Article
Energy & Fuels
Zain ul Abdin, Irfan Qasim, Owais Ahmad, Muhammad Rashid
Summary: Perovskite solar cells are cost-effective and stable in the global photovoltaic industry, with unique electronic and optical properties. Numerical investigations in this study designed novel solar cell configurations and optimized performance, exploring the impact of various electron transport materials on efficiency.
Article
Engineering, Environmental
Jing Zhou, Xueying Tian, Rui Chen, Weitao Chen, Xin Meng, Xinyu Guan, Jianan Wang, Sanwan Liu, Fumeng Ren, Shasha Zhang, Yiqiang Zhang, Zonghao Liu, Wei Chen
Summary: This study utilized an ultra-thin functional hydrophobic polymer, Parylene C, to enhance the operational lifetime of perovskite solar cells (PSCs). The Parylene C film, which was applied as a surface finish using chemical vapor deposition, provided tunnel contact and protected the perovskite layer. The Parylene C film reduced surface defects and hindered hole migration, resulting in improved efficiency and long-term stability of PSCs.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Chemistry, Physical
Weihuang Wang, Zixiu Cao, Li Wu, Fangfang Liu, Jianping Ao, Yi Zhang
Summary: The study focuses on the growth of Sb2Se3 thin films and the formation mechanism of Sb2Se3 nanorods, demonstrating that controlling the orientation of nanorods can improve the quality of the Sb2Se3 thin film. The research also achieved record efficiency for a VTD-processed Sb2Se3 solar cell with a carbon electrode.
ACS APPLIED ENERGY MATERIALS
(2021)
Review
Chemistry, Physical
Mingyue Wang, Claire J. Carmalt
Summary: This review discusses perovskite films for photovoltaic applications deposited by various chemical vapor deposition (CVD) methods and provides a summary of the development and investigation of CVD processes.
ACS APPLIED ENERGY MATERIALS
(2022)
Article
Chemistry, Physical
Florent Sahli, Nathanael Miaz, Niccolo Salsi, Cedric Bucher, Aymeric Schafflutzel, Quentin Guesnay, Leo Duchene, Bjorn Niesen, Christophe Ballif, Quentin Jeangros
Summary: Vapor-based processes show promise for depositing metal halide perovskite solar cells in industrial settings, allowing for uniform layer deposition over large areas and conformal layers on rough substrates. The development of a vapor transport deposition chamber helps control the complex sublimation of organic precursors, ensuring high-quality perovskite layers are produced. Small-scale methylammonium lead iodide solar cells are processed to validate the absorber quality produced by this method.
ACS APPLIED ENERGY MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Rong Deng, Pablo Ribeiro Dias, Marina Monteiro Lunardi, Jingjia Ji
Summary: Proper disposal of photovoltaic modules has become an emerging environmental and social issue, with the decommissioning volume set to increase significantly by 2030. Recycling high-purity silicon and silver from end-of-life solar cells can greatly improve recycling revenue. The development of an environmentally sustainable chemical process can efficiently recover these valuable materials in an environmentally friendly manner.
Article
Computer Science, Interdisciplinary Applications
Athmane Bakhta, Julien Vidal
Summary: This paper proposes a mathematical model describing the thin film formation during the co-evaporation PVD process for the production of CIGS type thin film photovoltaic cells. The model is calibrated on true experimental measurements and an optimization problem is considered to achieve certain targeted final concentration profiles. Despite its simplicity, the proposed model shows promising results towards a quantitatively predictive model.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Chemistry, Multidisciplinary
Abd El-Hady B. Kashyout, Said El-Hashash, Jehan El Nady, Marwa Fathy, Kamel Shoueir, Arwa Wageh, Ali El-Dissouky, Roshdy Abdel Rassoul
Summary: This study investigates the application of polythiophene (PT), polythiophene with embedded gold nanoparticles (PT-Au), and polythiophene with embedded palladium nanoparticles (PT-Pd) on the rear contact of single-crystalline silicon solar cells using the spin coating technique. The optical characteristics of the polymers and embedded nanoparticles show high absorption in the near-UV region. The coating reduces series resistance and increases cell efficiency, with up to a 7.25% improvement observed for PT-Au5% layers.
