Efficient Transport Research Articles

Boosting the electrocatalytic performance of CuCo2S4 via surface-state engineering for ampere current water electrolysis applications

For the efficient production of green H2 on an industrial scale, developing durable, cost-effective electrocatalysts using earth-abundant transition-metals is crucial. Herein, we report a robust, bifunctional sulfurized CuCo2O4 (CCS/Ov) catalyst with engineered oxygen-vacancies, in which the metal catalyst is tunes to high valence state, significantly altering the intrinsic reaction kinetics and generating better catalytic activity for efficient ion transport in various electrolytes (neutral, seawater, alkaline simulated-seawater (ASW), and KOH). The optimized dual-strategy synthesized CCS/Ov catalysts with hierarchical morphology exhibits modest overpotential of 383 and 355 mV at 1000 mA cm−2 for OER and HER, respectively, in 1 M KOH. Impressively, an electrolyzer cell (CCS/Ov||CCS/Ov) demonstrates low cell-voltage of 1.487 V (6 M KOH), with excellent robustness in an ASW (1 and 2 M) environment against corrosive chlorine. The bifunctional CCS/Ov||CCS/Ov catalyst outperforms a state-of-the-art paired Pt/C||RuO2 catalyst and maintains the lowest potential response at up to 2000 mA cm−2, while demonstrating remarkably stable simultaneous O2 and H2 generation over 10 days at various current rates. Additionally, DFT calculations confirmed that CCS/Ov catalysts demonstrate significantly enhanced HER and OER activities due to reduced H2O dissociation energy and strong intermediate binding energy, which is attributed to the anionic vacancy near Co3+. The excellent bifunctional performance of the hierarchical CCS/Ov highlights its potential as non-precious catalyst with facile fabrication approach.

Analysis of The Probability od Choosing a Public Transportation Mode Using A Binomial Model of Differential Logit

Urbanization and mobility of the population have increased interest in efficient and convenient transportation systems, especially for trips from Cirebon to Jakarta via the Cipali toll road. Public transportation modes that can be used from Cirebon to Jakarta include buses, travel and trains. This study reviews public transportation buses and travel, focusing on the characteristics and probability of mode selection by travelers. The crucial factors studied are cost, travel time, and access time. Primary data was obtained from questionnaires using the stated preference method and secondary data obtained from related sources. The method used is linear regression modeling and binomial logit difference, which is obtained from data on travel cost (X1), travel time (X2), and travel access time (X3), which is tested using SPSS software with the regression equation obtained is Y = 2.386 + 0.251 X1.3 + X2 + 0.301 X1.4 + 0.497 X3.1. with a travel cost of Rp. 110,000 and with a travel time of 4 hours and 30 minutes, travelers prefer the bus mode (64.2%) with the most implicative attribute is the cost of travel, then the percentage value calculated using probability calculations and binomial models logits, the difference is (99.9%) choosing the bus and (0.1%) choosing travel. If the trevel wants to intensify the opportunity to choose the mode used by travelers with a percentage above 50%, then travel must reduce the fare at least Rp. 25,000 from the bus fare.

Mechanochemistry-mediated colloidal liquid metals for electronic device cooling at kilowatt levels.

Electronic systems and devices operating at significant power levels demand sophisticated solutions for heat dissipation. Although materials with high thermal conductivity hold promise for exceptional thermal transport across nano- and microscale interfaces under ideal conditions, their performance often falls short by several orders of magnitude in the complex thermal interfaces typical of real-world applications. This study introduces mechanochemistry-mediated colloidal liquid metals composed of Galinstan and aluminium nitride to bridge the practice-theory disparity. These colloids demonstrate thermal resistances of between 0.42 and 0.86 mm2 K W-1 within actual thermal interfaces, outperforming leading thermal conductors by over an order of magnitude. This superior performance is attributed to the gradient heterointerface with efficient thermal transport across liquid-solid interfaces and the notable colloidal thixotropy. In practical devices, experimental results demonstrate their capacity to extract 2,760 W of heat from a 16 cm2 thermal source when coupled with microchannel cooling, and can facilitate a 65% reduction in pump electricity consumption. This advancement in thermal interface technology offers a promising solution for efficient and sustainable cooling of devices operating at kilowatt levels.

Impurity-healing interface engineering for efficient perovskite submodules.

