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Enhancing Stability and Performance in Perovskite Solar Cells Through Rationally Designed Phenanthro[9,10-D]Imidazole Derivatives for Tailored Interfacial engineering

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SSRN 2024年

作者： Sun, Shih-Sheng Ramanujam, Rajarathinam Shi, Zhong-En Lung, Chien-Yu Li, Sie-Rong Wei, William Wu Wang, Chi-Chun Chen, Chih Ping Institute of Chemistry Academia Sinica Nankang Taipei11529 Taiwan Taiwan International Graduate Program Sustainable Chemical Science and Technology Academia Sinica Nankang Taipei11529 Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University Hsinchu30050 Taiwan Department of Materials Engineering Organic Electronics Research Center Ming Chi University of Technology 84 Gunjuan Road Taishan New Taipei City24301 Taiwan Taipei Fuhsing Private School 262 Section 1 Dun-Hua South Road Taipei Taiwan College of Engineering Center for Sustainability and Energy Technologies Chang Gung University Taoyuan City33302 Taiwan

Interfacial engineering techniques play a significant role in the development of perovskite solar cells (PSCs). In inverted PSCs, nickel oxide (NiOx) is commonly used as a hole transport material (HTM). The poor interactions at the NiOx/CH3NH3PbI3 (MAPbI3) interface contributed to the low stability and power conversion efficiency (PCE) in devices. To address this issue, dopant-free ultrathin interfacial layers (IFLs) have been introduced between the NiOx and perovskite. These IFLs enhance the chemical interaction between the NiOx and perovskite interfaces and result in improved device performance. Herein, T-shape phenanthro[9,10-d]imidazole derivatives, SR-1 and SR-2, were designed and synthesized. The SR-molecules were employed as IFL materials in p-i-n devices with a device configuration of ITO/NiOx/IFL/MAPbI3/PCBM/BCP/Ag. Notably, the IFLs serve multiple functions: modifying the energy levels of NiOx, improving the surface roughness and crystallinity of MAPbI3, passivating defects, enhancing charge extraction, and reducing trap density at the NiOx/MAPbI3 interface. As a result, the PCEs of both devices with SR-1 and SR-2 IFLs outperformed that of the pristine device. The best performance of 20.3% efficiency with nearly negligible hysteresis was achieved from the device with SR-1. The devices with SR-molecules achieved remarkable thermal stability under ambient air conditions and continuous heating at 60 °C with 50-60% relative humidity. © 2024, The Authors. All rights reserved.

关键词： Thermodynamic stability

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Biomass to biofuel precursor: Conversion of glucose and fructose to 5-hydroxymethyfurfural by acid hydrolysis

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AIP Conference Proceedings 2022年第1期2681卷

作者： Nuttida Chanhom Prapaporn Prasertpong Nakorn Tippayawong 1Graduate Program in Energy Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand 2Department of Mechanical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand 3Department of Mechanical Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathum Thani Thailand.

Lignocellulosic biomass contains more than 60% of cellulose consisting of glucose and fructose that can be converted into synthetic fuel, called Dimethylfuran (DMF). DFM contains high energy density and research octane number, and low water solubility that is more appropriate than ethanol in terms of fuel. Production will start with the dehydration process to form 5-Hydroxymethylfural which will be converted to DMF in the following process. The purpose of this study was to evaluate the optimum conditions for the acid hydrolysis or dehydration conversion of glucose and fructose to 5-hydroxymethyfurfural. Response surface methodology and central composite design were used to facilitate the optimization of process variables. The HCI content ranged from 1.65 to 4.95% w/w, and the reaction time ranged from 30 to 40 minutes at a constant temperature of 140 °C. The results showed that the highest conversions for both glucose and fructose to HMF of 67 and 76 % could be achieved from 3.3 % w/w of HCl concentration and the reaction time of 35 min.

