Vibrational Spectroscopy最新文献_第3页

Raman spectroscopic evaluation of silver diamine fluoride in preventing acid-induced caries progression 二胺氟化银预防酸致龋进展的拉曼光谱评价

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-09-05 DOI: 10.1016/j.vibspec.2025.103856

Agata Daktera-Micker , Maciej Rzeczkowski , Zuzanna Buchwald , Tomasz Buchwald

The antibacterial mechanisms of silver diamine fluoride, as well as its ability to prevent tooth caries, are well-established. The aim of this study was to provide a clear evaluation of whether silver diamine fluoride, in addition to its antibacterial properties, is capable of inhibiting the progression of dental caries in an acidic environment to the same extent as silver nitrate. The results will help determine which of these two compounds has greater potential for application in the prevention and treatment of early carious lesions. To achieve this goal, studies were conducted on teeth under four conditions: healthy, after first demineralization, following the application of the tested compounds, and after second demineralization. At each stage of the research, Raman spectroscopy was used to assess changes in the enamel structure. These findings showed that, although neither compound completely inhibits the progression of demineralization, both can slow it down. Furthermore, no significant differences were observed between the two compounds in their effectiveness in reducing lesion progression. A notable observation was that the silver diamine fluoride was washed away by the demineralizing solution, causing the protective barrier it provided to disappear. This finding may be attributed to the limited penetration depth of the compounds into the enamel. The compounds primarily penetrated the demineralized areas, but the depth of enamel demineralization in our study was approximately 200 µm. This limited penetration could explain the washing out of the compound and its reduced effectiveness in inhibiting demineralization.

氟化二胺银的抗菌机制，以及它预防龋齿的能力，是公认的。本研究的目的是明确评估氟化二胺银除了抗菌性能外，是否能够在酸性环境中抑制龋齿的发展，其程度与硝酸银相同。该结果将有助于确定这两种化合物中哪一种在预防和治疗早期龋齿病变方面具有更大的应用潜力。为了实现这一目标，研究人员在四种情况下对牙齿进行了研究：健康、第一次脱矿后、使用测试化合物后和第二次脱矿后。在研究的每个阶段，使用拉曼光谱来评估牙釉质结构的变化。这些发现表明，虽然这两种化合物都不能完全抑制脱矿的进程，但它们都能减缓脱矿的进程。此外，两种化合物在减少病变进展的有效性方面没有显著差异。一个值得注意的观察结果是，氟化银二胺被脱矿溶液冲走，导致它提供的保护屏障消失。这一发现可能是由于化合物对牙釉质的渗透深度有限。化合物主要渗透到脱矿区，但我们研究的牙釉质脱矿深度约为200 µm。这种有限的渗透可以解释化合物被洗出及其抑制脱矿的效果降低的原因。

{"title":"Raman spectroscopic evaluation of silver diamine fluoride in preventing acid-induced caries progression","authors":"Agata Daktera-Micker , Maciej Rzeczkowski , Zuzanna Buchwald , Tomasz Buchwald","doi":"10.1016/j.vibspec.2025.103856","DOIUrl":"10.1016/j.vibspec.2025.103856","url":null,"abstract":"<div><div>The antibacterial mechanisms of silver diamine fluoride, as well as its ability to prevent tooth caries, are well-established. The aim of this study was to provide a clear evaluation of whether silver diamine fluoride, in addition to its antibacterial properties, is capable of inhibiting the progression of dental caries in an acidic environment to the same extent as silver nitrate. The results will help determine which of these two compounds has greater potential for application in the prevention and treatment of early carious lesions. To achieve this goal, studies were conducted on teeth under four conditions: healthy, after first demineralization, following the application of the tested compounds, and after second demineralization. At each stage of the research, Raman spectroscopy was used to assess changes in the enamel structure. These findings showed that, although neither compound completely inhibits the progression of demineralization, both can slow it down. Furthermore, no significant differences were observed between the two compounds in their effectiveness in reducing lesion progression. A notable observation was that the silver diamine fluoride was washed away by the demineralizing solution, causing the protective barrier it provided to disappear. This finding may be attributed to the limited penetration depth of the compounds into the enamel. The compounds primarily penetrated the demineralized areas, but the depth of enamel demineralization in our study was approximately 200 µm. This limited penetration could explain the washing out of the compound and its reduced effectiveness in inhibiting demineralization.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"141 ","pages":"Article 103856"},"PeriodicalIF":3.1,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005238","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 usage of ATR-FTIR spectroscopy combined with chemometrics in postmortem diagnosis of acute myocardial infarction ATR-FTIR光谱联合化学计量学在急性心肌梗死死后诊断中的应用

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-09-04 DOI: 10.1016/j.vibspec.2025.103857

Mustafa Talip Sener , Nihal Simsek Ozek , Ferhunde Aysin , Sezen Yildiz , Ozkan Aksakal

Myocardial infarction (MI) represents a leading cause of sudden death; however, the identification of acute MI in postmortem examinations remains challenging due to the lack of specific early morphological markers. This study explores the utility of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, in combination with chemometric analysis, for the postmortem diagnosis of MI. A rat model of MI was employed, and the expression levels and protein concentrations of JUNB and myoglobin (MYO) were quantified to corroborate the spectral findings. ATR-FTIR analysis revealed significant alterations in collagen and nucleic acid content between the control and MI groups, particularly during the early postmortem intervals. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) successfully differentiated between groups, achieving 100 % sensitivity and specificity, and 97 % classification accuracy through PCA-based linear discriminant analysis (LDA). Support vector machine (SVM) classification further confirmed these findings. Notably, spectral changes at 3285, 3016, 2920, 1338, 1236, and 974 cm⁻¹ exhibited strong correlations with JUNB and MYO gene and protein levels. This integrative approach demonstrates that ATR-FTIR spectroscopy, combined with multivariate analysis and molecular markers, offers a rapid, non-destructive, and highly accurate method for the early postmortem diagnosis of acute MI, highlighting its potential for forensic and clinical applications.