One issue that always strands the scaling-up development of perovskite photovoltaics is the significant efficiency drop when enlarging the device area, which is caused by the inhomogeneous distribution of defected sites1-3. In the narrow band gap formamidinium lead iodide (FAPbI3), the native impurities of PbI2 and δ-FAPbI3 non-perovskite could induce unfavored non-radiative recombination, as well as inferior charge transport and extraction 4,5.Here, we develop an impurity-healing interface engineering strategy to well address the issue both in small-area solar cell and large-scale submodule. With the introduction of a functional cation, 2-(1-cyclohexenyl)ethyl ammonium, two-dimensional (2D) perovskite with high mobility is rationally constructed on FAPbI3 to horizontally cover the film surface and vertically penetrate to the grain boundaries of 3D perovskites. Such unique configuration not only comprehensively transforms the PbI2 and δ-FAPbI3 impurities into stable 2D perovskite and realize a uniform defect passivation, but also provides interconnecting channels for efficient carrier transport. As a result, the FAPbI3-based small-area (0.085 cm2) solar cells achieve a champion efficiency over 25.86% with a notably high fill factor (FF) of 86.16%. More encouragingly, the fabricated submodules with the aperture area of 715.1 cm2 obtain a certified record efficiency of 22.46% with a good FF of 81.21%, showcasing the feasibility and effectualness of the impurity-healing interface engineering for scaling-up promotion with well-preserved photovoltaic performance.

Enhancing H+ conduction through glycolic acid-doped alginate-PVA based biopolymer electrolytes

This study investigates the development of a biopolymer blend electrolyte composed of alginate and poly (vinyl alcohol) (PVA), doped with glycolic acid (GA) to enhance H+ conductivity. The addition of GA significantly impacts the biopolymer blend's physicochemical properties and ionic conduction performance. Fourier transform infrared (FTIR) spectroscopy verified the intricate interactions and hydrogen bonding between the alginate-PVA matrix and GA. The addition of GA was shown to increase the amorphous phase, as observed through X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis. This increase in the amorphous phase was found to enhance the thermal stability. Impedance analysis demonstrated a significant increase in ionic conductivity from approximately ∼10⁻⁸ S cm⁻1 for the undoped blend to 3.45 × 10⁻⁵ S cm⁻1 with 30 wt% GA (sample GA-30). The enhanced H+ conduction behaviour was consistent across various temperatures, adhering to the Arrhenius rule. These findings suggest that the alginate-PVA-GA system is a promising candidate for efficient proton transport applications.

Single-Molecule Mechanoresistivity by Intermetallic Bonding.

The metal-electrode interface is key to unlocking emergent behaviour in all organic electrified systems, from battery technology to molecular electronics. In the latter, interfacial engineering has enabled efficient transport, higher device stability, and novel functionality. Mechanoresistivity - the change in electrical behaviour in response to a mechanical stimulus and a pathway to extremely sensitive force sensors - is amongst the most studied phenomena in molecular electronics, and the molecule-electrode interface plays a pivotal role in its emergence, reproducibility, and magnitude. In this contribution, we show that organometallic molecular wires incorporating a Pt(II) cation show mechanoresistive behaviour of exceptional magnitude, with conductance modulations of more than three orders of magnitude upon compression by as little as 1 nm. We synthesised series of cyclometalated Pt(II) molecular wires, and used scanning tunnelling microscopy - break junction techniques to characterise their electromechanical behaviour. Mechanoresistivity arises from an interaction between the Pt(II) cation and the Au electrode triggered by mechanical compression of the single-molecule device, and theoretical modelling confirms this hypothesis. Our study provides a new tool for the design of functional molecular wires by exploiting previously unreported ion-metal interactions in single-molecule devices, and develops a new framework for the development of mechanoresistive molecular junctions.

Human-powered vehicles as a way to abate transport-related greenhouse gas emissions: Part 2 - A virtual prototype for emissions and performance analyses

Velomobiles, despite their potential for efficient transportation, remain relatively unknown compared to electric cars, receiving limited attention in academic research and public awareness. This paper highlights their untapped potential and underlines public interest in their adoption, provided a velomobile meeting customer requirements is available. Leveraging the Model Based System Engineering (MBSE) methodology, this work presents a structured approach to design, focusing on customer needs translation and digital prototype validation. This iterative process ensures velomobiles meet performance criteria while minimizing environmental impact. The lack of standardized testing for the energy consumption of Human-Powered Vehicles (HPVs) is addressed by proposing an analysis of consumption under diverse operating conditions, giving information on the environmental assessments. This study underscores velomobiles’ potential as a sustainable transportation solution and provides a framework for their design, validation, and optimization.