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Characterization and performances of hydrophobic polymer membrane modified with dragon’s blood resin

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AIP Conference Proceedings 2023年第1期2613卷

作者： Aulia Chintia Ambarita Sri Mulyati Nasrul Arahman Muhammad Roil Bilad 1Doctoral School of Engineering Science School of Engineering Post Graduate Program Universitas Syiah Kuala Banda Aceh 23111 Indonesia 2Department of Chemical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia 3Department of Chemical and Process Engineering Faculty of Integrated Technologies Universiti Brunei Darussalam Jalan Tungku Link-Gadong BE1401 Brunei

Hydrophobic membranes have limitations, which are the low permeation rate and susceptible to fouling, therefore membrane modifications are generally required. In this paper, hydrophobic polymer membrane modification has been studied by mixing dragon's blood resin (DBR) as bio additive. Two types of polymers were used, they were polyethersulfon (M-3 PES) and polyvinylidene Two types of polymers were used, they were polyethersulfon (M-3 PES) and polyvinylidene fluoride (M-3 PVDF) with a concentration of 14.5% polymer and 3% DBR. The results showed that M-3 PES had greater porosity, water uptake, pore size, and clean water flux than M3-PVDF. However, the antifouling performance of M-3 PVDF membrane tends to be better than M-3 PES, as well as its rejection. Both membranes tend to be stable even after repeated use.

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Evaluation of thermal and spectroscopic properties of hybrid biocomposite OPW/ramie fiber for materials building

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AIP Conference Proceedings 2023年第1期2554卷

作者： Indra Mawardi Samsul Rizal Sri Aprilia Muhammad Faisal 1Doctoral Program School of Engineering Post Graduate Program Universitas Syiah Kuala Banda Aceh 23111 Indonesia 2Department of Mechanical Engineering Politeknik Negeri Lhokseumawe Lhokseumawe 24301 Indonesia 3Department of Mechanical Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia 4Department of Chemical Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia

Environmentally friendly and sustainable buildings encourage researchers to develop natural fiber-based building materials. This investigation was prompted by the abundance of oil palm wood and the fact that it is rarely used as a building material. This study aims to investigate the thermal and spectroscopic properties of a hybrid bio-composite based on oil palm wood as a candidate for green building materials. The hybrid composite was fabricated from oil palm wood and ramie fiber as reinforcement and tapioca starch as a matrix. Oil palm wood particles and ramie fiber were pretreated in 100°C water and NaOH solution, respectively. Hybrid biocomposite was fabricated using hotpress at constant temperature and pressure, with variations of HBC1, HBC2, HBC3 and HBC4. Evaluation of thermal properties in thermogravimetric analysis, differential scanning calorimetry, and spectroscopic was carried out. Thermogravimetric and spectroscopic analysis showed that the HBC3 sample was more stable up to the temperature 358°C and the bigger crystal size is 3.45 nm, compared to other samples. These results showed that oil palm wood-based hybrid composites have the potential to be used as green building materials.

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Applying sustainable city assessment framework for Chiang Mai’s future urban development

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AIP Conference Proceedings 2022年第1期2681卷

作者： Wiwat Pongruengkiat Preda Pichayapan Korrakot Y. Tippayawong Nakorn Tippayawong 1Graduate Program in Energy Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand 2Department of Civil Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand 3Department of Industrial Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand 4Department of Mechanical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