心肌梗死（MI）是猝死的主要原因；然而，由于缺乏特定的早期形态学标记，在死后检查中鉴定急性心肌梗死仍然具有挑战性。本研究探讨了衰减全反射-傅里叶变换红外光谱（ATR-FTIR）结合化学计量学分析在心肌梗死死后诊断中的应用。采用心肌梗死大鼠模型，定量分析了JUNB和肌红蛋白（MYO）的表达水平和蛋白浓度，以证实光谱结果。ATR-FTIR分析显示，对照组和心肌梗死组之间的胶原蛋白和核酸含量发生了显著变化，尤其是在死后早期。主成分分析（PCA）和层次聚类分析（HCA）通过基于PCA的线性判别分析（LDA）实现了组间的成功区分，灵敏度和特异度分别达到100 %和97 %。支持向量机（SVM）分类进一步证实了这些发现。值得注意的是，3285、3016、2920、1338、1236和974 cm⁻¹ 的光谱变化与JUNB和MYO基因和蛋白质水平有很强的相关性。这种综合方法表明，ATR-FTIR光谱与多变量分析和分子标记相结合，为急性心肌梗死的早期死后诊断提供了一种快速、非破坏性和高度准确的方法，突出了其在法医和临床应用中的潜力。

{"title":"The usage of ATR-FTIR spectroscopy combined with chemometrics in postmortem diagnosis of acute myocardial infarction","authors":"Mustafa Talip Sener , Nihal Simsek Ozek , Ferhunde Aysin , Sezen Yildiz , Ozkan Aksakal","doi":"10.1016/j.vibspec.2025.103857","DOIUrl":"10.1016/j.vibspec.2025.103857","url":null,"abstract":"<div><div>Myocardial infarction (MI) represents a leading cause of sudden death; however, the identification of acute MI in postmortem examinations remains challenging due to the lack of specific early morphological markers. This study explores the utility of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, in combination with chemometric analysis, for the postmortem diagnosis of MI. A rat model of MI was employed, and the expression levels and protein concentrations of JUNB and myoglobin (MYO) were quantified to corroborate the spectral findings. ATR-FTIR analysis revealed significant alterations in collagen and nucleic acid content between the control and MI groups, particularly during the early postmortem intervals. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) successfully differentiated between groups, achieving 100 % sensitivity and specificity, and 97 % classification accuracy through PCA-based linear discriminant analysis (LDA). Support vector machine (SVM) classification further confirmed these findings. Notably, spectral changes at 3285, 3016, 2920, 1338, 1236, and 974 cm⁻¹ exhibited strong correlations with JUNB and MYO gene and protein levels. This integrative approach demonstrates that ATR-FTIR spectroscopy, combined with multivariate analysis and molecular markers, offers a rapid, non-destructive, and highly accurate method for the early postmortem diagnosis of acute MI, highlighting its potential for forensic and clinical applications.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"141 ","pages":"Article 103857"},"PeriodicalIF":3.1,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005239","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

Spectroscopic profiling of lipid and protein alterations in kidney tissue induced by coated MoS2 quantum dots 包被二硫化钼量子点诱导肾组织脂质和蛋白质改变的光谱分析

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-08-25 DOI: 10.1016/j.vibspec.2025.103848

Eida M. Alshammari , Soheib D. Alsahafi , Ohoud A. A Alamri , Norah T.S. Albogamy , Ebtihaj Jambi , Abeer M. Alosaimi , Saedah R. AlMhyawi , Reem Alwafi , Abdu Saeed

Molybdenum disulfide (MoS₂) quantum dots (QDs) possess unique physicochemical properties that make them attractive for biomedical applications. However, their interactions with biological tissues at the molecular level remain insufficiently understood. In this study, we employed spectroscopic techniques to investigate molecular alterations in the lipids and proteins of murine kidney tissue following exposure to coated MoS₂ QDs. Healthy male SWR/J mice were divided into control and treated groups, with the latter receiving daily doses of encapsulated QDs. Spectroscopic analyses revealed subtle yet consistent changes in lipid composition and organization, evidenced by shifts in CH₂ and CH₃ stretching vibrations and decreased intensity in lipid-associated Raman bands. FTIR spectra also indicated a reduction in carbonyl ester content, suggesting lipid peroxidation effects. Additionally, minor perturbations in aromatic amino acid bands and heme-associated features were observed in UV-Vis spectra, indicating possible interactions with protein residues; however, no significant secondary structural changes in proteins were detected. These results demonstrate the utility of spectroscopic approaches in revealing molecular alterations induced by coated MoS₂ QDs in kidney tissue. Additionally, these findings confirm the importance of utilizing integrated spectroscopic approaches for evaluating the biocompatibility and safety of emerging nanomaterials at the molecular level.

