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175 results on '"Ghosh, Sujit K."'

1. Forecasting Malaria in Indian States: A Time Series Approach with R Shiny Integration

Author

Ghosh, Sujit K., Ananthakumar, Usha, Chougale, Praveen D., and Somaraj, Adithya B.

Subjects
Statistics - Applications
Abstract

Malaria remains a significant public health challenge in many regions, necessitating robust predictive models to aid in its management and prevention. This study focuses on developing and evaluating time series models for forecasting malaria cases across eight Indian states: Jharkhand, Chhattisgarh, Maharashtra, Meghalaya, Mizoram, Odisha, Tripura, and Uttar Pradesh. We employed various modeling approaches, including polynomial regression with seasonal components, log-transformed polynomial regression, lagged difference models, and ARIMA models, to capture the temporal dynamics of malaria incidence. Comprehensive model fitting, residual analysis, and performance evaluation using metrics such as Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) indicated that the log-transformed polynomial regression model consistently outperformed other models in terms of accuracy and robustness across all states. Rolling forecast validation further confirmed the superior predictive capability of the log-transformed model over time. Additionally, an interactive R Shiny tool was developed to facilitate the use of these predictive models by researchers and public health officials. This tool allows users to input data, select modeling approaches, and visualize predictions and performance metrics, providing a practical tool for real-time malaria forecasting and decision-making support. Our findings highlight the critical role of appropriate modeling techniques in malaria prediction and offer valuable resources for enhancing malaria surveillance and response efforts., Comment: 18 pages

Published
2024

2. Functional Time Transformation Model with Applications to Digital Health

Author

Ghosal, Rahul, Matabuena, Marcos, and Ghosh, Sujit K.

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

The advent of wearable and sensor technologies now leads to functional predictors which are intrinsically infinite dimensional. While the existing approaches for functional data and survival outcomes lean on the well-established Cox model, the proportional hazard (PH) assumption might not always be suitable in real-world applications. Motivated by physiological signals encountered in digital medicine, we develop a more general and flexible functional time-transformation model for estimating the conditional survival function with both functional and scalar covariates. A partially functional regression model is used to directly model the survival time on the covariates through an unknown monotone transformation and a known error distribution. We use Bernstein polynomials to model the monotone transformation function and the smooth functional coefficients. A sieve method of maximum likelihood is employed for estimation. Numerical simulations illustrate a satisfactory performance of the proposed method in estimation and inference. We demonstrate the application of the proposed model through two case studies involving wearable data i) Understanding the association between diurnal physical activity pattern and all-cause mortality based on accelerometer data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 and ii) Modelling Time-to-Hypoglycemia events in a cohort of diabetic patients based on distributional representation of continuous glucose monitoring (CGM) data. The results provide important epidemiological insights into the direct association between survival times and the physiological signals and also exhibit superior predictive performance compared to traditional summary based biomarkers in the CGM study.

Published
2024

4. Beyond 2-D Mass-Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions

Author

Kanodia, Shubham, He, Matthias Y., Ford, Eric B., Ghosh, Sujit K., and Wolfgang, Angie

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Fundamental to our understanding of planetary bulk compositions is the relationship between their masses and radii, two properties that are often not simultaneously known for most exoplanets. However, while many previous studies have modeled the two-dimensional relationship between planetary mass and radii, this approach largely ignores the dependencies on other properties that may have influenced the formation and evolution of the planets. In this work, we extend the existing nonparametric and probabilistic framework of \texttt{MRExo} to jointly model distributions beyond two dimensions. Our updated framework can now simultaneously model up to four observables, while also incorporating asymmetric measurement uncertainties and upper limits in the data. We showcase the potential of this multi-dimensional approach to three science cases: (i) a 4-dimensional joint fit to planetary mass, radius, insolation, and stellar mass, hinting of changes in planetary bulk density across insolation and stellar mass; (ii) a 3-dimensional fit to the California Kepler Survey sample showing how the planet radius valley evolves across different stellar masses; and (iii) a 2-dimensional fit to a sample of Class-II protoplanetary disks in Lupus while incorporating the upper-limits in dust mass measurements. In addition, we employ bootstrap and Monte-Carlo sampling to quantify the impact of the finite sample size as well as measurement uncertainties on the predicted quantities. We update our existing open-source user-friendly \texttt{MRExo} \texttt{Python} package with these changes, which allows users to apply this highly flexible framework to a variety of datasets beyond what we have shown here., Comment: Accepted in ApJ. Updated MRExo package and sample scripts available here: https://github.com/shbhuk/mrexo/tree/v1.0dev. Package will be released on PyPI (pip) along with full documentation upon publication in ApJ

Published
2023

5. Bayesian estimation of clustered dependence structures in functional neuroconnectivity

Author

Kim, Hyoshin, Ghosh, Sujit K., Di Martino, Adriana, and Hector, Emily C.

