Journal of Raman Spectroscopy最新文献

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Research on the Characterization of Heterogeneous Catalysts and Reactions Based on Surface-Enhanced Raman Spectroscopy 基于表面增强拉曼光谱的非均相催化剂及反应表征研究
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-04-04 DOI: 10.1002/jrs.6805
Bao-Ying Wen, Run-Ze Zhang, Yue-Jiao Zhang, Jian-Feng Li, Zhong-Qun Tian
{"title":"Research on the Characterization of Heterogeneous Catalysts and Reactions Based on Surface-Enhanced Raman Spectroscopy","authors":"Bao-Ying Wen,&nbsp;Run-Ze Zhang,&nbsp;Yue-Jiao Zhang,&nbsp;Jian-Feng Li,&nbsp;Zhong-Qun Tian","doi":"10.1002/jrs.6805","DOIUrl":"https://doi.org/10.1002/jrs.6805","url":null,"abstract":"<div>\u0000 \u0000 <p>Surface analysis techniques play a crucial role in elucidating heterogeneous catalytic reactions. Among these, surface-enhanced Raman spectroscopy (SERS) stands out due to its exceptional surface detection sensitivity and its unique ability to provide molecular fingerprints. However, the limitations of SERS technology, particularly its poor material and morphological universality, significantly impede its development. This paper summarizes a series of innovative SERS strategies developed by our group for the study of heterogeneous catalysts and reactions, such as the core-shell nanostructure “borrowing” strategy and the SHINERS-satellite strategy. These methods successfully overcome the limitations of traditional SERS, thereby paving new pathways for the in situ characterization of catalysts and reactions using SERS technology in practical applications. By employing these strategies, we not only conducted in-depth investigations into a series of key reactions, such as the oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER), but also successfully obtained direct spectroscopic evidence of critical intermediate species. Moreover, in combination with density functional theory (DFT) calculations and other advanced analytical techniques, we analyzed the mechanisms and structure–activity relationships of these catalytic reactions at the molecular level. Lastly, this paper provides a prospective outlook on the future development trends of SERS technology in the field of heterogeneous catalysis.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"546-555"},"PeriodicalIF":2.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Uncertainty Quantification Using Ensemble Learning and Monte Carlo Sampling for Performance Prediction and Monitoring in Cell Culture Processes 使用集成学习和蒙特卡罗采样的不确定性量化用于细胞培养过程的性能预测和监测
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-04-04 DOI: 10.1002/jrs.6808
Thanh Tung Khuat, Robert Bassett, Ellen Otte, Bogdan Gabrys
{"title":"Uncertainty Quantification Using Ensemble Learning and Monte Carlo Sampling for Performance Prediction and Monitoring in Cell Culture Processes","authors":"Thanh Tung Khuat,&nbsp;Robert Bassett,&nbsp;Ellen Otte,&nbsp;Bogdan Gabrys","doi":"10.1002/jrs.6808","DOIUrl":"https://doi.org/10.1002/jrs.6808","url":null,"abstract":"<p>Biopharmaceutical products, particularly monoclonal antibodies (mAbs), have gained prominence in the pharmaceutical market due to their high specificity and efficacy. As these products are projected to constitute a substantial portion of global pharmaceutical sales, the application of machine learning models in mAb development and manufacturing is gaining momentum. This paper addresses the critical need for uncertainty quantification in machine learning predictions, particularly in scenarios with limited training data. Leveraging ensemble learning and Monte Carlo simulations, our proposed method generates additional input samples to enhance the robustness of the model in small training datasets. We evaluate the efficacy of our approach through two case studies: predicting antibody concentrations in advance and real-time monitoring of glucose concentrations during bioreactor runs using Raman spectra data. Our findings demonstrate the effectiveness of the proposed method in estimating the uncertainty levels associated with process performance predictions and facilitating real-time decision-making in biopharmaceutical manufacturing. This contribution not only introduces a novel approach for uncertainty quantification but also provides insights into overcoming challenges posed by small training datasets in bioprocess development. The evaluation demonstrates the effectiveness of our method in addressing key challenges related to uncertainty estimation within upstream cell cultivation, illustrating its potential impact on enhancing process control and product quality in the dynamic field of biopharmaceuticals.