二硫化钼（MoS2）量子点（QDs）具有独特的物理化学性质，使其在生物医学应用中具有吸引力。然而，它们在分子水平上与生物组织的相互作用仍然不够清楚。在这项研究中，我们利用光谱技术研究了暴露于包被二硫化钼量子点后小鼠肾组织中脂质和蛋白质的分子变化。将健康雄性SWR/J小鼠分为对照组和治疗组，治疗组给予每日剂量的QDs胶囊。光谱分析揭示了脂质组成和组织的微妙而一致的变化，证明了CH₂和CH₃拉伸振动的变化和脂质相关拉曼带强度的降低。FTIR光谱还显示羰基酯含量降低，表明脂质过氧化作用。此外，在紫外可见光谱中观察到芳香氨基酸带和血红素相关特征的轻微扰动，表明可能与蛋白质残基相互作用；然而，在蛋白质中未检测到明显的二级结构变化。这些结果证明了光谱方法在揭示包被二硫化钼量子点在肾组织中引起的分子改变方面的效用。此外，这些发现证实了利用综合光谱方法在分子水平上评估新兴纳米材料的生物相容性和安全性的重要性。

{"title":"Spectroscopic profiling of lipid and protein alterations in kidney tissue induced by coated MoS2 quantum dots","authors":"Eida M. Alshammari , Soheib D. Alsahafi , Ohoud A. A Alamri , Norah T.S. Albogamy , Ebtihaj Jambi , Abeer M. Alosaimi , Saedah R. AlMhyawi , Reem Alwafi , Abdu Saeed","doi":"10.1016/j.vibspec.2025.103848","DOIUrl":"10.1016/j.vibspec.2025.103848","url":null,"abstract":"<div><div>Molybdenum disulfide (MoS<sub>2</sub>) quantum dots (QDs) possess unique physicochemical properties that make them attractive for biomedical applications. However, their interactions with biological tissues at the molecular level remain insufficiently understood. In this study, we employed spectroscopic techniques to investigate molecular alterations in the lipids and proteins of murine kidney tissue following exposure to coated MoS<sub>2</sub> QDs. Healthy male SWR/J mice were divided into control and treated groups, with the latter receiving daily doses of encapsulated QDs. Spectroscopic analyses revealed subtle yet consistent changes in lipid composition and organization, evidenced by shifts in CH₂ and CH₃ stretching vibrations and decreased intensity in lipid-associated Raman bands. FTIR spectra also indicated a reduction in carbonyl ester content, suggesting lipid peroxidation effects. Additionally, minor perturbations in aromatic amino acid bands and heme-associated features were observed in UV-Vis spectra, indicating possible interactions with protein residues; however, no significant secondary structural changes in proteins were detected. These results demonstrate the utility of spectroscopic approaches in revealing molecular alterations induced by coated MoS<sub>2</sub> QDs in kidney tissue. Additionally, these findings confirm the importance of utilizing integrated spectroscopic approaches for evaluating the biocompatibility and safety of emerging nanomaterials at the molecular level.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103848"},"PeriodicalIF":3.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144906921","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

Surface-enhanced Raman spectroscopy coupled with DFT for sensitive detection of tadalafil in complex matrices 表面增强拉曼光谱耦合DFT用于复杂基质中他达拉非的灵敏检测

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-08-22 DOI: 10.1016/j.vibspec.2025.103847

John J. Castillo , Tomas Rindzevicius , Ciro E. Rozo , Lasse Højlund Eklund Thamdrup , Anja Boisen

Tadalafil (TDF), a widely prescribed phosphodiesterase-5 inhibitor, is not only a clinically important pharmaceutical for erectile dysfunction but also a frequently encountered adulterant in counterfeit supplements, raising serious public health and regulatory concerns. This study presents a novel and integrated approach for the sensitive and selective detection of TDF in complex commercial matrices, combining experimental Surface-Enhanced Raman Scattering (SERS) spectroscopy with Density Functional Theory (DFT) simulations. The molecular geometry of TDF was optimized at the B3LYP/6–311 G(d) level, and theoretical Raman and SERS spectra were generated using a mixed basis set. A molecular electrostatic potential (MEP) map was constructed to identify key adsorption sites, offering mechanistic insights into SERS enhancement. Experimentally, gold-capped silicon nanopillar (AuNP) substrates enabled detection of TDF across a wide concentration range (0.75–100 µM). Through SERS mapping and calibration, we established a linear correlation between signal intensity and TDF concentration. Most importantly, the method demonstrated real-world applicability by successfully detecting TDF in spiked commercial multivitamin tablets. Finally, this work provides a robust sensing platform for detecting illicit pharmaceutical adulterants, bridging theoretical modeling with practical SERS analytics, and offering valuable tools for regulatory monitoring and consumer safety.

他达拉非（TDF）是一种广泛使用的磷酸二酯酶-5抑制剂，不仅是临床上治疗勃起功能障碍的重要药物，而且也是假冒补充剂中经常遇到的掺假成分，引起了严重的公共卫生和监管问题。本研究提出了一种新的综合方法，将实验表面增强拉曼散射（SERS）光谱与密度泛函理论（DFT）模拟相结合，用于复杂商业矩阵中TDF的敏感和选择性检测。在B3LYP/ 6-311 G(d)水平上对TDF的分子几何结构进行优化，并使用混合基集生成理论拉曼和SERS光谱。构建了分子静电势（MEP）图来确定关键的吸附位点，为SERS增强提供了机制见解。实验中，金顶硅纳米柱（AuNP）衬底可以在宽浓度范围（0.75-100 µM）内检测TDF。通过SERS制图和校准，我们建立了信号强度与TDF浓度之间的线性相关关系。最重要的是，该方法通过成功地检测加标商业复合维生素片中的TDF，证明了其在现实世界中的适用性。最后，这项工作为检测非法药物掺假提供了一个强大的传感平台，将理论建模与实际SERS分析联系起来，并为监管监测和消费者安全提供了有价值的工具。