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

Motivated by the need to model the dependence between regions of interest in functional neuroconnectivity for efficient inference, we propose a new sampling-based Bayesian clustering approach for covariance structures of high-dimensional Gaussian outcomes. The key technique is based on a Dirichlet process that clusters covariance sub-matrices into independent groups of outcomes, thereby naturally inducing sparsity in the whole brain connectivity matrix. A new split-merge algorithm is employed to achieve convergence of the Markov chain that is shown empirically to recover both uniform and Dirichlet partitions with high accuracy. We investigate the empirical performance of the proposed method through extensive simulations. Finally, the proposed approach is used to group regions of interest into functionally independent groups in the Autism Brain Imaging Data Exchange participants with autism spectrum disorder and and co-occurring attention-deficit/hyperactivity disorder., Comment: 23 pages, 8 figures, 2 tables

Published
2023

6. Distributional outcome regression via quantile functions and its application to modelling continuously monitored heart rate and physical activity

Author

Ghosal, Rahul, Ghosh, Sujit K., Schrack, Jennifer A., and Zipunnikov, Vadim

Subjects
Statistics - Methodology
Abstract

Modern clinical and epidemiological studies widely employ wearables to record parallel streams of real-time data on human physiology and behavior. With recent advances in distributional data analysis, these high-frequency data are now often treated as distributional observations resulting in novel regression settings. Motivated by these modelling setups, we develop a distributional outcome regression via quantile functions (DORQF) that expands existing literature with three key contributions: i) handling both scalar and distributional predictors, ii) ensuring jointly monotone regression structure without enforcing monotonicity on individual functional regression coefficients, iii) providing statistical inference via asymptotic projection-based joint confidence bands and a statistical test of global significance to quantify uncertainty of the estimated functional regression coefficients. The method is motivated by and applied to Actiheart component of Baltimore Longitudinal Study of Aging that collected one week of minute-level heart rate (HR) and physical activity (PA) data on 781 older adults to gain deeper understanding of age-related changes in daily life heart rate reserve, defined as a distribution of daily HR, while accounting for daily distribution of physical activity, age, gender, and body composition. Intriguingly, the results provide novel insights in epidemiology of daily life heart rate reserve.

Published
2023

24. Preferential separation of a radioactive TcO4− surrogate from a mixture of oxoanions by a cationic MOF.

Author

Fajal, Sahel, Ghosh, Dipayan, Mandal, Writakshi, and Ghosh, Sujit K.

Abstract

Preferential trapping of a selected metal-oxoanion from a mixture of other metal-oxoanionic toxic pollutants in water has been demonstrated by implementing energy-efficient adsorption followed by the ion-exchange method, utilizing a hydrolytically stable cationic metal–organic framework (MOF). The cationic MOF exhibits ultrafast and selective extraction efficiency towards ReO4− (a surrogate anion of radioactive TcO4−) over other metal-oxoanions in contaminated water systems. [ABSTRACT FROM AUTHOR]

Published
2024
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25. A Wearable System for Continuous Monitoring and Assessment of Speech, Gait, and Cognitive Decline for Early Diagnosis of ADRD

Author

Dieffenderfer, James, primary, Brewer, Alec, additional, Noonan, Maxwell A., additional, Smith, Madeline, additional, Eichenlaub, Emily, additional, Haley, Katarina L., additional, Jacks, Adam, additional, Lobaton, Edgar, additional, Neupert, Shevaun D., additional, Hess, Thomas M., additional, Franz, Jason R., additional, Ghosh, Sujit K., additional, Misra, Veena, additional, and Bozkurt, Alper, additional

Published
2023
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27. Unraveling mechanistic insights into covalent organic frameworks for highly efficient sequestration of organic iodides from simulated nuclear waste.

