Altmetric Attention Score Research Articles

Does the quality of orthodontic studies influence their Altmetric Attention Score?

The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.

The Association Between Altmetric Attention Scores and Public Engagement in the Medical Literature

IntroductionWith the advent of social media and the associated increase in connectivity between scientists and the lay public, the Altmetric Attention Score has been created as a way to measure these interactions between scholarly publications and media dissemination. Little is known, however, whether these types of media exchanges measured by Altmetrics may serve as a proxy for public engagement. As such, we have sought to determine whether or not an association exists between Altmetric scores and public engagement, as measured by article citation in a health policy document. MethodsThe top 100 highest scoring articles in the medical and health sciences with respect to Altmetric Attention Scores were selected from each of 3 y (2014, 2015, and 2016). Each article was then matched to an article from the same year and journal with the highest Relative Citation Ratio (RCR) for comparison. Bivariate analysis compared article groups with respect to citation in a public policy document, open-access status, and funding status, as well as Altmetric and RCR scores. A multivariable model was then constructed to identify significant factors associated with citation in a public policy document. Finally, a contour plot was generated in order to estimate the interaction between Altmetric Scores and RCR and their comparative effects on the probability of inclusion in a health policy document. ResultsOf the 600 articles included in the analysis, 286 (48%) had been cited by a public policy article. The only difference that existed between the cohorts was for funding status, with 55 articles (40%) in the RCR cohort having received funding compared to 81 (60%) in the Altmetric cohort (P = 0.011). On bivariate analysis, both Altmetric (P = 0.0018) and RCR (P < 0.0001) scores were independently predictive of policy citation. In a multivariable model, the interaction between Altmetric Scores and RCR with respect to policy inclusion was significant (OR = 1.22; 95% CI = 1.08-1.38) and a contour plot demonstrates that either high Altmetric score or RCR alone is sufficient to generate a high probability of policy inclusion. ConclusionsScholarly article Altmetric Scores may serve as a novel means to explore public engagement in scientific research and health policy. In addition, journals that aim to impact public policy through article dissemination may benefit from engagement in social media avenues in addition to traditional citation pathways in order to encourage broader inclusion.

Bibliometric analysis of global literature productivity in systemic lupus erythematosus from 2013 to 2022.

Bibliometric analysis is a mature method for quantitative evaluation of academic productivity. In view of the rapid development of research in the field of systemic lupus erythematosus (SLE) in the past decade, we used bibliometric methods to comprehensively analyze the literature in the field of SLE from 2013 to 2022. The relevant literature in the field of SLE from 2013 to 2022 was screened in the Web of Science Core Collection database. After obtaining and sorting out the data, CiteSpace and VOSviewer software were used to visualize the relevant data, and SPSS software was used for scientific statistics. A total of 18,450 publications were included in this study. The number of articles published over the past 10years has generally shown an upward trend, while Altmetric attention scores have also shown a clear upward trend in general and in most countries. Citation analysis and Altmetric analysis can mutually prove and supplement the influence of papers. The USA, China, Japan, Italy, and the UK are the most productive countries, but China and Japan are significantly inferior to other countries in terms of research influence. Four of the top ten authors are at the center of the collaboration network. LUPUS is the most contributing journal. The theme of systemic lupus erythematosus research mainly focuses on the pathogenesis, treatment, and management of SLE, and the emerging trend is related research on machine learning and immune cells. This study shows the research status of SLE, clarifies the main contributors in this field, discusses and analyzes the research hotspots and trends in this field, and provides reference for further research in this field to promote the development of SLE research. Key Points • Through bibliometric analysis, Altmetric analysis, and visual analysis, we reveal the global productivity characteristics of SLE-related papers in the past 10years. • The number of global SLE-related studies has shown a significant increase, indicating that SLE is still a hot topic and deserves further study. • Citation analysis and Altmetric analysis can mutually prove and supplement the influence of papers, and the attention of related literature among non-professional researchers is increasing. • The theme of SLE research mainly focuses on the pathogenesis, treatment, and management of SLE. The emerging trend is machine learning and immune cells, which may provide new strategies for the diagnosis and treatment of SLE in the future.