Sustainable city development concerns various dimensions such as citizen well-being, urban infrastructure, environmental friendliness, accessible transportation, and solid economics. Effective utilization of resources and energy is inevitable if a city wishes to transit towards sustainability. A sustainable city assessment framework is a useful tool in measuring and evaluating the management of the city resources without negative impact on the environment, facilitating the city to grant the well-being of the citizen in terms of safety, happiness, and convenience. The management can make use of the framework in planning and executing various policies for robust economic growth. Moving towards a status of a sustainable city is of great interest to an emerging city like Chiang Mai in Thailand. As a case study, Chiang Mai is unique in terms of its medium size, with the potential to be the regional hub. Chiang Mai is the 2nd largest city in Thailand, located in a strategic location and surrounded by diverse and nice natural environments, and is the center of medical and education excellence in northern Thailand. In this works, an overview of sustainable city indicators employed for several cities was conducted. The suitability of key indices was evaluated and discussed against the context of Chiang Mai. The Thai government's bio-circular-green (BCG) economy concept was also considered for economic and social development along with environmental protection to properly realize the potential of the city. From the preliminary findings, potential indicators of the sustainable city assessment may be grouped into three main components: economic, social, and environmental. Useful plans and guidelines from the sustainable city assessment framework were also proposed for the future development and expansion of Chiang Mai.

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Potential of Eggshell Waste Derived Calcium for Sustainable Production of Biogas from Cassava Wastewater

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SSRN 2022年

作者： Cruz, Ianny Andrade Andrade, Larissa Renata Santos de Jesus, Anderson Alles de Vasconcelos, Bruna Rego Bharagava, Ram Naresh Bilal, Muhammad Figueiredo, Renan Tavares de Souza, Ranyere Lucena Romanholo Ferreira, Luiz Fernando Graduate Program in Process Engineering Tiradentes University Av. Murilo Dantas 300 Farolândia SE Aracaju49032-490 Brazil Universidade Federal do Maranhão Campus Balsas MA Balsas65800-000 Brazil Biomass Technology Laboratory Department of Chemical Engineering and Biotechnology Engineering Université de Sherbrooke 2500 Boul. de L’Université SherbrookeQCJ1K 2R1 Canada Vidya Vihar Raebareli Road Uttar Pradesh Lucknow226 025 India School of Life Science and Food Engineering Huaiyin Institute of Technology Huaian223003 China Institute of Technology and Research Av. Murilo Dantas 300 Farolândia SE Aracaju49032-490 Brazil

Cassava is a staple crop that plays a significant role in the food security of many countries. However, its processing produces a liquid by-product known as cassava wastewater (CW), which can have adverse environmental consequences if discarded without treatment. Despite its cyanide content, CW has a high organic content and may be profitable when used to produce biogas. In this study, the influence of calcium particles from eggshell residues was investigated on the anaerobic digestion of CW. Moreover, the performance of the bioreactor was remotely monitored. Calcium particles from milled-calcined chicken eggshells were added to the bioreactor, and biogas production was investigated for 21 days. Adding 1 g/L and 3 g/L of calcium particles increased biogas (Bio H 2 + Bio CH 4 ) production by 195% and 338%, respectively. Finally, the requirement for digestate post-treatment before use in agriculture was observed after assessing its phytotoxicity through the germination and root growth of L. sativa seeds. © 2022, The Authors. All rights reserved.

关键词： Sustainable development

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Sequential Wet Extraction of Phosphorus from Sewage Sludge Using Alum Sludge: Reassessing the Aluminium-Phosphorus Speciation Using Experimental and Simulation Approach

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SSRN 2022年

作者： Tiwari, Satya Brat Hooper, Thomas J.N. Veksha, Andrei Chan, Wei Ping Fei, Xunchang Liu, Wen Lisak, Grzegorz Lim, Teik-Thye School of Civil and Environmental Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Nanyang Environment and Water Research Institute Nanyang Technological University 1 Cleantech Loop CleanTech One 637141 Singapore Interdisciplinary Graduate Program Nanyang Technological University Singapore Centre of High Field NMR Spectroscopy and Imaging Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link 637371 Singapore School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University 62 Nanyang Drive 637459 Singapore