Author

Fajal, Sahel, Majumder, Dipanjan, Mandal, Writakshi, Let, Sumanta, Dam, Gourab K., Shirolkar, Mandar M., and Ghosh, Sujit K.

Abstract

Over the last few decades, given the impending global energy and environmental crises, paramount development in nuclear energy as an alternative high power density and low-carbon energy source has been widely observed. However, this development is hindered due to certain problems associated with nuclear reactors, including the emission of volatile radioactive substances, like organic iodides and iodine, which must be eliminated before releasing the off-gas. These substances include methyl iodide (CH3I), ethyl iodide (CH3CH2I), and iodine, which are exceedingly harmful to both the environment and human health. Although several porous solid adsorbents have been successfully employed to sequester organic iodides (generally CH3I) from the vapor phase, the majority of the earlier investigations have largely focused on the saturation capacity and kinetic study of CH3I capture. However, the importance of the porous adsorbents' strategic functions in the unique binding interaction with organic iodides has been grossly underappreciated and poorly understood. Also, certain crucial difficulties pertaining to the practical capturing of radioactive organic iodides from nuclear waste were thwarted in the endeavors to construct innovative adsorbents. Herein, we have demonstrated a systematic strategy-driven study to understand the roles of framework-integrated functionalities towards organic iodide sequestration by varying the number of N-heteroatomic sites in a series of chemically stable porous covalent organic frameworks (COFs). The CH3I adsorption capacity was found to be positively correlated with the porosity or surface area as well as with the N-heteroatomic or heterocyclic functionalities, such as the imine, pyridine, and triazine sites of these COFs. Under both static and dynamic conditions, all the COFs exhibited high CH3I sorption capacities through the N-methylation reaction mechanism. This work is of fundamental importance to understanding the CH3I adsorption mechanisms and also offers direction for the design and development of novel adsorbents for relevant applications. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Cadmium-based Catalysts

Author

Mukherjee, Soumya and Ghosh, Sujit K.

Abstract

Catalytic processes, especially those involving metals carry upmost significance in the chemical industry, owing to their widespread usage and intertwined applications. The term ‘‘peak metal’’ has emerged in the last decade, as an outcome of the threat of metal depletion in the Earth’s crust. The imminent future crisis, a consequence of the rapidly growing world population along with incessant technological developments, is predicted to result in some of these metals running out in about twenty years onward. The severity of dealing with the aforementioned metal crisis is only somewhat toned down by the fact that, in contrast to fossil fuels, metals can be recycled in a judicious manner.3 Cadmium, which possesses substantial catalytic activity as recognised in the literature, is considered to possess limited availability and there is a potential future risk to provide an adequate supply of this metal. This compels the development of a new generation of cadmium-based catalysts. The discussion in this chapter focuses on literature-reports of the catalytic activities of diverse cadmium-based materials, in an attempt to present a concise overview of all the cadmium catalysts’ activities, leading to a prospective growth on this field of cadmium-based sustainable catalysis.

Published
2023
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42. Highly Stable and End‐group Tuneable Metal–Organic Framework/Polymer Composite for Superior Triboelectric Nanogenerator Application

Author

More, Yogeshwar D., primary, Saurabh, Satyam, additional, Mollick, Samraj, additional, Singh, Sachin Kumar, additional, Dutta, Subhajit, additional, Fajal, Sahel, additional, Prathamshetti, Anil, additional, Shirolkar, Mandar M., additional, Panchal, Suresh, additional, Wable, Minal, additional, Ogale, Satishchandra, additional, and Ghosh, Sujit K., additional

Published
2022
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45. How Reproducible are Surface Areas Calculated from the BET Equation? (Adv. Mater. 27/2022)

