Material Transport Research Articles

Three-dimensional flow structures modelling based on a depth-integrated method in a sharply curved open channel over topography

In this study, we introduce the bottom velocity calculation (BVC) technique, a depth-integrated approach for modeling three-dimensional flow systems in the two-dimensional (2D) river management model framework. The method has been expanded to a general coordinate system and its applicability to flow in bends and meanders for the applications to rivers. The method was validated to a laboratory experiment conducted in a sharply curved channel over topography. The pattern of water surface elevation and vertical velocity distribution can be replicated by the BVC method’s models, which also show strong qualitative agreement with the experimental dataset and 3D model. The benefit of using the BVC technique instead of the 2D model is verified; the 2D model is unable to replicate the profile since it does not take into account three-dimensional flow structures. As seen above, the BVC method is helpful in evaluating the river environment because it can account for the complicated material transports caused by three-dimensional flows in the meandering sections of the river channel.

Feasibility of a clouds and edge computing scheme for internal due date assignment in advanced manufacturing systems

Most of the existing edge computing applications in manufacturing systems are used for machine status detection, material transportation tracking, resource management, process control, and production planning, but are rarely used to support management activities. To fill this gap, this study designs a cloud and edge computing scheme for internal due date assignment, in which a sales representative visits a customer and negotiates with him/her the due date of a possible order. In the past, such tasks were accomplished by querying a deep learning system on the backend or cloud server, which was affected by difficulties such as cloud computing application licensing, network speed, and bandwidth. To overcome these difficulties, in the cloud and edge computing scheme, a possible order is broken down into lots that are released based on daily quotas. A deep neural network (DNN) is then constructed on the cloud server to estimate the output time of each lot, thereby obtaining the completion time of the possible order for internal due date assignment. A random forest (RF) is also built to approximate the trained DNN for internal due date assignment using edge computing. The cloud and edge computing scheme for internal due date assignment has been experimentally applied to a wafer fabrication case. According to the experimental results, the cloud and edge computing scheme provided a portable, self-contained, and instant solution for internal due date assignment that the common practice and cloud computing counterparts could not achieve. The cloud and edge computing scheme also avoided the potential leakage of confidential production condition data.

Regioselective late-stage functionalization of tetraphenylenes: rapid construction of double helical architectures and potential hole transport materials

Tetraphenylene-based cyclic iodonium salts could be achieved via regioselective iodination oriented by tert-butyl and nitro substituents. Subsequent atom(s) insertion to these iodonium salts yielded a series of [8 + n] and [n + 8 + n] fused-rings.

An extensive study on investigating the heterojunction compatibility of novel charge transport materials, defect management and design optimization for high-performance lead-free CsSnl3-based perovskite solar cells

An extensive study on investigating the heterojunction compatibility of novel charge transport materials, defect management and design optimization for high-performance lead-free CsSnl3-based perovskite solar cells

Multifunctional Organic Ammonium Dopants to Electron Transport Layer for Efficient Inverted Perovskite Solar Cells

Fullerenes are the most widely used electron transport material (ETM) in inverted perovskite solar cells (PSCs) with a p-i-n structure. However, nonradiative recombination at the interface between the perovskite and...

Recent breakthroughs in non-conjugated polymers for thermally activated delayed fluorescent OLEDs: emitters, hosts, and hole-transport materials

Non-conjugated linkers interrupt direct conjugation in the polymer backbone, providing enhanced solubility, blue TADF emitters, and high triplet energy host and hole transport materials.

A low-cost, high-performance, dopant-free phenyl-based hole transport material for efficient and stable perovskite solar cells

Benefiting from the expansion of the central structure, the carrier mobility of HTMs is elevated to 2.56 × 10−4 cm2 V−1 s−1. Thus, the PCE of PSCs with dopant-free HTL is increased from 17.57% to 20.37%.

Recent Progress on Spiro-type Hole Transport Materials for Efficient and Stable Perovskite Solar Cells

Hole transport materials (HTMs), as an important part of n-i-p perovskite solar cells (PSCs), are one of the main bottlenecks to further improve the efficiency and stability of devices. Since...

An effective universal ternary complex hole transport material enabled by intermolecular interactions for polymer solar cells

An effective universal ternary complex hole transport material enabled by intermolecular interactions for polymer solar cells

Can fullerene derivative PCBM serve as an innovative hole transport material for CsPbBr3 perovskite solar cells?

Can fullerene derivative PCBM serve as an innovative hole transport material for CsPbBr3 perovskite solar cells?

Theoretical study on the optoelectronic properties of fluorinated phenylpyrrole-based hole transport materials for perovskite solar cells

Hole transport materials (HTMs) in perovskite solar cells (PSCs) are crucial for hole transport and exciton dissociation; therefore, developing efficient HTMs is key to improving the stability and photoelectric conversion efficiency of PSCs.

