Engineering Design Research Articles

Sustainable STEM Lesson 2: Using Engineering Design to Make a Prototype

Sustainable STEM Lesson 2: Using Engineering Design to Make a Prototype

Application of Nonlinear Analysis in Evaluating Additive Manufacturing Process for Engineering Design Features: A Study and Recommendations

Application of Nonlinear Analysis in Evaluating Additive Manufacturing Process for Engineering Design Features: A Study and Recommendations

Reaction Environment Regulation for Electrocatalytic CO2 Reduction in Acids

AbstractThe electrocatalytic CO2 reduction reaction (CO2RR) is a sustainable route for converting CO2 into value‐added fuels and feedstocks, advancing a carbon‐neutral economy. The electrolyte critically influences CO2 utilization, reaction rate and product selectivity. While typically conducted in neutral/alkaline aqueous electrolytes, the CO2RR faces challenges due to (bi)carbonate formation and its crossover to the anolyte, reducing efficiency and stability. Acidic media offer promise by suppressing these processes, but the low Faradaic efficiency, especially for multicarbon (C2+) products, and poor electrocatalyst stability persist. The effective regulation of the reaction environment at the cathode is essential to favor the CO2RR over the competitive hydrogen evolution reaction (HER) and improve long‐term stability. This review examines progress in the acidic CO2RR, focusing on reaction environment regulation strategies such as electrocatalyst design, electrode modification and electrolyte engineering to promote the CO2RR. Insights into the reaction mechanisms via in situ/operando techniques and theoretical calculations are discussed, along with critical challenges and future directions in acidic CO2RR technology, offering guidance for developing practical systems for the carbon‐neutral community.

Molecular engineering design of twisted-backbone pure Type-I organic photosensitizers for hypoxic photodynamic therapy.

Photodynamic therapy (PDT), an emerging tumor therapeutic strategy has received tremendous attention. Enslaved by the high dependence of oxygen, Type-II photosensitizers (PSs) mediated PDT is restricted by the hypoxic environment of tumors. By transferring electrons to water or other substrates instead of oxygen, Type-I PSs hold the promise of achieving an ideal therapeutic effect under hypoxic conditions. In this study, three twisted-backbone PSs (CBz-TQs-1, CBz-TQs-2 and CBz-TQs-3) are synthesized and studied. Owing to different substituent effects, the ROS generation mechanism transfers from pure Type-II of their prototype PSs (TQs-1, TQs-2 and TQs-3) to mixed Type-I/II of CBz-TQs-1 and CBz-TQs-2 to pure Type-I of CBz-TQs-3. Moreover, CBz-TQs-3 exhibits an ultra-high ROS quantum yield (∼1.0). The in vitro and in vivo PDT effects of water-dissolvable nanoparticles (NPs) of CBz-TQs-3 are investigated. The results show that the phototoxicity of CBz-TQs-3 is not affected by hypoxic environments. In addition, a remarkable tumor ablation can be found after CBz-TQs-3 NPs mediated PDT on Balb/c mice with xenograft tumors. It proves that a twisted backbone strategy is beneficial for designing pure Type-I PSs with high-efficient hypoxic PDT.

The Role of Mechanical Engineering in Sports: Designing Equipment for Performance Enhancement

The Role of Mechanical Engineering in Sports: Designing Equipment for Performance Enhancement

Electric Double Layer Oriented Eutectic Additive Design towards Stable Zn Anodes with A High Depth of Discharge.

