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5. Exopolysaccharides for bioremediation

Author

Sharma, Ramesh, primary, Nath, Pinku Chandra, additional, Debnath, Shubhankar, additional, Ojha, Amiya, additional, Sarkar, Biswajit, additional, Bandyopadhyay, Tarun Kanti, additional, and Bhunia, Biswanath, additional

Published
2024
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20. High-throughput screening of the thermoelastic properties of ultra-high temperature ceramics

Author

Nath, Pinku, Plata, Jose J., Santana, Julia, Blancas, Ernesto J., Márquez, Antonio M., and Sanz, Javier Fdez.

Subjects
Condensed Matter - Materials Science
Abstract

Ultra-high temperature ceramics, UHTCs, are a group of materials with high technological interest because their use in extreme environments. However, their characterization at high temperatures represents the main obstacle for their fast development. Obstacles are found from a experimental point of view, where only few laboratories around the world have the resources to test these materials under extreme conditions, and also from a theoretical point of view, where actual methods are extremely expensive. Here, a new theoretical high-throughput framework for the prediction of the thermoelastic properties of materials is introduced. This approach can be systematically applied to any kind of crystalline material, drastically reducing the computational cost of previous methodologies. Elastic constants for UHTCs have been calculated at a wide range of temperatures with excellent agreement with experimentally reported values. Moreover, other mechanical properties such a bulk modulus, shear modulus or Poisson ration have been also explored. Other frameworks with similar computational cost have been used only for predicting isotropic or averaged properties, however this new approach opens the door to the calculation of anisotropic properties at a very low computational cost.

Published
2020

22. Contributors

Author

Adei, Evans, primary, Adsul, Tushar, additional, Afugu, Amos, additional, Afzal, Muhammad, additional, Ahamed, Mohd Imran, additional, Akpasi, Stephen, additional, Akram, Sumia, additional, Akter, Beauty, additional, Anekwe, Ifeanyi Michael Smarte, additional, Anwar, Naushad, additional, Armah, Edward Kwaku, additional, Asif, Muhammad, additional, Aslan, S., additional, Athar, Hafiz Muhammad, additional, Atuman, Samaila Joel, additional, Bandyopadhyay, Tarun Kanti, additional, Barbosa, Jhonatas Rodrigues, additional, Basumallick, Srijita, additional, Bera, Achinta, additional, Bhunia, Biswanath, additional, Butt, Faizan Waseem, additional, Danquah, Michael K., additional, Dey, Pritam, additional, Fadeyibi, Adeshina, additional, Faisal, Muhammad, additional, Ferreira, Clara Prestes, additional, Ghosh, Santanu, additional, Gopalram, Keerthiga, additional, Hayat, Sumreen, additional, Hasan, Nazmul, additional, Hira, Uzma, additional, Isa, Yusuf Makarfi, additional, Islam, Md. Mahbubul, additional, Islam, Md Abu Shahyn, additional, Işık, C., additional, Jeyaseelan, Christine, additional, Junior, Raul Nunes de Carvalho, additional, Jutur, Pannaga Pavan, additional, Kamal, Ahmed, additional, Kapoor, Ashish, additional, Kareya, Mukul Suresh, additional, Kataria, Bharti, additional, Khan, Mohd Arham, additional, Kumar, Ashish, additional, Kumar, Mukesh, additional, Kwawu, Caroline R., additional, Liaqat, Zainab, additional, Lima, Jeieli Wendel Gaspar, additional, Makaranga, Abdalah, additional, Malhotra, Milan, additional, Mamuk, A.E., additional, Maqbool, Fareeha, additional, Menkah, Elliot, additional, Mushtaq, Muhammad, additional, Muzammil, Saima, additional, Nadeem, Habibullah, additional, Nag, Bijaya, additional, Nath, Pinku Chandra, additional, Nesamma, Asha Arumugam, additional, Osei, Dacosta, additional, Ponnuchamy, Muthamilselvi, additional, Rasul, Ijaz, additional, Saha, Mitali, additional, Saleem, Tuba, additional, Saraf, Shubham, additional, Sathyanadh, Anusha, additional, Shakeel, Nimra, additional, Shammi, Mashura, additional, Shahzad, Tanvir, additional, Siddique, Muhammad Hussnain, additional, Singh, Pritam, additional, Stalinraja, Abinaya, additional, Tahir, Javeria, additional, Tetteh, Emmanuel Kweinor, additional, Thakur, Abhinay, additional, Tian, Guocai, additional, Tran, Khanh-Quang, additional, Twi-Yeboah, Nigel, additional, Vaishampayan, Vijay, additional, Varma, Atul Kumar, additional, Waseem, Muhammad, additional, and Winter, Julien, additional