Academic and online attention to palliative care: A bibliometric and altmetric perspective

Objective: With a combined bibliometric and altmetric study, we aimed to provide a visually detailed perspective on palliative care, which is attracting increasing attention from academia and society. We also evaluated the relationship between supporting and contrasting citation counts and the altmetric attention score (AAS) for the first time in the literature. Methods: Web of Science (WoS) database and Altmetric.com website were used to create Top100 (T100) citation and altmetric lists. Supporting and contrasting citations were found using Scite.ai database. Articles in both lists, published between 1975-2021, were analyzed in terms of study type, topic, first author, publication year, citation count, AAS, scite score, supporting and contrasting citation counts. Impact factor (IF), quartile of journal and journal citation indicator (JCI) were also examined. Results: A search of "Palliative care" in WoS yielded a total of 50.674 articles. A significant correlation was found between AAS and citation counts (p=0.001, r=0.328) in T100 citation list, and AAS and contrasting citations in T100 altmetric list (p=0,024, r=0,225). There was no statistically significant difference between IF, JCI and Q categories in both lists. Topic "PC for non-oncological diseases" were at the top of both lists. The USA, UK and Canada were countries with the most articles in T100 citation list. Conclusions: Palliative care articles that attract the attention of the academia also resonate on social media. Since AAS can be manipulated, it would be beneficial to use altmetric analysis in combination with bibliometric analysis rather than alone to formulate new policies on palliative care.

SP7.9 Correlation between Altmetric score and number of citations in 12 high impact factor medicine, surgery and anaesthesia journals

Abstract Introduction The citation count is traditionally used to measure the impact of scientific publications. The Altmetric attention score (AAS) by contrast, measures the digital dissemination of articles across social media platforms to determine their audience reach. However, whether the AAS correlates with citation counts is currently not well defined. This study, aimed to discern the correlation between citation counts and AAS in medical journals. Method We identified 12 highest impact journals in Internal Medicine, Surgery and Anaesthesia and included original articles, systematic reviews, meta-analyses, editorials and research letters published between 1 January 2019 and 31 December 2019. Up-to-date citations and AAS for each article were obtained between 1 and 7 January 2023 using a linked research information dataset, Dimensions Citation Data (https://app.dimensions.ai/discover/publication). Results We identified 2790 published manuscripts with median (IQR) AAS and citation scores of 39 (10-152) and 19 (7-56) respectively. Both scores differed by journal specialty, with the highest scores identified in Medicine and lowest in Anaesthesia journals. Randomized clincial trials had both the highest citations and AAS, with research letters having the lowest. There was a positive correlation between AAS and citations (ρ=0.4538; P&amp;lt;0.001). Other factors found to correlate with the citation scores were journal specialty (ρ=0.2047, P&amp;lt;0.001), journal impact factor(ρ=0.4538, P&amp;lt;0.001) and the type of study (ρ=0.4566, P&amp;lt;0.001). Conclusion This cross-sectional study, across 12 high impact factor specialty journals found that the AAS correlated with the citation count, suggesting that audience engagement via social media may influence the overall clinical and academic impact of publications.

Altmetric Analysis of Dermatology Manuscript Dissemination During the COVID-19 Era: Cross-Sectional Study.

Alternative bibliometrics or altmetrics, is a measure of an academic article's impact on social media outlets, which is quantified by the Altmetric Attention score (AAS). Given a lack of data for altmetric trends during the COVID-19 pandemic, we conducted a comprehensive, multivariable analysis of top dermatology manuscripts published during this time period. We aim to assess (1) the relationship between traditional bibiliometrics and Altmetrics and (2) factors associated with high AAS. All abstracted articles published in the top-5 (ranked by SCImago Journal Rankings) peer-reviewed dermatology journals published in 2021 were included in our study. We collected AAS as the dependent variable and categorical predictor variables included journal title, whether a conflict of interest existed, open access status, whether the article was related to COVID-19 or skin-of-color research, and the type of research (eg, clinical, basic science, review, etc). Numerical predictor variables consisted of the impact factor of journal, total citations, and number of authors. Multivariable linear or logistic regression models were used. The relationship between AAS and citation number was significant by multivariable analysis during the COVID-19 pandemic (P<.001). Numerous factors, including studies related to COVID-19, whether the article was open access, title of the journal, and journal impact factor were also independently related to higher AAS (P<.002). Our results validate the use of altmetrics as a complement to traditional bibliometrics, especially in times of widespread scientific interest. Despite existing in a complex realm of bibliometrics, there are also discernable patterns associated with higher AAS. This is especially relevant in the era of growing technologic importance and utility to assess the impact of scientific works within the general public.