Enhancing the stability of inverted perovskite solar cells through Cu2ZnSnS4 nanoparticles hole transporting material

Cu2ZnSnS4 nanoparticles as hole transport material stabilise perovskite solar cells' performance.

Floor space optimization of Molds in Boat Manufacturing using Dynamic programming and optimization algorithm

Floor space management in manufacturing of boats requires to be optimized as much as possible and particularly with reference to molds, which are large fixed assets. This article uses dynamic programming to solve the problem of floor space allocation, with particular emphasis on the minimization of unused space and the maximization of mold placement. By specifying the problem as a resource allocation problem, the article naturally considers spatial configurations and operational conditions such as mold size, production timeline, and material transportation. The dynamic programming approach is used to provide a scalable and cost-efficient solution as it is a decomposition of the problem into sub-problems and the global optimum is achieved for layouts. The analysis shows a potential of achieving a high space utilization, the elimination of operational constraints and an improvement of flow rates leading to the formulation of smart manufacturing solutions in the boat industry. This article explains about the analysis of Optimizing Floor Space in Boat Manufacturing, Formulation of the Mold Arrangement Challenge, Key Constraints and Variables in Space Optimization, Dynamic Programming for Mold Layout Optimization, Significance of Efficient Floor Space Utilization and Practical Applications in Boat Manufacturing Facilities were also discussed. In this review article, a total number of 60 papers were choosen from the year 2019 to 2024 accordingly. Moreover, 11 papers were selected from the year 2019, 18 papers were selected from 2020, 13 were selected from the year 2021, 9 papers from the year 2022, 6 papers were selected from 2023 and 3 were from 2024 respectively

PENGARUH VARIASI KECEPATAN DAN BEBAN TERHADAP JARAK TEMPUH PADA GEROBAK SORONG BERMESIN MOTOR MIO SPORTY 110 CC

The aim of this research is to determine the impact of speed and load variations on the travel distance of a motorized wheelbarrow with a 110 cc Mio Sporty engine. Choosing the right transport equipment, such as a motorized wheelbarrow, can enhance work efficiency by facilitating and speeding up the transportation of construction materials, with its capacity depending on the volume and durability of the wheelbarrow materials. Using an experimental method with speed variations of 15 km/h, 20 km/h, and 25 km/h, and loads of 40 kg, 60 kg, and 80 kg, along with 30 ml of Pertalite fuel, road tests were conducted to find speed and load efficiency. The results indicate that speed and load variations affect the travel distance. A speed of 20 km/h is the most efficient for the travel distance of the motorized wheelbarrow with a 110 cc Mio Sporty engine, as it shows the largest distance difference. Additionally, a load of 80 kg is the most efficient as it has the largest travel distance difference.

Integrating the Transportation Material in BIPA Learning at FPNU China

The Teaching of Indonesian as a Foreign Language (Bahasa Indonesia Bagi Penutur Asing or BIPA) is a means of introducing the Indonesian language and culture to the international community. This research discusses the teaching of transportation materials to BIPA learners at Fujian Polytechnic Normal University (FPNU) in China. Using the Contextual Teaching and Learning (CTL) theory regarding second language acquisition (SLA) in the integration of transportation material in BIPA learning. The approach used in this research is descriptive qualitative. The research was conducted by observing BIPA learning in the class, followed by recording the implementation of BIPA transportation material learning among respondents in the Indonesian Language Department at FPNU China. The findings showed that the transportation material helped BIPA respondents learn Indonesian through contextual and communicative methods. The material provided includes vocabulary related to types of public transportation in Indonesia. The research results showed that the material on Indonesia's transportation system provides a more contextual learning experience for respondents at FPNU China.

A analytical study on supply chain management and distribution channel at Chamundeshwari sugar industry, srinivasapura. hassan

Supply Chain Management (SCM) plays a crucial role in ensuring the efficiency and effectiveness of the Chamundeshwari Sugar Industry. This analytical study examines the intricate components of SCM within the industry, focusing on procurement, production, and distribution channels. The objective is to assess the current SCM strategies, identify potential inefficiencies, and propose recommendations for optimization. The study begins by analyzing the procurement process, including sourcing raw materials such as sugarcane, and how supplier relationships impact overall productivity. It then delves into the production process, evaluating the conversion of raw materials into finished products. The distribution channels, which are critical for delivering the final product to consumers, are also scrutinized, with particular attention to logistics, warehousing, and transportation. Through qualitative and quantitative analysis, the study highlights key challenges faced by the Chamundeshwari Sugar Industry, such as fluctuating raw material prices, transportation bottlenecks, and demand forecasting inaccuracies. Additionally, the research explores the impact of technological advancements on SCM, including the use of automation and data analytics for better decision-making. This study refers to testing through Chi-Square on analysis and interpretation. Key words: Logistics management, inventory management, procurement management, transpotation management, warehouse management, channel management.