Article
Thermodynamics
Mounir Abraim, Massaab El Ydrissi, Hicham Ghennioui, Abdellatif Ghennioui, Natalie Hanrieder, Stefan Wilbert, Omaima El Alani, Mohamed Boujoudar, Alae Azouzoute
Summary: Soiling is a limiting factor for the efficiency of PV installations. By implementing a reliable monitoring system, it is possible to reduce energy losses, improve profitability, optimize cleaning strategies, and estimate related costs.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Chemistry, Multidisciplinary
Dongxu Lin, Yujia Gao, Tiankai Zhang, Zhenye Zhan, Nana Pang, Zongwang Wu, Ke Chen, Tingting Shi, Zhenqiang Pan, Pengyi Liu, Weiguang Xie
Summary: In this study, a vapor deposited pure alpha-FAPbI(3) thin film solar cell with a record-breaking power conversion efficiency (PCE) over 20% is achieved by regulating the phase transition process. It is found that a fast phase transition between high-purity alpha- and delta-phase FAPbI(3) can be realized under high humidity conditions. The abnormal volume contraction induced by the formation of double hydrogen bonds is an interesting shortcut for the phase transition. This study redefines the effect of water molecules on FAPbI(3) solar cells.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Chemistry, Physical
Pierre Tomasini
Summary: The silicon chemical vapor deposition process via silane is determined using classical thermodynamics, showing that a linear function of temperature controls silicon growth rates and neatly maps the response of growth rate activation energy, providing clarity to the parameter space. The study demonstrates the portability of the linear function of temperature across reactors and extracts reactor scaling factors, reducing the complex silicon deposition process to its essentials through thermodynamics.
CHEMISTRY OF MATERIALS
(2021)
Article
Engineering, Chemical
Wei Liu, Daoyin Liu, Yingjuan Zhang, Bo Li
Summary: In this study, the Eulerian-Eulerian model with Population Balance Model (PBM) is used to predict the particle size distribution (PSD) of SiO2 particles in the MCVD process, and the Discrete Particle Model (DPM) is used to investigate the trajectories and deposition locations of the particles. The results show that the deposition distance and flight time of the particles increase with the increase of particle size and wall temperature.
Article
Chemistry, Physical
Guoqing Tong, Jiahao Zhang, Tongle Bu, Luis K. Ono, Congyang Zhang, Yuqiang Liu, Chenfeng Ding, Tianhao Wu, Silvia Mariotti, Said Kazaoui, Yabing Qi
Summary: Hybrid chemical vapor deposition (HCVD) is used to fabricate perovskite solar cells/modules (PSCs/PSMs) with the introduction of a passivation layer and a solvent, resulting in improved efficiency and stability. The oxygen loss of SnO2 in the HCVD process is mitigated by potassium sulfamate (H2KNO3S) while the uncoordinated Pb2+ in the perovskite film is passivated. N-methylpyrrolidone (NMP) is used as a solvent to dissolve PbI2 and lower the energy barrier for perovskite nucleation. The use of perovskite seeds further enhances crystal growth and grain size. The resulting solar cells and mini-modules exhibit high power conversion efficiency (PCE) and stable output performance, with excellent operational stability.
ADVANCED ENERGY MATERIALS
(2023)
Article
Green & Sustainable Science & Technology
Xudong Zha, Mengxuan Qiu, Hengwu Hu, Jinxiang Hu, Ruidong Lv, Qinxue Pan
Summary: A self-compacting concrete hollow slab solar pavement based on a micro photovoltaic array was proposed and optimized in this study. The results showed that the pavement has good power generation capacity and environmental benefits. The increased cost can be recovered after a certain period.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Chemistry, Physical
Jun Zhao, Xuerui Li, Junhui Lin, Xiaofang Zhao, Muhammad Ishaq, Shuo Chen, Zhuanghao Zheng, Zhenghua Su, Xianghua Zhang, Guang-Xing Liang
Summary: This study focuses on the preparation and performance optimization of Sb2(S, Se)3. By optimizing the thickness of the absorber layer, the carrier transport mechanism of the Sb2(S, Se)3 device can be improved and the number of defect states can be reduced, resulting in higher efficiency for the solar cell.