The Online Attention to Research in Legal Medicine: An Altmetric Study on the Most Discussed Articles on the Web

Background: Online attention is a relevant research feature that can be related to its societal impact. Online attention in the field of legal medicine was explored as well as the relation between citation count and the Altmetric Attention Score (AAS). Methods: A search was performed, through the free Dimensions app, during September 2020, on the journals related to legal medicine listed in the 2019 edition of the Journal Citation Reports (JCR). The 200 published items with the highest AAS were retrieved and screened for bibliometric data. Articles with related citations were gathered from Web of Science (WOS), Scopus, and Dimensions. Results: Seventy-five percent of the articles were published by five of the selected journals. Twitter and news outlets were the most prevalent Altmetric resources. Additionally, 73.5% of the articles were published between 2013 and 2020. The most frequent topics were the ones related to toxicology and pharmacology, followed by criminalistics and law and bioethics. A poor correlation was found between the citations in WOS, Dimensions, and Scopus and the AAS. Conclusions: The online attention on legal medicine-related topics can be considered high on social media. The high number of news outlets is a distinctive feature of the most discussed articles in legal medicine. In this field of medicine, citation-based metrics combined with Altmetric can allow a broader evaluation of research findings but it should be underlined that, when measuring very different aspects of a published item, the scores in classic citation databases and Altmetric do not have a direct relation.

Altmetric analysis of the most mentioned articles online in the orthopaedic literature

Social media has become a valuable tool for the distribution of scientific content. This investigation examined the most mentioned articles in orthopaedics and identified factors concurrent with greater dissemination. Altmetric Attention Score (AAS), which measures the online attention of an article, was examined for 88,683 publications in the top 50 orthopaedic journals by 2021 impact factor. Comparative and correlational analyses were completed. Overall, average AAS and citation count of the 100 most mentioned articles were 606.7 (SD ± 272.0) and 67.55 (SD ± 98.01), respectively. These articles had primarily male first authors (75%), were produced predominantly in the United States (60%), concerned the subspecialty of sports medicine (28%), and were cross-sectional analyses (22%). There were significant differences in AAS between publications (p < 0.05) by the degree of collaboration and the type of article. Such insights can guide authors when considering avenues to increase the impact of their research.

Are libraries ready to serve gamification tools for teaching and learning? A review based on computational mapping

Purpose Gamification is an emerging technique of applying game elements to difficult and tedious learning activities to make them fun and exciting. This study aims to review the scientific landscape of the library’s readiness to adopt gamification with context to application in teaching and learning purposes based on computational tools. The present research also aims to study the growth of literature on gamification, to identify the most contributing authors, countries, affiliations and journals and collaboration status with different geographical settings. The study will also identify the most influential paper on the area with the highest citation and Altmetric Attention Score (AAS) as well as analyzing the keywords for locating the research trend in the subject area. Design/methodology/approach The study has adopted Scientometric and Altmetric approach by considering the research outputs of a decade (2013–2022) from Scopus database. First, the required data has been searched using appropriate keywords forming the search strategy by running title–abstract–keywords considering the limitation in the system. The exported data is systematically visualized for performing science mapping like the collaboration of authors, countries, organizations and co-occurrence of keywords using VOSviewer. For finding the Altmetrics score and Mendeley readership of the influential research works, the system Dimension.ai is further used. Findings The study found 928 records indicating an exponential growth over the years with total 2,750 authors. Samuel Kai Wah Chu from the University of Hong Kong, China, is the most contributed author. Spain and the USA are highly productive countries, but there needs to be a strong collaboration pattern among authors. It is found that gamification is widely applied in education discipline than any other. Some of the libraries have already implemented gamification tools for learning purposes in their services. The research on gamification still lacks social media attention and needs to be promoted more through various social media platforms for greater visibility. Originality/value The study explores the global scientific literature to identify the library’s awareness of implementing gamification tools in their services for teaching and learning purposes. As per the author’s knowledge, no such study has been conducted until date with such aims and objectives through the application of both Scientometrics and Altmetrics approaches.

Exploring the use of preprints in dentistry

ObjectiveThis study aims to assess the use, impact, and dissemination of preprints in dentistry. MethodsThis is a meta-research study with a cross-sectional design. We included preprints published in dentistry, regardless of the year of publication. Searches were performed in the medRxiv.org and Preprints.org platforms and restricted to English. One researcher extracted the data, and another researcher verified data consistency. The following data were extracted: year of publication, country of the corresponding author, number of abstract and full-text views and downloads, Altmetric attention score, whether the preprint was mentioned in other servers such as Twitter and Publons, number of mentions in other servers, number of citations in the Dimensions database, and whether the preprint had already been published in a peer-reviewed journal. If already published, we extracted the journal's impact factor (JCR 2021) and the number of citations in the Dimensions database. We conducted a descriptive analysis of the extracted characteristics and explored relationships between metrics using the Spearman correlation. ResultsWe identified 276 preprints. Most of the studies were published between 2020 and 2022 (n = 229), especially those from ten countries. The most-cited preprint and published article are the same study. Only the correlation between the number of preprint citations and peer-reviewed article citations in the Dimensions database showed a large positive association (Spearman's rho = 0.5809). ConclusionPreprints gained popularity over the last several years due to the COVID-19 pandemic and reached a larger audience, especially on platforms such as Twitter. Clinical significancePreprint publishing allows faster dissemination of science for the benefit of society.