Published
2023
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27. Contributors

Author

Adhikari, Arpita, primary, Alanalp, Mine Begum, additional, Aydın, Elif Burcu, additional, Aydın, Muhammet, additional, Azad, Abul Kalam, additional, Baig, Mirza Shahed, additional, Balaji, D., additional, Bavage, Shyamlila B., additional, Benjamin, Stephen Rathinaraj, additional, Berrada, Mohammed, additional, Bhattacharya, Tanima, additional, Bhuvaneswari, V., additional, Camlibel, Nurhan Onar, additional, Chakraborty, Sarit, additional, Chalivendra, Vijaya, additional, Chattopadhyay, Dipankar, additional, Chaus, Wajid N., additional, Chopra, Hitesh, additional, Cochrane, Cedric, additional, Damiri, Fouad, additional, Das, Madhurima, additional, Das, Narayan Chandra, additional, Das, Poushali, additional, Das, Tushar Kanti, additional, De, Sriparna, additional, Dogu, Merve, additional, Durmus, Ali, additional, Dutra, Rosa Fireman, additional, Gaiji, Houda, additional, Ganguly, Sayan, additional, Gebretsadik, Abbay, additional, Gedanken, Aharon, additional, Ghatak, Avishek, additional, Ghosh, Prosenjit, additional, Ghosh, Suman Kumar, additional, Gupta, Akanksha, additional, Haftu, Mamu, additional, Jadhav, Prerana Badrinath, additional, Kaur, Damandeep, additional, Kaur, Manpreet, additional, Kaur, Navneet, additional, Khan, Shamim Ahmed, additional, Khan, Sharuk L., additional, Koncar, Vladan, additional, Kottiyatil, Abhilash J., additional, Lazim, Nurul Asmak Md, additional, Madhavan, K., additional, Majhi, Abhisek, additional, Majid, A.M.S. Abdul, additional, Maruthapandi, Moorthy, additional, Mozafari, M.R., additional, Muhamad, Ida Idayu, additional, Murthy, H.C. Ananda, additional, Nath, Jyotishka, additional, Nath, Pinku Chandra, additional, Naveen, V., additional, Nemera, Tesfaye, additional, Orasugh, Jonathan Tersur, additional, Parameswaranpillai, Jyotishkumar, additional, Paul, Pijush, additional, Porkodi, P., additional, Pramanik, Amit, additional, Rajabzadeh, Amin Reza, additional, Rajeshkumar, L., additional, Ramesh, M., additional, Ravikumar, C.R., additional, Roy, Biplab, additional, Saravanan, Arumugam, additional, Sengupta, Bratin, additional, Sezgintürk, Mustafa Kemal, additional, Siddiqui, Falak A., additional, Singh, Narinder, additional, Srinivasan, Seshasai, additional, Sultana, Rokeya, additional, Sunil, Sheeja, additional, and Vikhe, Sunayana Rahul, additional

Published
2023
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30. AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids

Author

Nath, Pinku, Usanmaz, Demet, Hicks, David, Oses, Corey, Fornari, Marco, Nardelli, Marco Buongiorno, Toher, Cormac, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