</p>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"623-636"},"PeriodicalIF":2.4,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jrs.6808","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial Acoustic Shock Wave-Induced Lattice Distortion-Driven Structural Order–Disorder Phase Transition in Natural Polycrystalline Forsterite (α-Mg2SiO4): X-Ray and Raman Spectroscopic Approaches 人工声激波诱导晶格畸变驱动天然多晶Forsterite (α-Mg2SiO4)结构有序-无序相变:x射线和拉曼光谱方法
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-04-03 DOI: 10.1002/jrs.6814
Sivakumar Aswathappa, Lidong Dai, S. Sahaya Jude Dhas, Raju Suresh Kumar
{"title":"Artificial Acoustic Shock Wave-Induced Lattice Distortion-Driven Structural Order–Disorder Phase Transition in Natural Polycrystalline Forsterite (α-Mg2SiO4): X-Ray and Raman Spectroscopic Approaches","authors":"Sivakumar Aswathappa,&nbsp;Lidong Dai,&nbsp;S. Sahaya Jude Dhas,&nbsp;Raju Suresh Kumar","doi":"10.1002/jrs.6814","DOIUrl":"https://doi.org/10.1002/jrs.6814","url":null,"abstract":"<div>\u0000 \u0000 <p>In the present work, the natural polycrystalline forsterite (α-Mg<sub>2</sub>SiO<sub>4</sub>) have been chosen for the shock wave recovery experiment which is one of the most prominent silicate group minerals in the upper mantle of the Earth. The analytical techniques such as X-ray diffractometry and Raman spectroscopy have been utilized to extract the impact of shock waves on the olivine samples. According to the observed XRD results, the intensities of uni-indexed diffraction peaks such as (020) and (002) have significantly reduced compared to the bi-indexed (101) and tri-indexed planes (112) at the exposure of 100 shocks. The Raman results demonstrate that the characteristic doublet Raman peaks such as asymmetry and symmetry SiO<sub>4</sub> normalized intensity ratio are found to have reduced and the calculated values are 0.9, 0.9, and 0.72 for 0, 50, and 100 shocks, respectively. Based on the obtained analytical results, the high degree of crystalline nature of α-Mg<sub>2</sub>SiO<sub>4</sub> has undergone the structurally disordered state of α-Mg<sub>2</sub>SiO<sub>4</sub> phase transition on exposing 100 shocks rather than the crystallographic transitions of β and γ-Mg<sub>2</sub>SiO<sub>4</sub>. From the results, the prismatic plane (020) has the major contribution to initiating structural revolution of the formation of its high-pressure phases and structurally disordered systems under extreme conditions.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"609-622"},"PeriodicalIF":2.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Raman Spectroscopy of Geological Varieties of Hematite of Varying Crystallinity and Morphology 不同结晶度和形态赤铁矿地质品种的拉曼光谱研究
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-04-01 DOI: 10.1002/jrs.6811
Claire P. Marshall, Gavin Stockdale, Claire A. Carr
{"title":"Raman Spectroscopy of Geological Varieties of Hematite of Varying Crystallinity and Morphology","authors":"Claire P. Marshall,&nbsp;Gavin Stockdale,&nbsp;Claire A. Carr","doi":"10.1002/jrs.6811","DOIUrl":"https://doi.org/10.1002/jrs.6811","url":null,"abstract":"<div>\u0000 \u0000 <p>Hematite, α-Fe<sub>2</sub>O<sub>3</sub>, is a common rock-forming mineral found in sedimentary, metamorphic, igneous rocks, as well as meteorites, and is ubiquitous on Mars. It is the most thermodynamically stable geological iron oxide mineral that forms under a variety of low- and high-temperature regimes, low- and high-pressure regimes, Eh and pH conditions. Hematite