SURFACES AND INTERFACES
(2023)
Article
Computer Science, Interdisciplinary Applications
Nohan Joemon, Melpakkam Pradeep, Lokesh K. Rajulapati, Raghunathan Rengaswamy
Summary: This paper introduces a smoothing-based approach for discovering partial differential equations from noisy measurements. The method is data-driven and improves performance by incorporating first principles knowledge. The effectiveness of the algorithm is demonstrated in a real system using a new benchmark metric.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhibin Lu, Yimeng Li, Chang He, Jingzheng Ren, Haoshui Yu, Bingjian Zhang, Qinglin Chen
Summary: This study proposes a new inverse design method using a physics-informed neural network to identify optimal heat sink designs. A hybrid PINN accurately approximates the governing equations of heat transfer processes, and a surrogate model is constructed for integration with optimization algorithms. The proposed method accelerates the search for Pareto-optimal designs and reduces search time. Comparing different scenarios facilitates real-time observation of multiphysics field changes, improving understanding of optimal designs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Luca Gasparini, Antonio Benedetti, Giulia Marchese, Connor Gallagher, Pierantonio Facco, Massimiliano Barolo
Summary: In this paper, a method for batch process monitoring with limited historical data is investigated. The methodology utilizes machine learning algorithms to generate virtual data and combines it with real data to build a process monitoring model. Automatic procedures are developed to optimize parameters, and indicators and metrics are proposed to assist virtual data generation activities.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Julia Jimenez-Romero, Adisa Azapagic, Robin Smith
Summary: Energy transition is a significant and complex challenge for the industry, and developing cost-effective solutions for synthesizing utility systems is crucial. The research combines mathematical formulation with realistic configurations and conditions to represent utility systems and provides a basis for synthesizing energy-efficient utility systems for the future.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Samuel Adeyemo, Debangsu Bhattacharyya
Summary: This work develops algorithms for estimating sparse interpretable data-driven models. The algorithms select the optimal basis functions and estimate the model parameters using Bayesian inferencing. The algorithms estimate the noise characteristics and model parameters simultaneously. The algorithms also exploit prior analysis and special properties for efficient pruning, and use a modified Akaike information criterion for model selection.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Abbasali Jafari-Nodoushan, Mohammad Hossein Dehghani Sadrabadi, Maryam Nili, Ahmad Makui, Rouzbeh Ghousi
Summary: This study presents a three-objective model to design a forward supply chain network considering interrelated operational and disruptive risks. Several strategies are implemented to cope with these risks, and a joint pricing strategy is used to enhance the profitability of the supply chain. The results show that managing risks and uncertainties simultaneously can improve sustainability goals and reduce associated costs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
T. A. Espaas, V. S. Vassiliadis
Summary: This paper extends the concept of higher-order search directions in interior point methods to convex nonlinear programming. It provides the mathematical framework for computing higher-order derivatives and highlights simplified computation for special cases. The paper also introduces a dimensional lifting procedure for transforming general nonlinear problems into more efficient forms and describes the algorithmic development required to employ these higher-order search directions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
David A. Linan, Gabriel Contreras-Zarazua, Eduardo Sanhez-Ramirez, Juan Gabriel Segovia-Hernandez, Luis A. Ricardez-Sandoval
Summary: This study proposes a parallel hybrid algorithm for optimal design of process flowsheets, which combines stochastic method with deterministic algorithm to achieve faster and improved convergence.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiaoyong Lin, Zihui Li, Yongming Han, Zhiwei Chen, Zhiqiang Geng
Summary: A novel GAT-LSTM model is proposed for the production prediction and energy structure optimization of propylene production processes. It outperforms other models and can provide the optimal raw material scheme for actual production processes.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangoz, Ali Mesbah, Fani Boukouvala, Fernando Lima, Antonio del Rio Chanona, Christos Georgakis
Summary: This paper provides a concise perspective on the potential of machine learning in the PSE domain, based on discussions and talks during the FIPSE 5 conference. It highlights the need for domain-specific techniques in molecular/material design, data analytics, optimization, and control.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hesam Hassanpour, Prashant Mhaskar, Brandon Corbett
Summary: This work addresses the problem of designing an offset-free implementable reinforcement learning (RL) controller for nonlinear processes. A pre-training strategy is proposed to provide a secure platform for online implementations of the RL controller. The efficacy of the proposed approach is demonstrated through simulations on a chemical reactor example.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hunggi Lee, Donghyeon Lee, Jaewook Lee, Dongil Shin
Summary: This study introduces an innovative framework that utilizes a limited number of sensors to detect chemical leaks early, mitigating the risk of major industrial disasters, and providing faster and higher-resolution results.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Sibel Uygun Batgi, Ibrahim Dincer
Summary: This study examines the environmental impacts of three alternative hydrogen-generating processes and determines the best environmentally friendly option for hydrogen production by comparing different impact categories. The results show that the solar-based HyS cycle options perform the best in terms of global warming potential, abiotic depletion, acidification potential, ozone layer depletion, and human toxicity potential.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
LaGrande Gunnell, Bethany Nicholson, John D. Hedengren
Summary: A review of current trends in scientific computing shows a shift towards open-source and higher-level programming languages like Python, with increasing career opportunities in the next decade. Open-source modeling tools contribute to innovation in equation-based and data-driven applications, and the integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to significantly accelerate progress, but long-term support mechanisms are still necessary.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Daniel Cristiu, Federico d'Amore, Fabrizio Bezzo
Summary: This study presents a multi-objective mixed integer linear programming framework to optimize the supply chain for mixed plastic waste in Northern Italy. Results offer quantitative insights into economic and environmental performance, balancing trade-offs between maximizing gross profit and minimizing greenhouse gas emissions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