Accelerating the calculations of finite-temperature thermodynamic properties is a major challenge for rational materials design. Reliable methods can be quite expensive, limiting their effective applicability in autonomous high-throughput workflows. Here, the 3-phonons quasi-harmonic approximation (QHA) method is introduced, requiring only three phonon calculations to obtain a thorough characterization of the material. Leveraging a Taylor expansion of the phonon frequencies around the equilibrium volume, the method efficiently resolves the volumetric thermal expansion coefficient, specific heat at constant pressure, the enthalpy, and bulk modulus. Results from the standard QHA and experiments corroborate the procedure, and additional comparisons are made with the recently developed self-consistent QHA. The three approaches - 3-phonons, standard, and self- consistent QHAs - are all included within the automated, open-source framework AFLOW, allowing automated determination of properties with various implementations within the same framework., Comment: 18 pages, 7 figures

Published
2018
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31. Spinodal superlattices of topological insulators

Author

Usanmaz, Demet, Nath, Pinku, Toher, Cormac, Plata, Jose Javier, Friedrich, Rico, Fornari, Marco, Nardelli, Marco Buongiorno, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science
Abstract

Spinodal decomposition is proposed for stabilizing self-assembled interfaces between topological insulators (TIs) by combining layers of iso-structural and iso-valent TlBi$X_2$ ($X$=S, Se, Te) materials. The composition range for gapless states is addressed concurrently to the study of thermodynamically driven boundaries. By tailoring composition, the TlBiS$_2$-TlBiTe$_2$ system might produce both spinodal superlattices and two dimensional eutectic microstructures, either concurrently or separately. The dimensions and topological nature of the metallic channels are determined by following the spatial distribution of the charge density and the spin-texture. The results validate the proof of concept for obtaining spontaneously forming two-dimensional TI-conducting channels embedded into three-dimensional insulating environments without any vacuum interfaces. Since spinodal decomposition is a controllable kinetic phenomenon, its leverage could become the long-sought enabler for effective TI technological deployment., Comment: 11 pages, 4 figures

Published
2018

33. The AFLOW Fleet for Materials Discovery

Author

Toher, Cormac, Oses, Corey, Hicks, David, Gossett, Eric, Rose, Frisco, Nath, Pinku, Usanmaz, Demet, Ford, Denise C., Perim, Eric, Calderon, Camilo E., Plata, Jose J., Lederer, Yoav, Jahnátek, Michal, Setyawan, Wahyu, Wang, Shidong, Xue, Junkai, Rasch, Kevin, Chepulskii, Roman V., Taylor, Richard H., Gomez, Geena, Shi, Harvey, Supka, Andrew R., Orabi, Rabih Al Rahal Al, Gopal, Priya, Cerasoli, Frank T., Liyanage, Laalitha, Wang, Haihang, Siloi, Ilaria, Agapito, Luis A., Nyshadham, Chandramouli, Hart, Gus L. W, Carrete, Jesús, Legrain, Fleur, Mingo, Natalio, Zurek, Eva, Isayev, Olexandr, Tropsha, Alexander, Sanvito, Stefano, Hanson, Robert M., Takeuchi, Ichiro, Mehl, Michael J., Kolmogorov, Aleksey N., Yang, Kesong, D'Amico, Pino, Calzolari, Arrigo, Costa, Marcio, De Gennaro, Riccardo, Nardelli, Marco Buongiorno, Fornari, Marco, Levy, Ohad, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science
Abstract

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available., Comment: 14 pages, 8 figures

Published
2017

34. A visual search engine for Bangladeshi laws

Author

Mandal, Manash Kumar, Nath, Pinku Deb, Mizan, Arpeeta Shams, and Saquib, Nazmus

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computers and Society, Statistics - Machine Learning
Abstract

