscore the potential for advanced imaging and AI-driven data analysis to guide the design of next-generation membranes with improved mechanical resilience and operational longevity.</p>\",\"PeriodicalId\":37,\"journal\":{\"name\":\"Environmental Science & Technology Letters Environ.\",\"volume\":\"12 8\",\"pages\":\"1069–1074\"},\"PeriodicalIF\":8.8000,\"publicationDate\":\"2025-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Science & Technology Letters Environ.\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.estlett.5c00529\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Science & Technology Letters Environ.","FirstCategoryId":"1","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.estlett.5c00529","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Nondestructive In Operando Imaging of Thin Film Composite Membrane Compaction Enhanced by AI-Based Segmentation
Reverse osmosis (RO) membranes are essential for desalination and water reuse, yet their permeability declines in high-pressure applications due to membrane compaction. This study investigates the structural and functional responses of commercial brackish, seawater, and high-pressure RO membranes at applied pressures up to 120 bar using a multiscale, nondestructive in operando scanning electron microscopy (iSEM) imaging platform. The iSEM technique reveals progressive densification across the composite membrane structure, which correlates with observed declines in water and solute permeance. To quantify these structural changes with greater fidelity, we combined X-ray computed tomography with AI-based segmentation enabling precise analysis of pore size distribution and thickness of the polysulfone support layer. Compared to traditional thresholding, AI segmentation accurately delineates material phases and void spaces, enhancing the reproducibility and resolution of morphological assessments. The results demonstrate that compaction-induced reductions in porosity and thickness strongly impact membrane transport properties. These findings provide mechanistic insights into the compaction behavior of RO membranes and underscore the potential for advanced imaging and AI-driven data analysis to guide the design of next-generation membranes with improved mechanical resilience and operational longevity.
期刊介绍:
Environmental Science & Technology Letters serves as an international forum for brief communications on experimental or theoretical results of exceptional timeliness in all aspects of environmental science, both pure and applied. Published as soon as accepted, these communications are summarized in monthly issues. Additionally, the journal features short reviews on emerging topics in environmental science and technology.