Innovative Synergistic Genetic Algorithm and Particle Swarm Optimization for Scheduling Optimization in Mobile Robots

Autonomous Mobile Robots (AMRs) are crucial in modern manufacturing for automating material handling and transportation. However, optimizing their task scheduling is challenging due to conflicting objectives like minimizing makespan and reducing energy consumption. Traditional algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) often yield suboptimal results. This study proposes an innovative Synergistic GA-PSO algorithm that combines the exploratory capabilities of GA with the fast convergence of PSO. Experiments conducted in MATLAB demonstrate that the Synergistic GA-PSO algorithm consistently outperforms GA, PSO, and ACO, especially in complex environments, by enhancing scheduling accuracy, reducing idle intervals, and lowering energy consumption.

Harnessing orbital and valley thermal transport in 2D materials: the significance of inversion symmetry

Orbitronics and valleytronics, analogous to spintronics, leverage the orbital degree of freedom and the valley degree of freedom of electrons to carry information, promising significant advancements in information processing. In this study, we disentangle the orbital and valley Nernst effect (VNE) in 2D monolayers, based on the global symmetry of the monolayers. We conduct an in-depth analysis of the orbital (valley) Nernst effect in inversion symmetric (asymmetric) monolayers, using an analytical tight binding model. Furthermore, we elucidate the dependence of the two effects on various inherent materials' parameters using the prototypical Kane-Mele model. Our calculations show that an inversion symmetric gapped Kagome lattice shows a significant orbital Nernst effect emerging from the interatomic contribution, even in the absence of both spin and VNEs. Furthermore, for the inversion asymmetric 2H-phase of TMDs, we elucidate that the valley degree of freedom encompasses the orbital degree of freedom and the VNE can be more accurately described using the orbital degree of freedom, hence termed as the valley-orbital Nernst effect.

High‐Efficiency and Stable Perovskite Solar Cells Enabled by Halogen‐Free Cosolvent‐Processed Pyrazine‐Based Dopant‐Free Hole Transport Material

ABSTRACTThe complex molecular structures of electron donor (D)–acceptor (A) polymers provide a wealth of useful hints for producing high power conversion efficiency (PCE) as hole transport materials (HTMs) in perovskite solar cells (PVSCs). Given the recent improvements in PCE, various features are focused on altering the functionalities of HTMs. In this study, a pyrazine‐based acceptor is fused with two known donors benzodithiophene (BDT) and dithienobenzodithiophene (DTBDT) to synthesize two new D–A type polymers (NBD‐Pyz and NDT‐Pyz) to employ them as dopant‐free HTM in PVSCs. The insertion of pyrazine moiety downshifted the energy levels and enhanced coplanarity for both the HTMs. NBD‐Pyz can significantly lower the trap density and passivate the perovskite layer. More interestingly, the NBD‐Pyz HTM performs better than NDT‐Pyz, exhibiting higher hole mobility and better solubility in 2‐methyl anisole (2MA) and o‐xylene. Moreover, a 2MA/o‐xylene cosolvent‐processed dopant‐free polymeric NBD‐Pyz HTM‐based device achieved a champion PCE of 22.9%. Unlike NDT‐Pyz and Spiro‐OMeTAD‐based PVSCs, the unencapsulated NBD‐Pyz devices were more stable, retaining almost 90% of their initial efficiency after 1000 h. In addition, excellent thermal stability was demonstrated by the resulting PVSCs without encapsulation. image

Ultra-Stiff yet Super-Elastic Graphene Aerogels by Topological Cellular Hierarchy.

Lightweight cellular materials with high stiffness and excellent recoverability are critically important in structural engineering applications, but the intrinsic conflict between these two properties presents a significant challenge. Here, a topological cellular hierarchy is presented, designed to fabricate ultra-stiff (>10 MPa modulus) yet super-elastic (>90% recoverable strain) graphene aerogels. This topological cellular hierarchy, composed of massive corrugated pores and nanowalls, is designed to carry high loads through predominantly reversible buckling within the honeycomb framework. The compressive modulus of the as-prepared graphene aerogel is nearly twice that of conventional graphene aerogel. This high-stiff graphene aerogel also exhibits exceptional mechanical recoverability, achieving up to 60% strain recovery over 10000 fatigue cycles without significant structural failure, outperforming most previously reported porous lattices and monoliths. It is further demonstrated that this graphene aerogel exhibits superior energy dissipation and anti-fatigue dynamic impact properties, with an energy absorption capacity nearly an order of magnitude greater than that of conventional aerogels. These exceptional properties of the topological cellular graphene aerogel open new avenues for high-energy bullet protection, offering great promise for the development of lightweight, armor-like protective materials in transportation and aerospace applications.