{"title":"Surface-enhanced Raman spectroscopy coupled with DFT for sensitive detection of tadalafil in complex matrices","authors":"John J. Castillo , Tomas Rindzevicius , Ciro E. Rozo , Lasse Højlund Eklund Thamdrup , Anja Boisen","doi":"10.1016/j.vibspec.2025.103847","DOIUrl":"10.1016/j.vibspec.2025.103847","url":null,"abstract":"<div><div>Tadalafil (TDF), a widely prescribed phosphodiesterase-5 inhibitor, is not only a clinically important pharmaceutical for erectile dysfunction but also a frequently encountered adulterant in counterfeit supplements, raising serious public health and regulatory concerns. This study presents a novel and integrated approach for the sensitive and selective detection of TDF in complex commercial matrices, combining experimental Surface-Enhanced Raman Scattering (SERS) spectroscopy with Density Functional Theory (DFT) simulations. The molecular geometry of TDF was optimized at the B3LYP/6–311 G(d) level, and theoretical Raman and SERS spectra were generated using a mixed basis set. A molecular electrostatic potential (MEP) map was constructed to identify key adsorption sites, offering mechanistic insights into SERS enhancement. Experimentally, gold-capped silicon nanopillar (AuNP) substrates enabled detection of TDF across a wide concentration range (0.75–100 µM). Through SERS mapping and calibration, we established a linear correlation between signal intensity and TDF concentration. Most importantly, the method demonstrated real-world applicability by successfully detecting TDF in spiked commercial multivitamin tablets. Finally, this work provides a robust sensing platform for detecting illicit pharmaceutical adulterants, bridging theoretical modeling with practical SERS analytics, and offering valuable tools for regulatory monitoring and consumer safety.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103847"},"PeriodicalIF":3.1,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903956","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

Infrared phenomics with 2D-COS unveils spatial heterogeneity and chemical evolution in a microbial biofilm 利用2D-COS的红外表型组学揭示了微生物生物膜的空间异质性和化学演化

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-08-13 DOI: 10.1016/j.vibspec.2025.103846

Pan Yang , Yadi Wang , Feng Geng , Junhong Lü , Xueling Li

Spatiotemporal mapping of the chemical dynamics of biofilm remains a fundamental challenge in microbial ecology. Here, we developed an infrared phenomics platform that integrating synchrotron-based Fourier transform infrared (SR-FTIR) microspectroscopy with two-dimensional correlation spectroscopy (2D-COS) to resolve the spatial heterogeneity and dynamic molecular gradients in Escherichia coli biofilms. By coupling hyperspectral imaging (30 μm resolution) with multivariate trajectory analysis, we revealed sequential chemical evolution: ester accumulation (1703 cm⁻¹) was found to precede enrichment of proteins (1653 cm⁻¹) and nucleic acids (1236 cm⁻¹), which was then followed by the deposition of polysaccharide (1055 cm⁻¹). This hierarchical molecular assembly was validated using principal component analysis (PCA) and cluster-based Euclidean distance metrics, thus establishing IR-2D-COS as a novel tool for the spatiotemporal analysis of microbial biofilm dynamics.

生物膜化学动力学的时空映射仍然是微生物生态学的一个基本挑战。在此，我们开发了一个红外表型组学平台，该平台将基于同步加速器的傅里叶变换红外（SR-FTIR）微光谱与二维相关光谱（2D-COS）相结合，来分析大肠杆菌生物膜的空间异质性和动态分子梯度。通过耦合高光谱成像（30 μm分辨率）和多变量轨迹分析，我们揭示了连续的化学进化：酯积累（1703 cm⁻¹）发生在蛋白质（1653 cm⁻¹）和核酸（1236 cm⁻¹）富集之前，然后是多糖（1055 cm⁻¹）的沉积。利用主成分分析（PCA）和基于聚类的欧几里得距离度量验证了这种分层分子组装，从而建立了IR-2D-COS作为微生物生物膜动力学时空分析的新工具。

引用次数: 0

Vibrational spectroscopy of urine combined with support vector machine for lupus nephritis diagnosis research 尿液振动光谱结合支持向量机诊断狼疮性肾炎的研究

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-08-11 DOI: 10.1016/j.vibspec.2025.103845

Xiaojing Sun , Zhaonan You , Yu Du , Bingqian Ran , Guohua Wu , Ying Tan , Longfei Yin

Lupus nephritis (LN) is one of the most common and serious organ manifestations of systemic lupus erythematosus (SLE), with a poor long-term prognosis and a complex diagnostic process, therefore it is important to find a simple, rapid and non-invasive method for the diagnosis of LN. This study investigated the feasibility of using surface-enhanced Raman spectroscopy (SERS) and Fourier Transform Infrared (FT-IR) spectroscopy of urine samples to classify healthy volunteers and LN patients. SERS and FT-IR data of urine samples were obtained from 100 LN patients and 100 healthy volunteers. To verify the stability of the classification algorithm, 50 independent experiments were conducted. In each experiment, the dataset was randomly divided and a classification model was established using the support vector machine (SVM) algorithm (linear kernel function). Meanwhile, it was compared with four other common classification algorithms and the results showed that SVM model had the best effect. The average classification accuracy of SERS and FT-IR spectra combined with SVM model for 50 independent experiments reached 96.97 % and 92.77 %, respectively. In addition, the features of SERS and FT-IR were spliced and then combined with SVM model for classification, corresponding to an average classification accuracy of 97.63 %. Subsequently, genetic algorithm was used to perform feature selection on the spliced features, and the 16 selected features were also input into SVM model, with an average classification accuracy of 99.47 % over 50 independent experiments. Therefore, urine vibrational spectroscopy combined with SVM model has great potential in the diagnosis of lupus nephritis.