occurs in a variety of forms, varying in crystallinity, morphology, and texture, which include micaceous, massive, kidney ore (botryoidal), oolitic, rainbow, and rare bulk single-crystals. Despite the plethora of literature in the geosciences on the application of Raman spectroscopy to investigate iron oxide minerals, thus far, there is a paucity in the literature on the effects on the Raman spectra of these geologically formed different textural hematite varieties. Here, we investigated the effects on the Raman spectra of the whole variety of geologically formed hematite. Our results clearly demonstrate that biaxial plots between the ratio of the <i>E</i><sub><i>g</i></sub>/<i>A</i><sub><i>1g</i></sub> modes (410/225 cm<sup>−1</sup>) and <i>E</i><sub><i>g</i></sub>/<i>E</i><sub><i>gL</i></sub> modes (410/294 cm<sup>−1</sup>) can distinguish between micaceous, massive, kidney ore (botryoidal), oolitic, rainbow, and rare bulk single-crystal hematite varieties, with reasonably high correlation coefficients.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"590-597"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Simultaneous Raman and FTIR-ATR Spectroscopy Techniques Combined With Chemometrics: Characterization and Comparison of Donkey Milk Adulteration 拉曼光谱和FTIR-ATR光谱技术结合化学计量学:驴奶掺假的表征和比较
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-31 DOI: 10.1002/jrs.6812
Sinem Çolak
{"title":"Simultaneous Raman and FTIR-ATR Spectroscopy Techniques Combined With Chemometrics: Characterization and Comparison of Donkey Milk Adulteration","authors":"Sinem Çolak","doi":"10.1002/jrs.6812","DOIUrl":"https://doi.org/10.1002/jrs.6812","url":null,"abstract":"<div>\u0000 \u0000 <p>Due to its nutritional qualities, donkey milk is a newly popular food. Because it has a high added value, it may be adulterated with using cheaper milks, like cow milk. This study has investigated a rapid method for the authentication of pure donkey milk using Raman and FTIR-ATR spectroscopy and comparison of the methods. Three preprocessing methods were applied to the spectra. The results show that donkey milk has lower fat and protein content compared with cow milk. Notably, Raman spectroscopy successfully distinguishes donkey and cow milk according to the presence and absence of β-carotene. Principal component analysis demonstrated a distinct separation between cow, adulterated donkey, and donkey. The variance value of 90.30% (PC1 = 72.76, PC2 = 17.53) is obtained from the first and second PCs for Raman data, and the variance value of 89.67% (PC1 = 65.25, PC2 = 24.41) is obtained from the first and second PCs for FTIR data. The Raman data could be used to separate donkey and cow milks, whereas the FTIR data were insufficient. It was observed that adulterated species could be separated between classes with Raman and FTIR. In the FTIR spectrum, there is a broad peak due to water, which accounts for about 87% of the milk composition, but this water peak is not included in the Raman spectrum. The results demonstrate the potential of Raman spectroscopy as a rapid and reliable method and suggest that it can be used as a nondestructive analytical tool for adulteration detection in donkey milk.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"598-608"},"PeriodicalIF":2.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of 3D Raman Mapping on Complex Inclusions: A Case Study of the Styrian Basin Mantle Xenoliths (W-Carpathian Pannonian Region) 三维拉曼制图在复杂包裹体中的应用——以西喀尔巴阡潘诺尼亚盆地地幔包体为例
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-25 DOI: 10.1002/jrs.6797
Justine L. Myovela, László E. Aradi, Tamás Spránitz, Zoltán Taracsák, Máté Hegedűs, Patrik Konečný, János Kovács, Márta Berkesi