When cellulose nanocrystals meet graphene oxide: Structurally enhanced aerogels for efficient solar steam generation and water purification

Pollution, population growth, and climate change are intensifying global freshwater shortages. Traditional methods of collecting freshwater, such as rainwater harvesting and sewage treatment, have high energy consumption, limiting their implementation in underdeveloped regions. On the other hand, solar-driven seawater evaporation offers a promising solution, purifying water using naturally abundant solar energy. Reduced graphene oxide (rGO) is considered as a strong candidate for this purpose due to its broad spectral absorption. However, its hydrophobicity hinders its direct use in solar steam generators. Here, we report the preparation of a series of cellulose nanocrystal (CNC)-rGO aerogels (CGAs) through a one-pot hydrothermal gelation process, followed by unidirectional freeze-drying. The introduction of CNCs enhances the hydrophilicity and structural stability of the resulting CGAs. The CGAs also feature uniform and unidirectional channels that promote efficient water transport, as confirmed by scanning electron microscopy (SEM) and X-ray microtomography (XMT). The CGAs have an optimized water evaporation rate of 1.80 kg m−2 h−1 under 1 sun irradiation, with 90 % solar-to-vapor energy efficiency. Moreover, durability and seawater desalination tests provide additional evidence for the practicality of CGAs in water purification. It is anticipated the implementation of CGAs will expedite the application of solar steam generators in practical scenarios.

N‐Type Molecular Thermoelectrics Based on Solution‐Doped Indenofluorene‐Dimalononitrile: Simultaneous Enhancement of Doping Level and Molecular Order

AbstractThe development of n‐type organic thermoelectric materials, especially π‐conjugated small molecules, lags far behind their p‐type counterparts, due primarily to the scarcity of efficient electron‐transporting molecules and the typically low electron affinities of n‐type conjugated molecules that leads to inefficient n‐doping. Herein, the n‐doping of two functionalized (carbonyl vs dicyanovinylene) indenofluorene‐based conjugated small molecules, 2,8‐bis(5‐(2‐octyldodecyl)thien‐2‐yl)indeno[1,2‐b]fluorene‐6,12‐dione (TIFDKT) and 2,2′‐(2,8‐bis(3‐alkylthiophen‐2‐yl)indeno[1,2‐b]fluorene‐6,12‐diylidene)dimalononitrile (TIFDMT) are demonstrated, with n‐type dopant N‐DMBI. While TIFDKT shows decent miscibility with N‐DMBI, it can be hardly n‐doped owing to its insufficiently low LUMO. On the other hand, TIFDMT, despite a poorer miscibility with N‐DMBI, can be efficiently n‐doped, reaching a respectable electrical conductivity of 0.16 S cm−1. Electron paramagnetic resonance measurements confirm the efficient n‐doping of TIFDMT. Based on density functional theory (DFT) calculations, the LUMO frontier orbital energy of TIFDMT is much lower, and its wave function is more delocalized compared to TIFDKT. Additionally, the polarons are more delocalized in the n‐doped TIFDMT. Remarkably, as indicated by the grazing‐incidence wide‐angle X‐ray scattering (GIWAXS), the molecular order for TIFDMT thin‐film is enhanced by n‐doping, leading to more favorable packing with edge‐on orientation and shorter π‐π stacking distances (from 3.61 to 3.36 Å). This induces more efficient charge transport in the doped state. Upon optimization, a decent thermoelectric power factor of 0.25 µWm−1K−2 is achieved for n‐doped TIFDMT. This work reveals the effect of carbonyl vs dicyanovinylene on the n‐doping efficiency, microstructure evolution upon doping and thermoelectric performance, offering a stepping stone for the future design of efficient n‐type thermoelectric molecules.

Perceptions of Service Enhancements in Shared Autonomous Vehicles: A Demographic Perspective

As the pressure on urban mobility rises, shared autonomous vehicles (SAVs) offer enhanced transportation efficiency and safety. This study investigates the valuations of additional services in SAVs, examining demographics’ impact on preferences for different service features. We use data from 1723 Norwegian respondents to an online survey. We find that women put increased value on a safety host. Younger respondents value fast travel time. More tech-savvy individuals showing a higher valuation for services enhancing personal utility and comfort. Intention to use strongly predicts valuation of utilities, but not social factors.