狼疮肾炎（Lupus nephroritis， LN）是系统性红斑狼疮（SLE）最常见、最严重的器官表现之一，长期预后差，诊断过程复杂，因此寻找一种简单、快速、无创的诊断方法具有重要意义。本研究探讨了利用尿液样本的表面增强拉曼光谱（SERS）和傅里叶变换红外光谱（FT-IR）对健康志愿者和LN患者进行分类的可行性。获得100例LN患者和100名健康志愿者尿液样本的SERS和FT-IR数据。为了验证分类算法的稳定性，我们进行了50个独立的实验。在每个实验中，随机划分数据集，并使用支持向量机（SVM）算法（线性核函数）建立分类模型。同时，将其与其他四种常用分类算法进行比较，结果表明SVM模型的分类效果最好。50个独立实验中，SERS和FT-IR光谱结合SVM模型的平均分类准确率分别达到96.97 %和92.77 %。此外，将SERS和FT-IR的特征拼接后，结合SVM模型进行分类，对应的平均分类准确率为97.63 %。随后，利用遗传算法对拼接后的特征进行特征选择，并将选择的16个特征输入到SVM模型中，经过50次独立实验，平均分类准确率达到99.47 %。因此，尿液振动光谱结合SVM模型在狼疮性肾炎的诊断中具有很大的潜力。

{"title":"Vibrational spectroscopy of urine combined with support vector machine for lupus nephritis diagnosis research","authors":"Xiaojing Sun , Zhaonan You , Yu Du , Bingqian Ran , Guohua Wu , Ying Tan , Longfei Yin","doi":"10.1016/j.vibspec.2025.103845","DOIUrl":"10.1016/j.vibspec.2025.103845","url":null,"abstract":"<div><div>Lupus nephritis (LN) is one of the most common and serious organ manifestations of systemic lupus erythematosus (SLE), with a poor long-term prognosis and a complex diagnostic process, therefore it is important to find a simple, rapid and non-invasive method for the diagnosis of LN. This study investigated the feasibility of using surface-enhanced Raman spectroscopy (SERS) and Fourier Transform Infrared (FT-IR) spectroscopy of urine samples to classify healthy volunteers and LN patients. SERS and FT-IR data of urine samples were obtained from 100 LN patients and 100 healthy volunteers. To verify the stability of the classification algorithm, 50 independent experiments were conducted. In each experiment, the dataset was randomly divided and a classification model was established using the support vector machine (SVM) algorithm (linear kernel function). Meanwhile, it was compared with four other common classification algorithms and the results showed that SVM model had the best effect. The average classification accuracy of SERS and FT-IR spectra combined with SVM model for 50 independent experiments reached 96.97 % and 92.77 %, respectively. In addition, the features of SERS and FT-IR were spliced and then combined with SVM model for classification, corresponding to an average classification accuracy of 97.63 %. Subsequently, genetic algorithm was used to perform feature selection on the spliced features, and the 16 selected features were also input into SVM model, with an average classification accuracy of 99.47 % over 50 independent experiments. Therefore, urine vibrational spectroscopy combined with SVM model has great potential in the diagnosis of lupus nephritis.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103845"},"PeriodicalIF":3.1,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841505","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

Spectral denoising approach using enhanced wavelet packet-optimized EEMD algorithm 基于增强小波包优化EEMD算法的频谱去噪方法

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-08-05 DOI: 10.1016/j.vibspec.2025.103844

Gang Liu, Xin Chen, Yi Zhang, Haibo Liang

The quantification of hydrocarbon gases within formation fluids is paramount for the detection and evaluation of oil and gas reservoirs through well-logging geophysical techniques. Nonetheless, the spectral data are frequently fraught with complexity and noise contamination, attributable to the heterogeneous nature and extensive concentration spectrum of alkane gases, coupled with environmental interferences. This pervasive noise can markedly distort the absorption spectra, consequently compromising the accuracy of alkane gas quantification. The imperative challenge lies in the precise denoising of acquired infrared spectra while meticulously preserving the signal-to-noise ratio and spectral resolution. This present an innovative denoising methodology for infrared spectral analysis, leveraging an advanced wavelet packet coupled with an optimized Ensemble Empirical Mode Decomposition algorithm. This approach initially employs a bivariate correlation analysis to discern and isolate the noisy components within the Intrinsic Mode Functions. Subsequently, it harnesses the sample entropy of the noise signals in tandem with the Grey Wolf Optimization algorithm to ascertain the most efficacious threshold set for each IMF component. The methodology culminates in the formulation of threshold parameters through the synthesis of the sample entropy of wavelet packet coefficients with the correlation coefficients of the noise, thereby tailoring the threshold function to the distinct noise attributes of each wavelet coefficient. Empirical findings demonstrate that our approach outperforms conventional denoising techniques, achieving superior signal-to-noise ratios and resolution, with an average perturbation to characteristic peaks of less than 0.3 %.