{"title":"Application of 3D Raman Mapping on Complex Inclusions: A Case Study of the Styrian Basin Mantle Xenoliths (W-Carpathian Pannonian Region)","authors":"Justine L. Myovela,&nbsp;László E. Aradi,&nbsp;Tamás Spránitz,&nbsp;Zoltán Taracsák,&nbsp;Máté Hegedűs,&nbsp;Patrik Konečný,&nbsp;János Kovács,&nbsp;Márta Berkesi","doi":"10.1002/jrs.6797","DOIUrl":"https://doi.org/10.1002/jrs.6797","url":null,"abstract":"<p>Fluid and melt inclusions trapped in mantle xenoliths provide direct insights into the metasomatic agent in the lithospheric mantle, including its volatile content. We conducted 3D Raman mapping on fluid and melt inclusions in modally metasomatized mantle xenoliths from the Styrian Basin (W-Carpathian Pannonian Region) to explore how this method can be utilized to study the role of fluids and melts in the upper mantle. 3D Raman mapping revealed complex phase assemblages of coexisting fluid and solid phases in the inclusions. Fluid phases are CO<sub>2</sub> (49.2–98.4 mol%, 19.1–61.0 vol%) and H<sub>2</sub>O (1.5–50.8 mol%, 8.6–35.3 vol%). This H<sub>2</sub>O concentration range is considerably higher than in most mantle fluids (∼10–15 mol%). Solid phases are silicates, carbonates, sulfides, and sulfates present in varying volume% (vol%). 3D Raman mapping shows that liquid H<sub>2</sub>O wets other phases in the mapped fluid inclusions and may be preferentially lost compared to the CO<sub>2</sub>-rich phase during inclusion decrepitation. The accuracy of CO<sub>2</sub>-H<sub>2</sub>O mol ratios from Raman 3D mapping in fluid inclusions can be affected by variable Raman cross-sections of trapped phases. Therefore, thermodynamic modeling is recommended to validate measured CO<sub>2</sub>-H<sub>2</sub>O mol ratios. 3D Raman mapping may underestimate low Raman scatterers like silicate glass in fluid inclusions, but their volumes can be corrected based on FIB-SEM analyses. Thermodynamic modeling suggests that the fluid compositions in the Raman-mapped fluid inclusions may reflect non-equilibrium entrapment, whereas those in the melt inclusions reflect equilibrium entrapment in this mantle portion. The discovered C-O-H fluids provide new information on fluid-rock reactions in the lithospheric mantle.</p>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"577-589"},"PeriodicalIF":2.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jrs.6797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Deciphering the Structure and Association Behavior in Aqueous Lithium Nitrate Solution 破译硝酸锂水溶液的结构和缔合行为
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-24 DOI: 10.1002/jrs.6798
Jisheng Li, Xiufang Wang, Fayan Zhu, Yunxia Wang, Lulu Song, Yongquan Zhou, Yunqi Ma
{"title":"Deciphering the Structure and Association Behavior in Aqueous Lithium Nitrate Solution","authors":"Jisheng Li,&nbsp;Xiufang Wang,&nbsp;Fayan Zhu,&nbsp;Yunxia Wang,&nbsp;Lulu Song,&nbsp;Yongquan Zhou,&nbsp;Yunqi Ma","doi":"10.1002/jrs.6798","DOIUrl":"https://doi.org/10.1002/jrs.6798","url":null,"abstract":"<div>\u0000 \u0000 <p>Among all associative species, lithium ions predominantly form a four-coordinated tetrahedral structure, with exceptions occurring only rarely in the case of five-coordinated structures, which exhibit higher energy. As the concentration of the lithium nitrate solution increases, an ion association process may occur, accompanied by multiple ion pair transformations. This study employs micro-Raman spectroscopy and component analysis methods to investigate lithium nitrate hexahydrate aqueous solutions with water-to-salt molar ratios (WSR) ranging from 1 to 22. Within the examined concentration range, as the solution concentration increases, the characteristic vibration wavenumber of nitrate ions shifts from 1047 to 1062 cm<sup>−1</sup>, while the half-peak width broadens from 14.5 to 25 cm<sup>−1</sup>. In dilute lithium nitrate solutions, lithium ions and nitrate ions adopt tetrahedral (tetrahydrate) and bowl-shaped (hexahydrate) structures, respectively. Depending on the WSR: At WSR ≥ 5, the primary species include free hydrated ions, solvent-shared ion pairs (SIP), and contact ion pairs (CIP). When 12.5 ≤ WSR &lt; 20, the main species are solvent-shared ion pairs. For WSR &lt; 5, the predominant species consist of two types of ion pairs: CIP and complex ion pairs, with the amounts of free ions and CIP rapidly decreasing to zero. As WSR decreases from 5 to 1, the proportion of CIP diminishes from a maximum of 35% to 0%, while the percentage of Complex species increases significantly. Notably, when the WSR approaches 1, the percentage content of Complex species reaches approximately 95%.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"637-646"},"PeriodicalIF":2.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Identification of Breast Cancer Subtypes by Raman Spectroscopy Integrated With Machine Learning Algorithms: Analyzing the Influence of Baseline 结合机器学习算法的拉曼光谱识别乳腺癌亚型:分析基线的影响