Author

Osterrieth, Johannes W. M., primary, Rampersad, James, additional, Madden, David, additional, Rampal, Nakul, additional, Skoric, Luka, additional, Connolly, Bethany, additional, Allendorf, Mark D., additional, Stavila, Vitalie, additional, Snider, Jonathan L., additional, Ameloot, Rob, additional, Marreiros, João, additional, Ania, Conchi, additional, Azevedo, Diana, additional, Vilarrasa‐Garcia, Enrique, additional, Santos, Bianca F., additional, Bu, Xian‐He, additional, Chang, Ze, additional, Bunzen, Hana, additional, Champness, Neil R., additional, Griffin, Sarah L., additional, Chen, Banglin, additional, Lin, Rui‐Biao, additional, Coasne, Benoit, additional, Cohen, Seth, additional, Moreton, Jessica C., additional, Colón, Yamil J., additional, Chen, Linjiang, additional, Clowes, Rob, additional, Coudert, François‐Xavier, additional, Cui, Yong, additional, Hou, Bang, additional, D'Alessandro, Deanna M., additional, Doheny, Patrick W., additional, Dincă, Mircea, additional, Sun, Chenyue, additional, Doonan, Christian, additional, Huxley, Michael Thomas, additional, Evans, Jack D., additional, Falcaro, Paolo, additional, Ricco, Raffaele, additional, Farha, Omar, additional, Idrees, Karam B., additional, Islamoglu, Timur, additional, Feng, Pingyun, additional, Yang, Huajun, additional, Forgan, Ross S., additional, Bara, Dominic, additional, Furukawa, Shuhei, additional, Sanchez, Eli, additional, Gascon, Jorge, additional, Telalović, Selvedin, additional, Ghosh, Sujit K., additional, Mukherjee, Soumya, additional, Hill, Matthew R., additional, Sadiq, Muhammed Munir, additional, Horcajada, Patricia, additional, Salcedo‐Abraira, Pablo, additional, Kaneko, Katsumi, additional, Kukobat, Radovan, additional, Kenvin, Jeff, additional, Keskin, Seda, additional, Kitagawa, Susumu, additional, Otake, Ken‐ichi, additional, Lively, Ryan P., additional, DeWitt, Stephen J. A., additional, Llewellyn, Phillip, additional, Lotsch, Bettina V., additional, Emmerling, Sebastian T., additional, Pütz, Alexander M., additional, Martí‐Gastaldo, Carlos, additional, Padial, Natalia M., additional, García‐Martínez, Javier, additional, Linares, Noemi, additional, Maspoch, Daniel, additional, Suárez del Pino, Jose A., additional, Moghadam, Peyman, additional, Oktavian, Rama, additional, Morris, Russel E., additional, Wheatley, Paul S., additional, Navarro, Jorge, additional, Petit, Camille, additional, Danaci, David, additional, Rosseinsky, Matthew J., additional, Katsoulidis, Alexandros P., additional, Schröder, Martin, additional, Han, Xue, additional, Yang, Sihai, additional, Serre, Christian, additional, Mouchaham, Georges, additional, Sholl, David S., additional, Thyagarajan, Raghuram, additional, Siderius, Daniel, additional, Snurr, Randall Q., additional, Goncalves, Rebecca B., additional, Telfer, Shane, additional, Lee, Seok J., additional, Ting, Valeska P., additional, Rowlandson, Jemma L., additional, Uemura, Takashi, additional, Iiyuka, Tomoya, additional, van der Veen, Monique A., additional, Rega, Davide, additional, Van Speybroeck, Veronique, additional, Rogge, Sven M. J., additional, Lamaire, Aran, additional, Walton, Krista S., additional, Bingel, Lukas W., additional, Wuttke, Stefan, additional, Andreo, Jacopo, additional, Yaghi, Omar, additional, Zhang, Bing, additional, Yavuz, Cafer T., additional, Nguyen, Thien S., additional, Zamora, Felix, additional, Montoro, Carmen, additional, Zhou, Hongcai, additional, Kirchon, Angelo, additional, and Fairen‐Jimenez, David, additional

Published
2022
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49. How Reproducible are Surface Areas Calculated from the BET Equation?