Correlation Between Altmetric Scores and Citation Count in 4 High-Impact Plastic Surgery Journals.

The Altmetric Attention Score (AAS) aims to determine the impact of research articles throughout the internet and social media outlets. The AAS is a weighted average of the interaction on platforms including Twitter, Facebook, Reddit, and more. The aim of this study was to investigate the relationship between the AAS and traditional bibliometrics across plastic surgery journals. Articles, number of citations (NOC), and H-index information in Annals of Plastic Surgery (APS), Plastic and Reconstructive Surgery (PRS), Plastic and Reconstructive Surgery Global Open (PRS GO), and Aesthetic Surgery Journal (ASJ) from 2017, 2018, and 2019 were queried with the Scopus Online Tool. AAS metrics were collected with the Altmetric Score Calculator Bookmarklet. Descriptive statistics, Spearman rank-correlation analyses, and analyses of variance were performed to measure associations between NOC and AAS. A total of 3612 articles were analyzed. NOC was weakly correlated with AAS in APS, PRS GO, and ASJ, and moderately correlated with AAS in PRS. NOC was weakly correlated with Twitter mentions in APS, PRS GO, and ASJ, and moderately correlated in PRS. NOC was weakly correlated with news outlet reporting. The H-index of the first author showed more significant correlations with the AAS than the H-index of the last author. NOC and H-index of the first author correlated with AAS in the plastic surgery literature, suggesting AAS may be a useful adjunct to traditional bibliometrics when evaluating the impact and reach of peer-reviewed articles.

THE ASSOCIATION BETWEEN ALTMETRIC, PLUMX METRICS AND CITATION COUNT OF PUBLICATIONS: A CROSS-SECTIONAL STUDY AMONG TOP CHILD AND ADOLESCENT PSYCHIATRY JOURNALS.

Altmetric Attention Score (AAS) and PlumX Metrics are becoming important to evaluate the impact of the publication in addition to classical scientific rating method such as citation count and impact factor. These metrics collect data about publications&apos; tweet count, Facebook interaction count and other social interactions. In this study, it is aimed to examine the association between AAS, PlumX Metrics and citation count of top child and adolescent psychiatry. We identified the five journals and retrospectively analysed the publications published in 2019. All the original research articles, met analysis, and reviews were analysed. The articles were divided into two groups as original articles/research articles and meta-analysis/systematic review. We have hypothesized that there could be a positive correlation between AAS and PlumX Metrics data and citation count among these journals and there could be a difference between AAS, PlumX scores and citation count between original articles/research articles and meta-analysis/systematic review as their reading potential is different. We have found a significant positive correlation between citation count, AAS and PlumX Metrics. This association continued after controlling the journal impact factor. In linear regression analysis, type of publication, total count of tweets, and Mendeley reads predicted the citation count. In addition to the classical methods measuring the quality of the articles such as the total citation count and impact factor, the importance of AAS and PlumX Metrics has been increasing. It is important to share scientific publications on these platforms in order to increase the impact of the articles.

Assessment of the dissemination of COVID-19 articles across social media: An Altmetrics Study.

The use of social media assists in the distribution of information about COVID-19 to the general public and health professionals. Alternative-level metrics (Altmetrics) is an alternative method to traditional bibliometrics that assess the amount of sharing and spreading of a scientific article on social media platforms. Our objective was to characterize and compare traditional bibliometrics (citation-count) with newer metrics (Altmetric Attention Score) of the top 100 Altmetric scored COVID-19 articles. The 100 highest Altmetric Attention Score (AAS) articles were identified utilizing the Altmetric explorer in May 2020. AAS, journal name, and mentions from various social media databases (Twitter, Facebook, Wikipedia, Reddit, Mendeley, Dimension) of each article were collected. Citation-counts were collected from the Scopus database. The median AAS and citation-count were 4922.50 and 24.00, respectively. Of 100 articles, The New England Journal of Medicine published the most articles at 18% (18/100). Twitter was the most frequently used social media platform with 96.3% of the mentions (985,429/1,022,975). Positive correlations were seen between AAS and citation-count (r2=.0973; P=.002). Our research characterized the top 100 articles by AAS regarding COVID-19 in the Altmetric database. Altmetrics could complement with traditional citation-count when assessing the dissemination of an article regarding COVID-19. RR2-10.2196/21408.