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-24 DOI: 10.1002/jrs.6799
Chao Yang, Kaisaier Aizezi, Juan Li, Xiaoting Wang, Fengling Li, Wen Lei, Jingjing Xia, Ayitila Maimaitijiang
{"title":"The Identification of Breast Cancer Subtypes by Raman Spectroscopy Integrated With Machine Learning Algorithms: Analyzing the Influence of Baseline","authors":"Chao Yang,&nbsp;Kaisaier Aizezi,&nbsp;Juan Li,&nbsp;Xiaoting Wang,&nbsp;Fengling Li,&nbsp;Wen Lei,&nbsp;Jingjing Xia,&nbsp;Ayitila Maimaitijiang","doi":"10.1002/jrs.6799","DOIUrl":"https://doi.org/10.1002/jrs.6799","url":null,"abstract":"<div>\u0000 \u0000 <p>The question of how the baseline of Raman spectroscopy impacts data models has remained unexplored. In this research, we utilized three spectral datasets—raw, preprocessed, and baseline data—to construct identification models for breast cancer molecular subtypes using four machine learning algorithms and examined and analyzed the influence of baseline data on the performance of these models. In the identification models for cancer cell molecular subtypes, regardless of whether they pertained to normal or breast cancer cells, preprocessed data consistently yielded the most optimal model performance, trailed by raw data, and ultimately followed by baseline data. Despite the baseline data giving the worst classification performance, when coupled with the artificial neural network, it consistently attained a recognition accuracy of approximately 92.50 ± 5.30% in the binary classification and 90.60 ± 1.52% in the five-class classification. The results suggested that baseline data held a notable contribution to the performance of data models. Looking ahead, it could potentially harness the concept of food by-product processing to maximize the utilization of baseline data. Furthermore, when integrated with feature visualization strategies, the UVE-SPA and ICO approaches, employing merely 30 or 258 variables, respectively, were able to yield model results comparable to those of preprocessed data (with 858 variables), attaining an accuracy of 96.00 ± 1.87%. This underscored the pivotal role of the selected Raman spectral regions in distinguishing breast cancer molecular subtypes. Beyond the standard protein, lipid, and nucleic acid regions, the selected features encompassed cysteine, phenylalanine, and carotenoid, all of which, according to established research, had held crucial significance in the development and progression of cancer. This project delved into the impact of Raman baseline on model outcomes, furnishing valuable data to enhance future Raman spectroscopy modeling techniques and igniting discussions on the untapped potential of baseline data in forthcoming endeavors.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"556-566"},"PeriodicalIF":2.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Simulated Infrared and Raman Spectra of Phosphorus Allotropes 磷同素异形体的模拟红外和拉曼光谱
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-22 DOI: 10.1002/jrs.6788
Laura Bonometti, Giuseppe Sansone, Antti J. Karttunen, Lorenzo Maschio