Author

Universidad de Alicante. Departamento de Química Inorgánica, Osterrieth, Johannes W. M., Rampersad, James, Madden, David G., Rampal, Nakul, Skoric, Luka, Connolly, Bethany M., Allendorf, Mark D., Stavila, Vitalie, Snider, Jonathan L., Ameloot, Rob, Marreiros, João, Coudert, François-Xavier, Cui, Yong, Hou, Bang, D'Alessandro, Deanna M., Doheny, Patrick W., Dincă, Mircea, Sun, Chenyue, Doonan, Christian, Huxley, Michael Thomas, Evans, Jack D., Bara, Dominic, Falcaro, Paolo, Ricco, Raffaele, Farha, Omar, Idrees, Karam B., Islamoglu, Timur, Feng, Pingyun, Yang, Huajun, Forgan, Ross S., Furukawa, Shuhei, Sanchez, Eli, Gascon, Jorge, Telalović, Selvedin, Ghosh, Sujit K., Mukherjee, Soumya, Hill, Matthew R., Sadiq, Muhammed Munir, Horcajada, Patricia, DeWitt, Stephen J. A., Salcedo-Abraira, Pablo, Kaneko, Katsumi, Kukobat, Radovan, Kenvin, Jeff, Keskin, Seda, Kitagawa, Susumu, Otake, Ken-ichi, Lively, Ryan P., Llewellyn, Phillip L., Lotsch, Bettina V., Emmerling, Sebastian T., Pütz, Alexander M., Martí-Gastaldo, Carlos, Padial, Natalia M., Garcia-Martinez, Javier, Linares, Noemi, Maspoch, Daniel, Rosseinsky, Matthew J., Suárez del Pino, Jose A., Moghadam, Peyman Z., Oktavian, Rama, Morris, Russel E., Wheatley, Paul S., Navarro, Jorge, Petit, Camille, Danaci, David, Katsoulidis, Alexandros P., Schröder, Martin, Han, Xue, Yang, Sihai, Serre, Christian, Mouchaham, Georges, Sholl, David S., Thyagarajan, Raghuram, Siderius, Daniel, van der Veen, Monique A., Snurr, Randall Q., Goncalves, Rebecca B., Telfer, Shane, Lee, Seok J., Ting, Valeska P., Rowlandson, Jemma L., Uemura, Takashi, Iiyuka, Tomoya, Rega, Davide, Van Speybroeck, Veronique, Rogge, Sven M.J., Lamaire, Aran, Walton, Krista S., Bingel, Lukas W., Wuttke, Stefan, Andreo, Jacopo, Yaghi, Omar, Ania, Conchi O., Zhang, Bing, Yavuz, Cafer T., Nguyen, Thien S., Zamora, Félix, Montoro, Carmen, Zhou, Hongcai, Kirchon, Angelo, Fairen-Jimenez, David, Azevedo, Diana, Vilarrasa-García, Enrique, Santos, Bianca F., Bu, Xian-He, Chang, Ze, Bunzen, Hana, Champness, Neil R., Griffin, Sarah L., Chen, Banglin, Lin, Rui-Biao, Coasne, Benoit, Cohen, Seth, Moreton, Jessica C., Colón, Yamil J., Chen, Linjiang, Clowes, Rob, Universidad de Alicante. Departamento de Química Inorgánica, Osterrieth, Johannes W. M., Rampersad, James, Madden, David G., Rampal, Nakul, Skoric, Luka, Connolly, Bethany M., Allendorf, Mark D., Stavila, Vitalie, Snider, Jonathan L., Ameloot, Rob, Marreiros, João, Coudert, François-Xavier, Cui, Yong, Hou, Bang, D'Alessandro, Deanna M., Doheny, Patrick W., Dincă, Mircea, Sun, Chenyue, Doonan, Christian, Huxley, Michael Thomas, Evans, Jack D., Bara, Dominic, Falcaro, Paolo, Ricco, Raffaele, Farha, Omar, Idrees, Karam B., Islamoglu, Timur, Feng, Pingyun, Yang, Huajun, Forgan, Ross S., Furukawa, Shuhei, Sanchez, Eli, Gascon, Jorge, Telalović, Selvedin, Ghosh, Sujit K., Mukherjee, Soumya, Hill, Matthew R., Sadiq, Muhammed Munir, Horcajada, Patricia, DeWitt, Stephen J. A., Salcedo-Abraira, Pablo, Kaneko, Katsumi, Kukobat, Radovan, Kenvin, Jeff, Keskin, Seda, Kitagawa, Susumu, Otake, Ken-ichi, Lively, Ryan P., Llewellyn, Phillip L., Lotsch, Bettina V., Emmerling, Sebastian T., Pütz, Alexander M., Martí-Gastaldo, Carlos, Padial, Natalia M., Garcia-Martinez, Javier, Linares, Noemi, Maspoch, Daniel, Rosseinsky, Matthew J., Suárez del Pino, Jose A., Moghadam, Peyman Z., Oktavian, Rama, Morris, Russel E., Wheatley, Paul S., Navarro, Jorge, Petit, Camille, Danaci, David, Katsoulidis, Alexandros P., Schröder, Martin, Han, Xue, Yang, Sihai, Serre, Christian, Mouchaham, Georges, Sholl, David S., Thyagarajan, Raghuram, Siderius, Daniel, van der Veen, Monique A., Snurr, Randall Q., Goncalves, Rebecca B., Telfer, Shane, Lee, Seok J., Ting, Valeska P., Rowlandson, Jemma L., Uemura, Takashi, Iiyuka, Tomoya, Rega, Davide, Van Speybroeck, Veronique, Rogge, Sven M.J., Lamaire, Aran, Walton, Krista S., Bingel, Lukas W., Wuttke, Stefan, Andreo, Jacopo, Yaghi, Omar, Ania, Conchi O., Zhang, Bing, Yavuz, Cafer T., Nguyen, Thien S., Zamora, Félix, Montoro, Carmen, Zhou, Hongcai, Kirchon, Angelo, Fairen-Jimenez, David, Azevedo, Diana, Vilarrasa-García, Enrique, Santos, Bianca F., Bu, Xian-He, Chang, Ze, Bunzen, Hana, Champness, Neil R., Griffin, Sarah L., Chen, Banglin, Lin, Rui-Biao, Coasne, Benoit, Cohen, Seth, Moreton, Jessica C., Colón, Yamil J., Chen, Linjiang, and Clowes, Rob