Enhancing Cooperative Lane-Changing for Intelligent Connected Vehicles: A DDPG-Based Approach

Current research on lane-changing for intelligent connected vehicles (ICVs) primarily focuses on the control of a single ICV. Even studies on cooperative lane-changing among multiple ICVs often use fixed control algorithms, which are difficult to adapt to constantly changing traffic conditions. This paper proposes a method based on the deep deterministic policy gradient (DDPG) model. The DDPG algorithm has strong generalization capabilities, enabling it to handle complex traffic scenarios. Combined with the design of innovative reward functions, it successfully achieves the control of cooperative lane-changing for multiple ICVs. The novelty of this model is mainly reflected in the implementation of multiple ICVs control and cooperative strategies through the design of a speed reward function. Specifically, when two or more ICVs come within a 15-m range, a collaborative strategy is implemented. In this strategy, the original speeds of the vehicles involved are replaced with their average speed. This average speed is then used to compute the velocity reward. Moreover, an additional headway reward is introduced when two vehicles are on the same lane with a distance of less than 10[Formula: see text]m between them, further optimizing lane-changing decisions and enhancing driving efficiency. The innovative approach described in this paper has been validated through simulations in the highway-env simulation environment. The model’s effectiveness was tested under various conditions, including different road densities and numbers of ICVs. Results indicate that with an increasing number of episodes, the model consistently enhances both the fleet’s and each individual vehicle’s average speed and steps. It also ensures that the headway is maintained within a desired range of 10–20[Formula: see text]m. This paper showcases the potential applications of a new DDPG-based multi-networked vehicular cooperative lane-changing decision model across different scenarios. These findings provide important reference values for future research and development in intelligent transportation systems (ITS), particularly in optimizing vehicle cooperative behaviors and enhancing traffic efficiency. This paper emphasizes the model’s potential to significantly impact the management and operation of future vehicular networks, paving the way for more sophisticated and efficient transportation systems.

Zero‐Bias Anti‐Ohmic Behaviour in Diradicaloid Molecular Wires

AbstractOpen‐shell materials bearing multiple spin centres provide a key route to efficient charge transport in single‐molecule electronic devices. They have narrow energy gaps, and their molecular orbitals align closely to the Fermi level of the metallic electrodes, thus allowing efficient electronic transport and higher conductance. Maintaining and stabilising multiple open‐shell states—especially in contact with metallic electrodes—is however very challenging, generally requiring a continuous chemical or electrochemical potential to avoid self‐immolation of the open‐shell character. To overcome this issue, we designed, synthesised, and measured the conductance of a series of bis(indeno) fused acenes, where stability is imparted by a close‐shell quinoidal conformation in resonance with the diradical electronic configuration. We show here that these compounds have anti‐ohmic behaviour, with conductance increasing with increasing molecular length, at an unprecedented rate and across the entire bias window ( ). Density Functional Theory (DFT) calculations support our findings, showing the rapidly narrowing HOMO–LUMO gap, unique to these diradicaloid structures, is responsible for the observed behaviour. Our results provide a framework for achieving efficient transport in neutral compounds and demonstrate the promise that diradicaloid materials have in single‐molecule electronics, owing to their great stability and unique electronic structure.

Trajectory planning and automatic docking of LNG five-axis loading arm

PurposeIn response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.Design/methodology/approachAn automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.FindingsThe docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.Originality/valueThe proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Multi-Functional Silole Hole Transport Layer for Efficient and Stable Lead-Tin Perovskite and Tandem Solar Cells.

Despite high theoretical efficiencies and rapid improvements in performance, high-efficiency ≈1.2eV mixed Sn-Pb perovskite solar cells (PSCs) generally rely on poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT: PSS) as the hole transport layer (HTL); a material that is considered to be a bottleneck for long-term stability due to its acidity and hygroscopic nature. Seeking to replace PEDOT: PSS with an alternative HTL with improved atmospheric and thermal stability, herein, a silole derivative (Silole-COOH) tuned with optimal electronic properties and efficient carrier transport by incorporating a carboxyl functional group is designed, which results in an optimal band alignment for hole extraction from Sn-Pb perovskites and robust air and thermal stability. Thin films composed of the Silole-COOH exhibit superior conductivity and carrier mobility compared to PEDOT: PSS, in addition to reduced nonradiative quasi-Fermi-level splitting losses at the HTL/perovskite interface and improved quality of Sn-Pb perovskite. Replacement of PEDOT: PSS with Silole-COOH leads to 23.2%-efficient single-junction Sn-Pb PSCs, 25.8%-efficient all-perovskite tandems, and long operating stability in ambient air.