ZnSO4-based electrolytes for aqueous zinc ion batteries (AZIBs) fail to meet practical application metrics due to hydrogen evolution reaction (HER) and dendrite growth. In this work, we rationally designed a highly polarized eutectic additive, glycerophosphorylcholine (GPC), to regulate the EDL structure for stable Zn anodes with a high depth of discharge (DOD). On one hand, GPC molecules with abundant hydroxyl groups can precisely regulate the hydrogen bond network in EDL to suppress HER. On the other hand, the enrichment of GPC at the interface is positively responsible for the negative charge density on the Zn surface, which leads to the formation of a robust ZnxPyOz-rich solid-electrolyte interphase (SEI) and terminates dendrite growth in the charge-rich sites. This EDL-oriented eutectic additive engineering enables highly reversible and selectively (002)-textured Zn anodes to operate for over 1450h at a high DOD of 45.3%. Meanwhile, a high-capacity (185.7 mAh g-1) aqueous Zn||VS2 full cell shows remarkable cycling stability over 220 cycles with an excellent capacity retention of 90.4% even at a low current density of 0.1 A g-1 (0.5 C). This work sheds light on electrolyte design and interface engineering for high-performance aqueous batteries. This article is protected by copyright. All rights reserved.

Election Optimizer Algorithm: A New Meta-Heuristic Optimization Algorithm for Solving Industrial Engineering Design Problems

This paper introduces the election optimization algorithm (EOA), a meta-heuristic approach for engineering optimization problems. Inspired by the democratic electoral system, focusing on the presidential election, EOA emulates the complete election process to optimize solutions. By simulating the presidential election, EOA introduces a novel position-tracking strategy that expands the scope of effectively solvable problems, surpassing conventional human-based algorithms, specifically, the political optimizer. EOA incorporates explicit behaviors observed during elections, including the party nomination and presidential election. During the party nomination, the search space is broadened to avoid local optima by integrating diverse strategies and suggestions from within the party. In the presidential election, adequate population diversity is maintained in later stages through further campaigning between elite candidates elected within the party. To establish a benchmark for comparison, EOA is rigorously assessed against several renowned and widely recognized algorithms in the field of optimization. EOA demonstrates superior performance in terms of average values and standard deviations across the twenty-three standard test functions and CEC2019. Through rigorous statistical analysis using the Wilcoxon rank-sum test at a significance level of 0.05, experimental results indicate that EOA consistently delivers high-quality solutions compared to the other benchmark algorithms. Moreover, the practical applicability of EOA is assessed by solving six complex engineering design problems, demonstrating its effectiveness in real-world scenarios.

Leveraging co-production within ecosystem restoration to maximize benefits to coastal birds

Coastal Louisiana's ecosystems are threatened by anthropogenic factors exacerbated by climate change induced sea-level rise. The 2010 Deepwater Horizon oil spill resulted in injuries and deaths to coastal birds in Louisiana, and the ongoing loss of habitat has limited the potential for successful nesting of resident birds throughout the coast. Habitat loss is being addressed through increased large-scale ecosystem restoration as a result of settlement funds from the Deepwater Horizon oil spill. To further inform bird restoration in Louisiana, an avian restoration guidance document (Guidance for Coastal Ecosystem Restoration and Monitoring to Create or Improve Bird-NestingHabitat, 2023) was developed to maximize restoration benefits for coastal breeding birds while also achieving broader habitat restoration objectives. The developed restoration guidance was co-produced by subject-matter experts and professionals, including avian experts, engineers, and coastal restoration project managers. The result of this cross-disciplinary effort was specific and targeted guidance that presents designable habitat features that are in the control of project engineers and are also important high-value bird nesting habitats (e.g., shoreline access, elevation heterogeneity and edge habitat). For the first time in Louisiana, defined nest-site characteristics and monitoring approaches are readily available to inform ecosystem restoration project implementation. The restoration document specifically emphasizes bird species that breed and nest in coastal habitats in Louisiana, and restoration managers can use these guidelines to explicitly incorporate bird nesting habitat features into coastal restoration planning, design, and implementation. In developing this guidance, many knowledge gaps and data needs were identified specific to engineering and project design, enabling the research community to frame research questions around specific coastal restoration questions. The co-production of science model applied here for avian resources is applicable to a wide range of other living marine resources that may benefit from large-scale ecosystem restoration and is an example of the benefits of working relationships, communications, and common goal setting.