地层流体中烃类气体的定量是利用测井地球物理技术对油气储层进行探测和评价的关键。然而，由于烷烃气体的异质性和广泛的浓度谱，再加上环境干扰，光谱数据往往充满了复杂性和噪声污染。这种普遍存在的噪声会显著地扭曲吸收光谱，从而影响烷烃气体定量的准确性。在保证红外光谱的信噪比和光谱分辨率的前提下，对采集到的红外光谱进行精确的去噪处理，这是一个迫切的挑战。本文提出了一种创新的红外光谱分析降噪方法，利用先进的小波包和优化的集成经验模态分解算法。该方法最初采用双变量相关分析来识别和隔离本征模态函数中的噪声成分。随后，利用噪声信号的样本熵与灰狼优化算法相结合，确定每个IMF分量的最有效阈值设置。该方法最终通过将小波包系数的样本熵与噪声的相关系数合成来确定阈值参数，从而根据每个小波系数的不同噪声属性定制阈值函数。实证结果表明，我们的方法优于传统的去噪技术，实现了优越的信噪比和分辨率，对特征峰的平均扰动小于0.3 %。

{"title":"Spectral denoising approach using enhanced wavelet packet-optimized EEMD algorithm","authors":"Gang Liu, Xin Chen, Yi Zhang, Haibo Liang","doi":"10.1016/j.vibspec.2025.103844","DOIUrl":"10.1016/j.vibspec.2025.103844","url":null,"abstract":"<div><div>The quantification of hydrocarbon gases within formation fluids is paramount for the detection and evaluation of oil and gas reservoirs through well-logging geophysical techniques. Nonetheless, the spectral data are frequently fraught with complexity and noise contamination, attributable to the heterogeneous nature and extensive concentration spectrum of alkane gases, coupled with environmental interferences. This pervasive noise can markedly distort the absorption spectra, consequently compromising the accuracy of alkane gas quantification. The imperative challenge lies in the precise denoising of acquired infrared spectra while meticulously preserving the signal-to-noise ratio and spectral resolution. This present an innovative denoising methodology for infrared spectral analysis, leveraging an advanced wavelet packet coupled with an optimized Ensemble Empirical Mode Decomposition algorithm. This approach initially employs a bivariate correlation analysis to discern and isolate the noisy components within the Intrinsic Mode Functions. Subsequently, it harnesses the sample entropy of the noise signals in tandem with the Grey Wolf Optimization algorithm to ascertain the most efficacious threshold set for each IMF component. The methodology culminates in the formulation of threshold parameters through the synthesis of the sample entropy of wavelet packet coefficients with the correlation coefficients of the noise, thereby tailoring the threshold function to the distinct noise attributes of each wavelet coefficient. Empirical findings demonstrate that our approach outperforms conventional denoising techniques, achieving superior signal-to-noise ratios and resolution, with an average perturbation to characteristic peaks of less than 0.3 %.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103844"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144851987","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

Near-infrared spectroscopy and ensemble learning modeling for moisture detection in forest floor leaf litter 森林凋落叶水分探测的近红外光谱与集合学习模型

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-07-25 DOI: 10.1016/j.vibspec.2025.103841

Tao Zhu, Jian Xing

The moisture content of forest floor litter is a critical indicator for assessing forest ecosystem stability and predicting wildfire risks. Traditional near-infrared (NIR) spectroscopy methods face limitations in species applicability and model accuracy. To enhance detection generalization capability and accuracy, this study proposes a moisture content detection model optimized by differential evolution (DE) algorithm and introduces an improved triangular kernel function (ITK) for least squares support vector machine (LSSVM) regression prediction, constructing a DE-LSSVM-ITK-based litter moisture content detection model. Using forest floor litter from Quercus mongolica, Fraxinus mandshurica, and Larix gmelinii as research subjects, the model employed a ten-fold cross-validation strategy to train and ensemble 10 optimal models, with the average prediction results on the test set serving as the final output. Experimental results demonstrate that the DE-LSSVM-ITK ensemble model achieves higher prediction accuracy and robustness, making it suitable for constructing moisture content detection models for different tree species. This provides a reliable technical approach for forest ecological monitoring and fire prevention.

森林凋落物含水率是评价森林生态系统稳定性和预测森林火灾风险的重要指标。传统的近红外光谱方法在物种适用性和模型精度方面存在局限性。为了提高检测泛化能力和准确性，本文提出了一种基于差分进化（DE）算法优化的含水率检测模型，并引入改进的三角核函数（ITK）用于最小二乘支持向量机（LSSVM）回归预测，构建了基于DE-LSSVM-ITK的凋落物含水率检测模型。该模型以蒙古栎、水曲柳和落叶松的森林凋落物为研究对象，采用10倍交叉验证策略对10个最优模型进行训练和集成，以测试集上的平均预测结果作为最终输出。实验结果表明，DE-LSSVM-ITK集成模型具有较高的预测精度和鲁棒性，适用于构建不同树种含水率检测模型。这为森林生态监测和防火提供了可靠的技术途径。