High‐Performance, Single‐Component Ambipolar Organic Electrochemical Transistors with Balanced n/p‐Type Properties for Inverter and Biosensor Applications

AbstractAmbipolar organic electrochemical transistors (OECTs) with a single organic mixed ionic‐electronic conductor (OMIEC) have unique advantages by reducing fabrication complexity and cost in complementary logic circuit and bioelectronic applications. However, the design and synthesis of high‐performance ambipolar OMIECs for efficient transport and coupling both cation/anion and electron/hole remain challenging. Herein, a donor–acceptor (D–A)‐typed ambipolar OMIEC polymer (DHF‐gTT) is presented, whose superior ambipolarity stems from the concurrent oligoethyleneglycol‐functionalized D/A units that facilitates cation/anion injection and transport. Additionally, the fluorination of acceptor unit improves both hole/electron transports due to the fully‐locked backbone and promotes electron injection by down‐shifting molecular energy levels. Consequently, DHF‐gTT‐based OECTs achieve balanced figure‐of‐merit (µC*) for both p‐type and n‐type operations (12.4–14.6 F cm−1 V−1 s−1), setting new benchmarks for ambipolar OECTs, in terms of n‐type µC* and electron/hole mobilities. Such ambipolar OECTs enable the inverter to achieve a record‐high gain (102 V/V) and associated n‐type and p‐type molecular detectors to offer real‐time and highly sensitive detection of histamine and hydrogen peroxide detection, respectively. These results indicate the effectiveness of judicious molecular design on achieving high‐performance ambipolar OMIECs, allowing the state‐of‐the‐art single‐component ambipolar OECTs for both highly integrated logic circuit and bioelectronic applications.

Efficient electron transport at the perovskite nanodots interface facilitates CO2 photoreduction

How to achieve controllable preparation of heterostructure and in-situ optimize the interface and internal electron transfer by a fast and economic synthesis method has become a big challenge in the practical application of photocatalysis. Herein, an island-shaped SrTiO3 (STO) perovskite nanodots and TiO2 (T) compounded S-scheme SrTiO3/TiO2 (ST) heterostructure was successfully developed. During the millisecond reaction process, the decomposed Sr2+ penetrated into the TiO2 lattice causing the lattice expansion and inducing local atomic rearrangements, resulting in the generation of STO phase. Owing to the synergy of the efficient electron transport at the perovskite nanodots interface and the stronger reduction capacity, the performance of the optimized ST1 sample is greatly improved to 86.90 μmol g−1 for CO2-to-CO and 21.31 μmol g−1 for CO2-to-CH4. The utilization of electrons reached up to 119.74 μmol g−1 h−1, which was 3.13 times higher than that of T. Detailed characterizations and density functional theory (DFT) calculations proof that the formation of intermediates HCOO− and CO32− is the key to the performance improvement critically. Overall, this work originally reports a feasible strategy for flame synthesis of S-scheme heterostructure photocatalyst.

Analysis of Road Roughness and Driver Comfort in 'Long-Haul' Road Transportation Using Random Forest Approach.

Global trade depends on long-haul transportation, yet comfort for drivers on lengthy trips is sometimes neglected. Rough roads have a major negative influence on driver comfort and increase the risk of weariness, distracted driving, and accidents. Using Random Forest regression, a machine learning technique well-suited to examining big datasets and nonlinear relationships, this study examines the relationship between road roughness and driver comfort. Using the MIRANDA mobile application, data were gathered from 1,048,576 rows, including vehicle acceleration and values for the International Roughness Index (IRI). The Support Vector Regression (SVR) and XGBoost models were used for comparative analysis. Random Forest was preferred because of its ability to be deployed in real time and use less memory, even if XGBoost performed better in terms of training time and prediction accuracy. The findings showed a significant relationship between driver discomfort and road roughness, with rougher roads resulting in increased vertical acceleration and lower comfort levels (Road Roughness: SD-0.73; Driver's Comfort: Mean-10.01, SD-0.64). This study highlights how crucial it is to provide smooth surfaces and road maintenance in order to increase road safety, lessen driver weariness, and promote long-haul driver welfare. These results offer information to transportation authorities and policymakers to help them make data-driven decisions that enhance the efficiency of transportation and road conditions.