Sewage sludge (SS) is a reclaimable phosphorus (P) source and is a potential alternative to the natural phosphate mineral. This study explored the alkaline leaching of P from alum sludge (AS)-amended dry SS, with or without the acidic pretreatment. The highest orthophosphate (ortho-P) alkaline recovery was 74% for the acid-pretreated SS+AS mix. Amending SS with AS averted the loss of ortho-P during the acidic pretreatment by 59% compared to the reference case (unamended SS). Standards Measurements and Testing (SMT) analysis revealed apatite to non-apatite inorganic phosphorus conversion during the acidic pretreatment, especially in the amended SS. This conversion was due to the dissolution of Ca-P and adsorption of dissolved ortho-P on Al(OH)3 during the acidic pretreatment. Visual MINTEQ modelling, solid-state NMR (31P, 27Al and 31P-1H CP-HETCOR) and Al 2p XPS data indicated the high abundance of Al(OH)3(s), which enhanced the ortho-P adsorption. There was no formation of AlPO4, possibly because the acid-sludge mixture reached the metastable equilibrium and not the true equilibrium during the acidic pretreatment. 31P liquid NMR, SEM, FTIR and XRD provided additional insight into the effects of acidic pretreatment on sludges. Overall, Ca-P to Al-P conversion enhanced the alkaline ortho-P recovery by about 12% compared to the reference case (unamended + non-pretreated). This study demonstrated that P leaching efficiency from SS can be improved (with appropriate process modifications) irrespective of the intrinsic property of SS. © 2022, The Authors. All rights reserved.

关键词： Sewage sludge

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Evaluation of Artificial Neural Network Models for Predictive Monitoring of Biogas Production from Cassava Wastewater: Comparison of Training Algorithms

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SSRN 2022年

作者： Cruz, Ianny Andrade Nascimento, Victor Ruan Silva Felisardo, Raul José Alves dos Santos, Ataíde Mateus Gualberto de Jesus, Anderson Alles de Vasconcelos, Bruna Rego Bilal, Muhammad de Souza, Ranyere Lucena Ferreira, Luiz Fernando Romanholo Graduate Program in Process Engineering Tiradentes University Av. Murilo Dantas 300 Farolândia SE Aracaju49032-490 Brazil Programa de Pós-Graduação em Engenharia Elétrica Universidade Federal de Sergipe Av. Marechal Rondon s/n Jd. Rosa Elze SE São Cristóvão49100-000 Brazil Universidade Federal do Maranhão Campus Balsas MA Balsas65800-000 Brazil Biomass Technology Laboratory Department of Chemical Engineering and Biotechnology Engineering Université de Sherbrooke 2500 Boul. de L’Université SherbrookeQCJ1K 2R1 Canada Institute of Chemical Technology and Engineering Faculty of Chemical Technology Poznan University of Technology Berdychowo 4 PoznanPL-60695 Poland Institute of Technology and Research Av. Murilo Dantas 300 Farolândia SE Aracaju49032-490 Brazil

In this study, machine learning integrated based models for predicting cumulative biogas from anaerobic digestion (AD) of cassava wastewater were developed using artificial neural networks (ANNs). Biogas generation was investigated for 21 days with and without the inclusion of calcium particles from milled calcined chicken waste as a low-cost substitute for buffering. Digestion time, pH, and calcium concentration were selected as input features for biogas prediction through the implementation of the ANN approach. Moreover, seven different training algorithms were used to train the model, and a genetic algorithm (GA) was also implemented to optimize the ANN architecture, resulting in faster learning and higher prediction performance. Given the data set, the Levenberg-Marquardt algorithm with a hyperbolic tangent as a transfer function to the hidden and output layers was the most efficient model in predicting the biogas produced with an R-value of 0.9999. © 2022, The Authors. All rights reserved.