{"title":"Near-infrared spectroscopy and ensemble learning modeling for moisture detection in forest floor leaf litter","authors":"Tao Zhu, Jian Xing","doi":"10.1016/j.vibspec.2025.103841","DOIUrl":"10.1016/j.vibspec.2025.103841","url":null,"abstract":"<div><div>The moisture content of forest floor litter is a critical indicator for assessing forest ecosystem stability and predicting wildfire risks. Traditional near-infrared (NIR) spectroscopy methods face limitations in species applicability and model accuracy. To enhance detection generalization capability and accuracy, this study proposes a moisture content detection model optimized by differential evolution (DE) algorithm and introduces an improved triangular kernel function (ITK) for least squares support vector machine (LSSVM) regression prediction, constructing a DE-LSSVM-ITK-based litter moisture content detection model. Using forest floor litter from Quercus mongolica, Fraxinus mandshurica, and Larix gmelinii as research subjects, the model employed a ten-fold cross-validation strategy to train and ensemble 10 optimal models, with the average prediction results on the test set serving as the final output. Experimental results demonstrate that the DE-LSSVM-ITK ensemble model achieves higher prediction accuracy and robustness, making it suitable for constructing moisture content detection models for different tree species. This provides a reliable technical approach for forest ecological monitoring and fire prevention.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103841"},"PeriodicalIF":3.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722617","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

Identification of environmental microplastics using large language models: DeepSeek-R1-Distill-Llama-8B, GPT-4o, and GPT-4o-mini 使用大型语言模型识别环境微塑料：deepseek - r1 -蒸馏- llama - 8b， gpt - 40和gpt - 40 -mini

IF 3.1 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-07-23 DOI: 10.1016/j.vibspec.2025.103842

Zijiang Yang , Hisayuki Arakawa

Microplastic pollution in the environment poses increasing risks to both ecological and human health. Identifying microplastics in environmental samples is important for monitoring and mitigation. However, current methods rely on manual interpretation of infrared (IR) spectra, which is time-consuming and labor-intensive. Thus, this study investigates the potential of large language models (LLMs) for identifying microplastics using IR spectra from environmental samples. Three models, DeepSeek-R1-Distill-Llama-8B, GPT-4o-2024–08–06 (GPT-4o), and GPT-4o-mini-2024–07–18 (GPT-4o-mini), were evaluated within a structured workflow that integrates spectral processing and model implementation. A performance evaluation framework was developed to measure identification accuracy. Results indicate that DeepSeek-R1-Distill-Llama-8B outperformed others, achieving an accuracy exceeding 0.93 across all tested polymer types, making it the preferred choice. GPT-4o proved a strong alternative, particularly when local execution is impractical, with accuracy above 0.86. GPT-4o-mini underperformed and is not recommended. Despite these promising outcomes, challenges persist, including the need to optimize spectral processing parameters and refine prompt design. As the first study to apply LLMs to microplastic identification, this work offers a foundational reference for leveraging LLM-driven spectral analysis in environmental monitoring.

环境中的微塑料污染对生态和人类健康构成越来越大的风险。鉴定环境样品中的微塑料对于监测和缓解至关重要。然而，目前的方法依赖于人工解释红外光谱，这是费时费力的。因此，本研究探讨了利用环境样品的红外光谱识别微塑料的大语言模型（LLMs）的潜力。DeepSeek-R1-Distill-Llama-8B、gpt - 40 -2024 - 08 - 06 （gpt - 40）和gpt - 40 -mini-2024 - 07 - 18 （gpt - 40 -mini）三种模型在集成了光谱处理和模型实现的结构化工作流程中进行了评估。开发了一个性能评估框架来衡量识别的准确性。结果表明，DeepSeek-R1-Distill-Llama-8B优于其他方法，在所有测试的聚合物类型中实现了超过0.93的精度，使其成为首选。gpt - 40被证明是一个强大的替代方案，特别是当本地执行不切实际时，其精度高于0.86。gpt - 40 -mini表现不佳，不推荐使用。尽管取得了这些有希望的成果，但挑战依然存在，包括需要优化光谱处理参数和改进提示设计。作为第一个将llm应用于微塑料识别的研究，本工作为利用llm驱动的光谱分析在环境监测中提供了基础参考。

{"title":"Identification of environmental microplastics using large language models: DeepSeek-R1-Distill-Llama-8B, GPT-4o, and GPT-4o-mini","authors":"Zijiang Yang , Hisayuki Arakawa","doi":"10.1016/j.vibspec.2025.103842","DOIUrl":"10.1016/j.vibspec.2025.103842","url":null,"abstract":"<div><div>Microplastic pollution in the environment poses increasing risks to both ecological and human health. Identifying microplastics in environmental samples is important for monitoring and mitigation. However, current methods rely on manual interpretation of infrared (IR) spectra, which is time-consuming and labor-intensive. Thus, this study investigates the potential of large language models (LLMs) for identifying microplastics using IR spectra from environmental samples. Three models, DeepSeek-R1-Distill-Llama-8B, GPT-4o-2024–08–06 (GPT-4o), and GPT-4o-mini-2024–07–18 (GPT-4o-mini), were evaluated within a structured workflow that integrates spectral processing and model implementation. A performance evaluation framework was developed to measure identification accuracy. Results indicate that DeepSeek-R1-Distill-Llama-8B outperformed others, achieving an accuracy exceeding 0.93 across all tested polymer types, making it the preferred choice. GPT-4o proved a strong alternative, particularly when local execution is impractical, with accuracy above 0.86. GPT-4o-mini underperformed and is not recommended. Despite these promising outcomes, challenges persist, including the need to optimize spectral processing parameters and refine prompt design. As the first study to apply LLMs to microplastic identification, this work offers a foundational reference for leveraging LLM-driven spectral analysis in environmental monitoring.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103842"},"PeriodicalIF":3.1,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739301","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