Abstract

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Published
2022

50. How Reproducible are Surface Areas Calculated from the BET Equation?

Author

European Commission, European Research Council, University of Cambridge, Trinity College Cambridge, National Nuclear Security Administration (US), Department of Energy (US), Alexander von Humboldt Foundation, Center for Advancing Electronics Dresden, Science and Engineering Research Board (India), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Universidad de Alicante, Research Foundation - Flanders, Engineering and Physical Sciences Research Council (UK), National Research Foundation of Korea, Indonesia Endowment Fund for Education, National Institute of Standards and Technology (US), Osterrieth, Johannes W. M., Rampersad, James, Madden, David, Rampal, Nakul, Skoric, Luka, Connolly, Bethany, Allendorf, Mark D., Stavila, Vitalie, Snider, Jonathan L., Ameloot, Rob, Marreiros, João, Bara, Dominic, Furukawa, Shuhei, Sánchez, Eli, Gascón, Jorge, Telalović, Selvedin, Ghosh, Sujit K., Mukherjee, Soumya, Hill, Matthew R., Sadiq, Muhammed Munir, Horcajada, Patricia, DeWitt, Stephen J. A., Salcedo Abraira, Pablo, Kaneko, Katsumi, Kukobat, Radovan, Kenvin, Jeff, Keskin, Seda, Kitagawa, Susumu, Otake, Ken-Ichi, Lively, Ryan P., Llewellyn, Phillip, Lotsch, Bettina V., Emmerling, Sebastian T., Pütz, Alexander M., Martí-Gastaldo, Carlos, Padial, Natalia M., García-Martínez, Javier, Linares, Noemí, Maspoch, Daniel, Rosseinsky, Matthew J., Suárez, José Antonio, Moghadam, Peyman, Oktavian, Rama, Morris, Russell E., Wheatley, Paul S., Navarro, Jorge, Petit, Camille, Danaci, David, Katsoulidis, Alexandros P., Schröder, Martin, Han, Xue, Yang, Sihai, Serre, Christian, Mouchaham, Georges, Sholl, David S., Thyagarajan, Raghuram, Siderius, Daniel, Veen, Monique A. van der, Snurr, Randall Q., Goncalves, Rebecca B., Telfer, Shane, Lee, Seok J., Ting, Valeska P., Rowlandson, Jemma L., Uemura, Takashi, Iiyuka, Tomoya, Rega, Davide, Speybroeck, Veronique van, Rogge, Sven M. J., Lamaire, Aran, Walton, Krista S., Bingel, Lukas W., Wuttke, Stefan, Andreo, Jacopo, Yaghi, Omar, Ania, Conchi O., Zhang, Bing, Yavuz, Cafer T., Nguyen, Thien S., Zamora, Félix, Montoro, Carmen, Zhou, Hongcai, Kirchon, Angelo, Fairen-Jiménez, David, Azevedo, Diana, Vilarrasa-García, E., Santos, Bianca S., Bu, Xian-He, Chang, Ze, Bunzen, Hana, Champness, Neil R., Griffin, Sarah L., Chen, Banglin, Lin, Rui-Biao, Coasne, Benoit, Cohen, Seth, Moreton, Jessica C., Colón, Yamil J., Chen, Linjiang, Clowes, Rob, Coudert, François Xavier, Cui, Yong, Hou, Bang, D'Alessandro, Deanna M., Doheny, Patrick W., Dincă, Mircea, Sun, Chenyue, Doonan, Christian J., Huxley, Michael Thomas, Evans, Jack D., Falcaro, Paolo, Ricco, Raffaele, Farha, Omar, Idrees, Karam B., Islamoglu, Timur, Feng, Pingyun, Chang, Huajun, Forgan, Ross