Study on visualization of impact damage characteristics of honey peaches based on finite element method.

The study of visualization of impact damage of fruit under different thicknesses of buffer materials can provide more efficient transportation and packaging solutions, and thus the economic losses caused by fruit damage can be reduced. Pearl cotton (EPE) is commonly used as a buffer material in the market, and the impact damage behavior of honey peaches under different thicknesses of EPE buffer material was studied by using the finite element method. Firstly, the damage area, maximum contact force and damage volume during the collision of honey peaches with EPE materials of different thicknesses (2, 4, and 6mm) were obtained by the single pendulum device, and then the Modulus of elasticity and Poisson's ratio of peach flesh were obtained by compression test. Finally, the finite element model of honey peach was built and the collision simulations were performed. The results of the study showed that the values of mechanical parameters of honey peach decreased with the increase of the thickness of the buffer material. When the collision angle was below 60°, the honey peaches were not damaged in the collision with the EPE material with a thickness of 4mm or more. By comparing the tested values with the simulated values, it was found that the errors of the damage area, damage volume and maximum contact force were less than 19.71%, 26.82%, and 25.88%, respectively. The study not only proves the possibility of the finite element method in the quantitative prediction of honey peaches damage but also provides rational support for the packaging design of honey peaches.

Anionic Ionomer: Released Surface-Immobilized Cations and an Established Hydrophobic Microenvironment for Efficient and Durable CO2-to-Ethylene Electrosynthesis at High Current over One Month.

Electrosynthesis of multicarbon products, such as C2H4, from CO2 reduction on copper (Cu) catalysts holds promise for achieving carbon neutrality. However, maintaining a steady high current-level C2H4 electrosynthesis still encounters challenges, arising from unstable alkalinity and carbonate precipitation caused by undesired ion migration at the cathode under a repulsive electric field. To address these issues, we propose a universal "charge release" concept by incorporating tiny amounts of an oppositely charged anionic ionomer (e.g., perfluorinated sulfonic acid, PFSA) into a cationic covalent organic framework on the Cu surface (cCOF/PFSA). This strategy effectively releases the hidden positive charge within the cCOF, enhancing surface immobilization of cations to impede both outward migration of generated OH- and inward migration of cations, inhibiting carbonate precipitation and creating a strong alkaline microenvironment. Meanwhile, the ionomer's hydrophobic chains create a hydrophobic environment within the cCOF, facilitating efficient gas transport. In situ characterizations and theoretical calculations demonstrate that the cCOF/PFSA catalyst establishes a hydrophobic strong alkaline microenvironment, optimizing the adsorption strength and configuration of *CO intermediates to promote the C2H4 formation. The optimized catalyst achieves a 70.5% Faradaic efficiency for C2H4 with a partial current density over 470 mA cm-2. Notably, it delivers a high single-pass carbon efficiency of 96.5% for CO2RR and sustains an exceptional stability over 760 h. When implemented in a large-area MEA electrolyzer and a 5-cell MEA stack, the system achieves an industrial current of 15 A and continuous C2H4 production exceeding 19 mL min-1, marking a significant step toward industrial feasibility in CO2RR-to-C2H4 conversion.

Simulation-Based Optimization for Vertiport Location Selection: A Surrogate Model With Machine Learning Method

We present Vertiport-informed Surrogate-Based Optimization with Machine Learning Surrogates (VinS), a novel framework for solving the vertiport location problem for urban air mobility operations. The primary focus of this work is on the optimization of vertiport locations to facilitate efficient urban air transportation. Our framework helps choose not only the optimal vertiport locations but also the optimal number of vertiports. We develop a simulation model to analyze the impacts of various vertiport location configurations on the efficiency of the transportation network. To expedite the simulation process, a surrogate model is trained using machine learning algorithms, effectively reducing the computational time for evaluating a given vertiport location configuration. With the machine learning surrogate models, we apply a genetic algorithm to find the optimal set of vertiport locations. An empirical study was performed in the San Francisco Bay Area, from which we found that given the optimal set of vertiport locations, we further reduced the total travel time in the entire transportation system in the Bay Area compared with the sampled sets by 0.05% (400 h) on average. We release our framework at: https://github.com/Xuan-1998/LPSim .