Browsing and finding relevant information for Bangladeshi laws is a challenge faced by all law students and researchers in Bangladesh, and by citizens who want to learn about any legal procedure. Some law archives in Bangladesh are digitized, but lack proper tools to organize the data meaningfully. We present a text visualization tool that utilizes machine learning techniques to make the searching of laws quicker and easier. Using Doc2Vec to layout law article nodes, link mining techniques to visualize relevant citation networks, and named entity recognition to quickly find relevant sections in long law articles, our tool provides a faster and better search experience to the users. Qualitative feedback from law researchers, students, and government officials show promise for visually intuitive search tools in the context of governmental, legal, and constitutional data in developing countries, where digitized data does not necessarily pave the way towards an easy access to information., Comment: Presented at NIPS 2017 Workshop on Machine Learning for the Developing World. Corresponding author: Nazmus Saquib

Published
2017

36. The AFLOW Fleet for Materials Discovery

Author

Toher, Cormac, Oses, Corey, Hicks, David, Gossett, Eric, Rose, Frisco, Nath, Pinku, Usanmaz, Demet, Ford, Denise C., Perim, Eric, Calderon, Camilo E., Plata, Jose J., Lederer, Yoav, Jahnátek, Michal, Setyawan, Wahyu, Wang, Shidong, Xue, Junkai, Rasch, Kevin, Chepulskii, Roman V., Taylor, Richard H., Gomez, Geena, Shi, Harvey, Supka, Andrew R., Al Rahal Al Orabi, Rabih, Gopal, Priya, Cerasoli, Frank T., Liyanage, Laalitha, Wang, Haihang, Siloi, Ilaria, Agapito, Luis A., Nyshadham, Chandramouli, Hart, Gus L. W., Carrete, Jesús, Legrain, Fleur, Mingo, Natalio, Zurek, Eva, Isayev, Olexandr, Tropsha, Alexander, Sanvito, Stefano, Hanson, Robert M., Takeuchi, Ichiro, Mehl, Michael J., Kolmogorov, Aleksey N., Yang, Kesong, D’Amico, Pino, Calzolari, Arrigo, Costa, Marcio, De Gennaro, Riccardo, Buongiorno Nardelli, Marco, Fornari, Marco, Levy, Ohad, Curtarolo, Stefano, Andreoni, Wanda, editor, and Yip, Sidney, editor

Published
2020
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39. Predicting the lattice thermal conductivity of solids by solving the Boltzmann transport equation: AFLOW - AAPL an automated, accurate and effcient framework

Author

Plata, Jose J., Usanmaz, Demet, Nath, Pinku, Toher, Cormac, Carrete, Jesus, Asta, Mark, de Jong, Maarten, Nardelli, Marco Buongiorno, Fornari, Marco, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science
Abstract

One of the most accurate approaches for calculating lattice thermal conductivity, $\kappa_l$, is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path. High computational costs and lack of automation in the frameworks using this methodology affect the discovery rate of novel materials with ad-hoc properties. Here, we present the Automatic-Anharmonic-Phonon-Library, AAPL. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain $\kappa_l$, and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. We show an "experiment versus theory" study of the approach, we compare accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation, we demonstrate that it is possible to improve accuracy without increasing computational requirements by combining AAPL with the pseudo-hybrid functional ACBN0., Comment: 11 pages, 3 figures

Published
2016

40. High-Throughput Prediction of Finite-Temperature Properties using the Quasi-Harmonic Approximation

Author

Nath, Pinku, Plata, Jose J., Usunmaz, Demet, Orabi, Rabih Al Rahal Al, Fornari, Marco, Nardelli, Marco Buongiorno, Toher, Cormac, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science
Abstract

In order to calculate thermal properties in automatic fashion, the Quasi-Harmonic Approximation (QHA) has been combined with the Automatic Phonon Library (APL) and implemented within the AFLOW framework for high-throughput computational materials science. As a benchmark test to address the accuracy of the method and implementation, the specific heats, thermal expansion coefficients, Gr\"uneisen parameters and bulk moduli have been calculated for 130 compounds. It is found that QHA-APL can reliably predict such values for several different classes of solids with root mean square relative deviation smaller than 28% with respect to experimental values. The automation, robustness, accuracy and precision of QHA-APL enable the computation of large material data sets, the implementation of repositories containing thermal properties, and finally can serve the community for data mining and machine learning studies., Comment: 18 pages, 7 figures