{"title":"Simulated Infrared and Raman Spectra of Phosphorus Allotropes","authors":"Laura Bonometti,&nbsp;Giuseppe Sansone,&nbsp;Antti J. Karttunen,&nbsp;Lorenzo Maschio","doi":"10.1002/jrs.6788","DOIUrl":"https://doi.org/10.1002/jrs.6788","url":null,"abstract":"<p>Elemental phosphorus is both an intriguing and challenging case in solid state chemistry. The variety of existing allotropes, with different chemistry and properties, makes this long-time studied element still of high intertest today. In this work, we have systematically investigated the vibrational properties of white \u0000<span></span><math>\u0000 <mi>γ</mi></math>, white \u0000<span></span><math>\u0000 <mi>β</mi></math>, fibrous red, violet, and black phosphorus allotropes by simulating their infrared (IR) and Raman spectra at the density functional theory (DFT) level. The latter are provided as powder and directionally resolved (oriented single crystal) spectra. As all results are obtained with the same method and computational setup, our work provides a data set that is consistent across the different polimorphs, hence minimizing discrepancies arising from methodological differences. Our results are in general good agreement with available experimental and theoretical spectra from literature in both the Raman and IR cases. At the same time, some of our spectra are meant to fill gaps in the existing literature.</p>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 7","pages":"567-576"},"PeriodicalIF":2.4,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jrs.6788","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving Machine Learning–Based Bacterial Discrimination by Learning Single-Cell Raman Data From Multiple Growth Phases 通过学习来自多个生长阶段的单细胞拉曼数据来改进基于机器学习的细菌识别
IF 2.4 3区 化学
Journal of Raman Spectroscopy Pub Date : 2025-03-22 DOI: 10.1002/jrs.6804
Nodoka Oda, Nanako Kanno, Shingo Kato, Moriya Ohkuma, Shinsuke Shigeto
{"title":"Improving Machine Learning–Based Bacterial Discrimination by Learning Single-Cell Raman Data From Multiple Growth Phases","authors":"Nodoka Oda,&nbsp;Nanako Kanno,&nbsp;Shingo Kato,&nbsp;Moriya Ohkuma,&nbsp;Shinsuke Shigeto","doi":"10.1002/jrs.6804","DOIUrl":"https://doi.org/10.1002/jrs.6804","url":null,"abstract":"<div>\u0000 \u0000 <p>Bacterial discrimination using single-cell Raman spectroscopy and machine/deep learning techniques has been widely explored for promising applications in medical, environmental, and food sciences. To construct a machine-learning model that can achieve highly accurate and robust discrimination of bacteria in real-world samples, data consisting of Raman spectra of bacterial cells acquired under various physiological conditions are essential. Despite much effort to study the effects of growth phase on bacterial discrimination, it is not yet fully elucidated which growth phase(s) needs to be included in training data to efficiently improve discrimination accuracy and what growth phase-dependent changes in cellular components underlie accurate discrimination. Here, we used random forest (RF), an ensemble machine learning method, to discriminate six model bacterial species, including both Gram-positive and Gram-negative bacteria, at five different growth phases ranging from lag to late stationary phases. We compared four RF classification models that were trained on Raman data from one (either midexponential or late stationary), two (midexponential and late stationary), and all five growth phases. The species discrimination accuracy of the model built on the training data consisting of the two distinctly different growth phases exceeded 80% with a marked increase of 24% and 32.5% relative to the models learning data from a single growth phase. This increase was greater than what we found in going from training data with two growth phases to that with all five growth phases (13%). We also revealed that Raman bands that are relatively invariant (e.g., proteins) and specific to the growth phase (e.g., DNA/RNA and intracellular storage materials) are both important for attaining accurate bacterial discrimination. The present study provides a simple yet effective way to construct training data for good discrimination performance, which could be extended to discriminate bacterial cells under other physiological conditions such as nutrient, temperature, and pH.</p>\u0000 </div>","PeriodicalId":16926,"journal":{"name":"Journal of Raman Spectroscopy","volume":"56 6","pages":"481-490"},"PeriodicalIF":2.4,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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