The top 100 most cited Mohs micrographic surgery articles: an analysis of Altmetrics data from 2010 to 2020.

With skin cancer rates rising, there is a consistent stream of literature published on Mohs micrographic surgery (MMS). However, there are no studies examining MMS article visibility and readership patterns. The Altmetric Attention Score (AAS) is a metric that quantifies article distribution on media platforms. We analyzed the 100 most cited MMS publications from 2010 to 2020 and constructed multivariate regression models using top 25th percentile AASs and mentions on Facebook, Twitter, and new outlets as outcome variables. Articles with an AAS in the top 25th quartile consistently performed better with higher citations, Twitter mentions, Facebook mentions, and journal impact factors compared to articles in the lower three quartiles (53.8 vs 33.9; 4.68 vs 0.44; 0.32 vs 0.08; 53.5 vs 14.6; p < 0.05 for all). There were significantly lower female last authors versus males in the top quartile of AAS articles, with males 142 times more likely to have articles in the top quartile (p < 0.05). Studies comparing MMS to other surgical techniques and funded articles had higher odds of being in the top quartile of AASs (aOR 29.63 p < 0.05; aOR 74.50 p < 0.05). AASs can be useful to understand public interest, readership, and article features that influence the reach of MMS literature.

Do linguistic features of research article titles affect received online attention? A corpus-based analysis

Purpose Scientific impact is traditionally assessed with citation-based metrics. Recently, altmetric indices have been introduced to measure scientific impact both within academia and among the general public. However, little research has investigated the association between the linguistic features of research article titles and received online attention. To address this issue, the authors examined in the present study the relationship between a series of title features and altmetric attention scores.Design/methodology/approach The data included 8,658 titles of Science articles. The authors extracted six features from the title corpus (i.e. mean word length, lexical sophistication, lexical density, title length, syntactic dependency length and sentiment score). The authors performed Spearman’s rank analyses to analyze the correlations between these features and online impact. The authors then conducted a stepwise backward multiple regression to identify predictors for the articles' online impact.Findings The correlation analyses revealed weak but significant correlations between all six title features and the altmetric attention scores. The regression analysis showed that four linguistic features of titles (mean word length, lexical sophistication, title length and sentiment score) have modest predictive effects on the online impact of research articles.Originality/value In the internet era with the widespread use of social media and online platforms, it is becoming increasingly important for researchers to adapt to the changing context of research evaluation. This study identifies several linguistic features that deserve scholars’ attention in the writing of article titles. It also has practical implications for academic administrators and pedagogical implications for instructors of academic writing courses.

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ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTIssue Editorial MastheadCite this: Acc. Mater. Res. 2023, 4, 6, XXX-XXXPublication Date (Web):June 23, 2023Publication History Published online23 June 2023Published inissue 23 June 2023https://doi.org/10.1021/mrv004i006_1695121Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (194 KB) Get e-Alertsclose Get e-Alerts

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ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTIssue Editorial MastheadCite this: ACS Appl. Nano Mater. 2023, 6, 12, XXX-XXXPublication Date (Web):June 23, 2023Publication History Published online23 June 2023Published inissue 23 June 2023https://doi.org/10.1021/anv006i012_1695010Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (168 KB) Get e-Alertsclose Get e-Alerts

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ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTIssue Editorial MastheadCite this: ACS Sens. 2023, 8, 6, XXX-XXXPublication Date (Web):June 23, 2023Publication History Published online23 June 2023Published inissue 23 June 2023https://doi.org/10.1021/sev008i006_1695276Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (258 KB) Get e-Alertsclose Get e-Alerts

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ADVERTISEMENT RETURN TO ISSUEPREVArticleIssue Publication InformationCite this: ACS Appl. Nano Mater. 2023, 6, 12, XXX-XXXPublication Date (Web):June 23, 2023Publication History Published online23 June 2023Published inissue 23 June 2023https://doi.org/10.1021/anv006i012_1695009Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (124 KB) Get e-Alertsclose Get e-Alerts

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ADVERTISEMENT RETURN TO ISSUEPREVArticleIssue Publication InformationCite this: ACS Appl. Opt. Mater. 2023, 1, 6, XXX-XXXPublication Date (Web):June 23, 2023Publication History Published online23 June 2023Published inissue 23 June 2023https://doi.org/10.1021/otv001i006_1695105Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views-Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (199 KB) Get e-Alertsclose Get e-Alerts