Published
2016

43. High-Throughput Prediction of the Thermal and Electronic Transport Properties of Large Physical and Chemical Spaces Accelerated by Machine Learning: Charting the ZT of Binary Skutterudites

Author

Universidad de Sevilla. Departamento de Química Física, Ministerio de Ciencia e Innovación (MICIN). España, Red Española de Supercomputación (RES), Santana Andreo, Julia, Márquez Cruz, Antonio Marcial, Plata Ramos, José Javier, Blancas, Ernesto J., González Sánchez, José Luis, Fernández Sanz, Javier, Nath, Pinku, Universidad de Sevilla. Departamento de Química Física, Ministerio de Ciencia e Innovación (MICIN). España, Red Española de Supercomputación (RES), Santana Andreo, Julia, Márquez Cruz, Antonio Marcial, Plata Ramos, José Javier, Blancas, Ernesto J., González Sánchez, José Luis, Fernández Sanz, Javier, and Nath, Pinku

Abstract

Thermal and electronic transport properties are the keys to many technological applications of materials. Thermoelectric, TE, materials can be considered a singular case in which not only one but three different transport properties are combined to describe their performance through their TE figure of merit, ZT. Despite the availability of high-throughput experimental techniques, synthesizing, characterizing, and measuring the properties of samples with numerous variables affecting ZT are not a cost- or time-efficient approach to lead this strategy. The significance of computational materials science in discovering new TE materials has been running in parallel to the development of new frameworks and methodologies to compute the electron and thermal transport properties linked to ZT. Nevertheless, the trade-off between computational cost and accuracy has hindered the reliable prediction of TE performance for large chemical spaces. In this work, we present for the first time the combination of new ab initio methodologies to predict transport properties with machine learning and a high-throughput framework to establish a solid foundation for the accurate prediction of thermal and electron transport properties. This strategy is applied to a whole family of materials, binary skutterudites, which are well-known as good TE candidates. Following this methodology, it is possible not only to connect ZT with the experimental synthetic (carrier concentration and grain size) and operando (temperature) variables but also to understand the physical and chemical phenomena that act as driving forces in the maximization of ZT for p-type and n-type binary skutterudites.

Published
2024

44. First principles thermodynamical modeling of the binodal and spinodal curves in lead chalcogenides

Author

Usanmaz, Demet, Nath, Pinku, Plata, Jose J., Hart, Gus L. W., Takeuchi, Ichiro, Nardelli, Marco Buongiorno, Fornari, Marco, and Curtarolo, Stefano

Subjects
Condensed Matter - Materials Science
Abstract

High-throughput ab-initio calculations, cluster expansion techniques and thermodynamic modeling have been synergistically combined to characterize the binodal and the spinodal decompositions features in the pseudo-binary lead chalcogenides PbSe-PbTe, PbS-PbTe, and PbS-PbSe. While our results agree with the available experimental data, our consolute temperatures substantially improve with respect to previous computational modeling. The computed phase diagrams corroborate that the formation of spinodal nanostructures causes low thermal conductivities in these alloys. The presented approach, making a rational use of online quantum repositories, can be extended to study thermodynamical and kinetic properties of materials of technological interest., Comment: 8 pages, 4 figures, submitted

Published
2015
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46. C-phycoerythrin production from Anabaenasp. BTA 903: Optimization, production kinetics, thermodynamic, and stability analysis

Author

Nath, Pinku Chandra, Bandyopadhyay, Tarun Kanti, Mahata, Nibedita, Tiwari, Onkar Nath, Bobby, Md. Nazneen, Indira, Mikkili, and Bhunia, Biswanath