关键词： Genetic algorithms

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Structural basis for a conserved neutralization epitope on the receptor-binding domain of SARS-CoV-2

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Nature Communications 2023年第1期14卷 311-311页

作者： Huang, Kuan-Ying A. Chen, Xiaorui Mohapatra, Arpita Nguyen, Hong Thuy Vy Schimanski, Lisa Tan, Tiong Kit Rijal, Pramila Vester, Susan K. Hills, Rory A. Howarth, Mark Keeffe, Jennifer R. Cohen, Alexander A. Kakutani, Leesa M. Wu, Yi-Min Shahed-Al-Mahmud, Md Chou, Yu-Chi Bjorkman, Pamela J. Townsend, Alain R. Ma, Che Graduate Institute of Immunology and Department of Pediatrics National Taiwan University Hospital College of Medicine National Taiwan University Taipei Taiwan Genomics Research Center Academia Sinica Taipei Taiwan College of Medicine Chang Gung University Taoyuan Taiwan Chemical Biology and Molecular Biophysics program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Institute of Biochemical Sciences National Taiwan University Taipei Taiwan MRC Human Immunology Unit Weatherall Institute of Molecular Medicine University of Oxford John Radcliffe Hospital Oxford United Kingdom Department of Biochemistry University of Oxford Oxford OX1 3QU United Kingdom Division of Biology and Biological Engineering California Institute of Technology Pasadena United States Institute of Biological Chemistry Academia Sinica Taipei 11529 Taiwan Biomedical Translation Research Center Academia Sinica Taipei 11529 Taiwan Department of Pharmacology University of Cambridge Tennis Court Road Cambridge CB2 1PD United Kingdom

Antibody-mediated immunity plays a crucial role in protection against SARS-CoV-2 infection. We isolated a panel of neutralizing anti-receptor-binding domain (RBD) antibodies elicited upon natural infection and vaccination and showed that they recognize an immunogenic patch on the internal surface of the core RBD, which faces inwards and is hidden in the “down” state. These antibodies broadly neutralize wild type (Wuhan-Hu-1) SARS-CoV-2, Beta and Delta variants and some are effective against other sarbecoviruses. We observed a continuum of partially overlapping antibody epitopes from lower to upper part of the inner face of the RBD and some antibodies extend towards the receptor-binding motif. The majority of antibodies are substantially compromised by three mutational hotspots (S371L/F, S373P and S375F) in the lower part of the Omicron BA.1, BA.2 and BA.4/5 RBD. By contrast, antibody IY-2A induces a partial unfolding of this variable region and interacts with a conserved conformational epitope to tolerate all antigenic variations and neutralize diverse sarbecoviruses as well. This finding establishes that antibody recognition is not limited to the normal surface structures on the RBD. In conclusion, the delineation of functionally and structurally conserved RBD epitopes highlights potential vaccine and therapeutic candidates for COVID-19. © 2023, The Author(s).

关键词： Antibodies SARS-CoV-2

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Explainable uncertainty quantifications for deep learning-based molecular property prediction

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Journal of cheminformatics 2023年第1期15卷 13页

作者： Chu-I Yang Yi-Pei Li Department of Chemical Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Department of Chemical Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yipeili@ntu.edu.tw. Taiwan International Graduate Program (TIGP) Academia Sinica No. 128 Sec. 2 Academia Road Taipei 11529 Taiwan. yipeili@ntu.edu.tw.

Quantifying uncertainty in machine learning is important in new research areas with scarce high-quality data. In this work, we develop an explainable uncertainty quantification method for deep learning-based molecular property prediction. This method can capture aleatoric and epistemic uncertainties separately and attribute the uncertainties to atoms present in the molecule. The atom-based uncertainty method provides an extra layer of chemical insight to the estimated uncertainties, i.e., one can analyze individual atomic uncertainty values to diagnose the chemical component that introduces uncertainty to the prediction. Our experiments suggest that atomic uncertainty can detect unseen chemical structures and identify chemical species whose data are potentially associated with significant noise. Furthermore, we propose a post-hoc calibration method to refine the uncertainty quantified by ensemble models for better confidence interval estimates. This work improves uncertainty calibration and provides a framework for assessing whether and why a prediction should be considered unreliable.

关键词： Deep learning Explainable AI Molecular property prediction Uncertainty quantifications

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