S., European Commission, European Research Council, University of Cambridge, Trinity College Cambridge, National Nuclear Security Administration (US), Department of Energy (US), Alexander von Humboldt Foundation, Center for Advancing Electronics Dresden, Science and Engineering Research Board (India), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Universidad de Alicante, Research Foundation - Flanders, Engineering and Physical Sciences Research Council (UK), National Research Foundation of Korea, Indonesia Endowment Fund for Education, National Institute of Standards and Technology (US), Osterrieth, Johannes W. M., Rampersad, James, Madden, David, Rampal, Nakul, Skoric, Luka, Connolly, Bethany, Allendorf, Mark D., Stavila, Vitalie, Snider, Jonathan L., Ameloot, Rob, Marreiros, João, Bara, Dominic, Furukawa, Shuhei, Sánchez, Eli, Gascón, Jorge, Telalović, Selvedin, Ghosh, Sujit K., Mukherjee, Soumya, Hill, Matthew R., Sadiq, Muhammed Munir, Horcajada, Patricia, DeWitt, Stephen J. A., Salcedo Abraira, Pablo, Kaneko, Katsumi, Kukobat, Radovan, Kenvin, Jeff, Keskin, Seda, Kitagawa, Susumu, Otake, Ken-Ichi, Lively, Ryan P., Llewellyn, Phillip, Lotsch, Bettina V., Emmerling, Sebastian T., Pütz, Alexander M., Martí-Gastaldo, Carlos, Padial, Natalia M., García-Martínez, Javier, Linares, Noemí, Maspoch, Daniel, Rosseinsky, Matthew J., Suárez, José Antonio, Moghadam, Peyman, Oktavian, Rama, Morris, Russell E., Wheatley, Paul S., Navarro, Jorge, Petit, Camille, Danaci, David, Katsoulidis, Alexandros P., Schröder, Martin, Han, Xue, Yang, Sihai, Serre, Christian, Mouchaham, Georges, Sholl, David S., Thyagarajan, Raghuram, Siderius, Daniel, Veen, Monique A. van der, Snurr, Randall Q., Goncalves, Rebecca B., Telfer, Shane, Lee, Seok J., Ting, Valeska P., Rowlandson, Jemma L., Uemura, Takashi, Iiyuka, Tomoya, Rega, Davide, Speybroeck, Veronique van, Rogge, Sven M. J., Lamaire, Aran, Walton, Krista S., Bingel, Lukas W., Wuttke, Stefan, Andreo, Jacopo, Yaghi, Omar, Ania, Conchi O., Zhang, Bing, Yavuz, Cafer T., Nguyen, Thien S., Zamora, Félix, Montoro, Carmen, Zhou, Hongcai, Kirchon, Angelo, Fairen-Jiménez, David, Azevedo, Diana, Vilarrasa-García, E., Santos, Bianca S., Bu, Xian-He, Chang, Ze, Bunzen, Hana, Champness, Neil R., Griffin, Sarah L., Chen, Banglin, Lin, Rui-Biao, Coasne, Benoit, Cohen, Seth, Moreton, Jessica C., Colón, Yamil J., Chen, Linjiang, Clowes, Rob, Coudert, François Xavier, Cui, Yong, Hou, Bang, D'Alessandro, Deanna M., Doheny, Patrick W., Dincă, Mircea, Sun, Chenyue, Doonan, Christian J., Huxley, Michael Thomas, Evans, Jack D., Falcaro, Paolo, Ricco, Raffaele, Farha, Omar, Idrees, Karam B., Islamoglu, Timur, Feng, Pingyun, Chang, Huajun, and Forgan, Ross S.

Abstract

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Published
2022

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