Spectroscopic and genotoxic assessment of Imazamox herbicide-induced alterations in the Allium cepa model system Imazamox除草剂致葱模型系统改变的光谱和遗传毒性评估

IF 2.7 3区化学 Q2 CHEMISTRY, ANALYTICAL

Vibrational Spectroscopy

Pub Date : 2025-07-23 DOI: 10.1016/j.vibspec.2025.103843

Gulgun Cakmak-Arslan , Pinar Goc Rasgele

Imazamox (IMA), an imidazolinone herbicide, is commonly used to control weeds in crops such as sunflower, beans, peas and chickpeas. In the current study, the effects of 24 h exposure to different IMA concentrations (125, 250, and 500 ppm) on Allium cepa root tips were investigated at molecular level using Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy and genotoxicity tests. The ATR-FTIR results indicated that all doses of IMA caused an increase in lipid peroxidation levels and a decrease in tissue metabolic activity, along with a decrease in protein, carbohydrate and nucleic acid content and an increase in saturated lipid content. In addition, IMA caused important structural modifications including shortened lipid chains, reduced membrane disorder and fluidity, increased carbonyl content and lipid to protein ratio. Principal component analysis (PCA) and Hierarchical cluster analysis (HCA) confirmed these spectral alterations by effectively distinguishing control and IMA-treated groups across different doses. Genotoxicity assays further demonstrated that IMA induced various mitotic abnormalities, such as c-mitosis, irregular metaphase and micronuclei formation in A. cepa root tips. The observed structural and genotoxic changes were clearly dose-dependent, with higher concentrations causing more severe effects. These findings highlight the potential risks associated with IMA exposure and suggest that more caution should be exercised in the use of this herbicide. Furthermore, the successful application of ATR-FTIR spectroscopy to detect herbicide-induced molecular changes suggests that this technique, combined with chemometrics and A. cepa as a bioindicator model system, offers a rapid and reliable biomonitoring tool to evaluate pesticide toxicity.

Imazamox （IMA）是一种咪唑啉酮类除草剂，通常用于控制向日葵、豆类、豌豆和鹰嘴豆等作物的杂草。本研究利用衰减全反射-傅里叶变换红外（ATR-FTIR）光谱和遗传毒性试验，在分子水平上研究了24 h暴露于不同浓度的IMA（125、250和500 ppm）对洋葱根尖的影响。ATR-FTIR结果表明，所有剂量的IMA均引起脂质过氧化水平升高，组织代谢活性降低，蛋白质、碳水化合物和核酸含量降低，饱和脂质含量增加。此外，IMA引起了重要的结构修饰，包括缩短脂链，减少膜的无序性和流动性，增加羰基含量和脂蛋白比。主成分分析（PCA）和层次聚类分析（HCA）通过有效区分不同剂量的对照组和ima治疗组，证实了这些光谱变化。遗传毒性实验进一步表明，IMA诱导了A. cepa根尖的各种有丝分裂异常，如c-有丝分裂、不规则中期和微核形成。观察到的结构和基因毒性变化明显是剂量依赖性的，浓度越高，影响越严重。这些发现强调了与IMA暴露相关的潜在风险，并建议在使用这种除草剂时应更加谨慎。此外，ATR-FTIR光谱技术在除草剂诱导的分子变化检测中的成功应用表明，该技术与化学计量学和a . cepa作为生物指标模型系统相结合，为农药毒性评价提供了一种快速可靠的生物监测工具。

{"title":"Spectroscopic and genotoxic assessment of Imazamox herbicide-induced alterations in the Allium cepa model system","authors":"Gulgun Cakmak-Arslan , Pinar Goc Rasgele","doi":"10.1016/j.vibspec.2025.103843","DOIUrl":"10.1016/j.vibspec.2025.103843","url":null,"abstract":"<div><div>Imazamox (IMA), an imidazolinone herbicide, is commonly used to control weeds in crops such as sunflower, beans, peas and chickpeas. In the current study, the effects of 24 h exposure to different IMA concentrations (125, 250, and 500 ppm) on <em>Allium cepa</em> root tips were investigated at molecular level using Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy and genotoxicity tests. The ATR-FTIR results indicated that all doses of IMA caused an increase in lipid peroxidation levels and a decrease in tissue metabolic activity, along with a decrease in protein, carbohydrate and nucleic acid content and an increase in saturated lipid content. In addition, IMA caused important structural modifications including shortened lipid chains, reduced membrane disorder and fluidity, increased carbonyl content and lipid to protein ratio. Principal component analysis (PCA) and Hierarchical cluster analysis (HCA) confirmed these spectral alterations by effectively distinguishing control and IMA-treated groups across different doses. Genotoxicity assays further demonstrated that IMA induced various mitotic abnormalities, such as c-mitosis, irregular metaphase and micronuclei formation in <em>A. cepa</em> root tips. The observed structural and genotoxic changes were clearly dose-dependent, with higher concentrations causing more severe effects. These findings highlight the potential risks associated with IMA exposure and suggest that more caution should be exercised in the use of this herbicide. Furthermore, the successful application of ATR-FTIR spectroscopy to detect herbicide-induced molecular changes suggests that this technique, combined with chemometrics and <em>A. cepa</em> as a bioindicator model system, offers a rapid and reliable biomonitoring tool to evaluate pesticide toxicity.</div></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"140 ","pages":"Article 103843"},"PeriodicalIF":2.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702402","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