Abstract

The cyanobacterium BTA 903 isolated from Manipur state of India was identified as Anabaenasp. after phylogenetic analysis. BTA 903 contained ash (5.84% w/w), carbohydrate (42.36% w/w), protein (33.46% w/w), lipid (16.46% w/w), and moisture (1.88% w/w), respectively. BTA 903 required 0.3 M glycine and 5 mM sodium glutamate as supplements in BG 11 media in order to achieve the highest amount of cell growth along with C-phycoerythrin (PE) production. The light intensity of 6 k Lux, along with a photoperiod of 14:10 (L:D) was revealed to be optimal for increased productivity. The yields of C-phycoerythrin, C-phycocyanin, allophycocyanin, chlorophyll-a, and ammonia excretion after 30 days of incubation of Anabaena sp. were 49.96, 27.53, and 30.39, 6.9, and 31.2 mg per gram of biomass, respectively. The biomass productivity of Anabaenasp. BTA 903 was found to be 39 mgL−1day−1after 30 days of incubation. PE from Anabaenasp. was extracted using 0.05 M phosphate buffer (pH-7). The deactivation process of PE was investigated using a first-order kinetic model. The rate constant (kd) was found to be in the range of 0–0.01 h−1when the deactivation study was carried out at pH 7 and temperatures ranging from 10 to 30 °C. The highest level of PE deactivation was found at 80 °C and pH 12 due to a higher kdvalue (0.671 h−1). At pH 7, the highest Gibb’s free energy for PE was found to be 103.70–115.69 kJ/mol. PE’s pH and thermal tolerances suggested that it could be used for industrial applications.

Published
2024
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49. List of Contributors

Author

Abdullah, Bawadi, primary, Abdulrahman, Abdulrasheed, additional, Abidin, Sumaiya Zainal, additional, Abudula, Abuliti, additional, Alhraki, Nour, additional, An, Ping, additional, Arun, Naveenji, additional, Assabumrungrat, Suttichai, additional, Atsunori, Matsuda, additional, Bahari, Mahadi B., additional, Castro, Jonathan D., additional, Chimpae, Supanida, additional, Dalai, Ajay K., additional, Gao, Kang, additional, Guan, Guoqing, additional, Ha, Hoang Thu, additional, Huang, Chao-Wei, additional, Idris, Nurul Hayati, additional, Iliuta, Maria Cornelia, additional, Ismail, Mohammad, additional, Jacobs, Gary, additional, Jalil, Aishah Abdul, additional, Kendall, Kevin, additional, Khan, Maksudur Rahman, additional, Kim-Lohsoontorn, Pattaraporn, additional, Maan, Karan Singh, additional, Martinelli, Michela, additional, Matamoros, Maria E., additional, Meshkani, Fereshteh, additional, Minh, Tran Dinh, additional, Mohamed, Abdul Rahman, additional, Mohammadi, Maedeh, additional, Mustafa, Nurul Shafikah Mohd, additional, Nanda, Sonil, additional, Nath, Pinku, additional, Nguyen, Ba-Son, additional, Nguyen, Trinh Duy, additional, Nguyen, Van-Huy, additional, Nguyen-Tri, Phuong, additional, Nimmas, Talita, additional, Noppakun, Nichamon, additional, Phuc, Nguyen H.H., additional, Powell, Jon, additional, Reddy, Sivamohan N., additional, Sahraei, Ommolbanin Ali Zadeh, additional, Saravanan, Prabhu, additional, Setiabudi, Herma Dina, additional, Shafiqah, Mohd-Nasir Nor, additional, Shang, Nathan Jinlei, additional, Sharma, Ajit, additional, Shirazi, Mohammad Mahdi A., additional, Siang, Tan Ji, additional, Van Le, Quyet, additional, Vo, Dai-Viet N., additional, Wang, Jiajia, additional, Wongsakulphasatch, Suwimol, additional, Xian, Ooi Yve, additional, Yahya, Muhammad Syarifuddin, additional, Yang, Yanyan, additional, Yap, Muhammad Firdaus Asyraf Abd. Halim, additional, Yee, Chin Sim, additional, Yu, Zhongliang, additional, Yue, Xiyan, additional, and Zhao, Zhongkai, additional

Published
2020
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