Breaking piezoelectric limits of molecules for biodegradable implants

AbstractIn the quest for optimizing biodegradable implants, the exploration of piezoelectric materials stands at the forefront of biomedical engineering research. Traditional piezoelectric materials often suffer from limitations in biocompatibility and biodegradability, significantly impeding their in vivo study and further biomedical application. By leveraging molecular engineering and structural design, a recent innovative approach transcends the conventional piezoelectric limits of the molecules designed for biodegradable implants. The biodegradable molecular piezoelectric implants may open new avenues for their applications in bioenergy harvesting/sensing, implanted electronics, transient medical devices and tissue regeneration.

Binary Organic Solar Cells with Exceeding 19% Efficiency via the Synergy of Polyfluoride Polymer and Fluorous Solvent.

Rational molecular design and suitable device engineering are two important strategies to boost the efficiencies in organic solar cells (OSCs). Yet these two approaches are independently developed, while their synergy is believed to be more productive. Herein, a branched polyfluoride moiety, heptafluoroisopropoxyl group, is introduced into the sidechains of conjugated polymers for the first time. Compared with the conventional alkyl chain, this polyfluoride chain can endow the resulting polymer namely PF7 with highly packing order and strong crystallinity owing to the strong polarization and fluorine-induced interactions, while good solubility and moderate miscibility are retained. As a result, PF7 comprehensively outperforms the state-of-the-art polymer PM6 in photovoltaic properties. More importantly, based on the solubility of heptafluoroisopropoxyl groups in fluorous solvents, a new post-treatment denoted as fluorous solvent vapor annealing (FSVA) is proposed to match PF7. Differing from the existing post-treatments, FSVA can selectively reorganize fluoropolymer molecules but less impact small molecules in blend films. By employing the synergy of fluoropolymer and fluorous solvent, the device achieves a remarkable efficiency of 19.09%, which is among the best efficiencies in binary OSCs. The polymer PF7 and the FSVA treatment exhibit excellent universality in various OSCs with different material combinations or device architectures. This article is protected by copyright. All rights reserved.

Pruning techniques for artificial intelligence networks: a deeper look at their engineering design and bias: the first review of its kind

Pruning techniques for artificial intelligence networks: a deeper look at their engineering design and bias: the first review of its kind

Process design in chemical engineering CFD symposium

Process design in chemical engineering <scp>CFD</scp> symposium

PointGAT: A Quantum Chemical Property Prediction Model Integrating Graph Attention and 3D Geometry.

Predicting quantum chemical properties is a fundamental challenge for computational chemistry. While the development of graph neural networks has advanced molecular representation learning and property prediction, their performance could be further enhanced by incorporating three-dimensional (3D) structural geometry into two-dimensional (2D) molecular graph representation. In this study, we introduce the PointGAT model for quantum molecular property prediction, which integrates 3D molecular coordinates with graph-attention modeling. Comparison with other current models in molecular prediction tasks showed that PointGAT could provide higher predictive accuracy in various benchmark data sets from MoleculeNet, including ESOL, FreeSolv, Lipop, HIV, and 6 out of 12 tasks of the QM9 data set. To further examine PointGAT prediction of quantum mechanical (QM) energies, we constructed a C10 data set comprising 11,841 charged and chiral carbocation intermediates with QM energies calculated at the DM21/6-31G*//B3LYP/6-31G* levels. Notably, PointGAT achieved an R2 value of 0.950 and an MAE of 1.616 kcal/mol, outperforming even the best-performing graph neural network model with a reduction of 0.216 kcal/mol in MAE and an improvement of 0.050 in R2. Additional ablation studies indicated that incorporating molecular geometry into the model resulted in markedly higher predictive accuracy, reducing the MAE value from 1.802 to 1.616 kcal/mol. Moreover, visualization of PointGAT atomic attention weights suggested its predictions were interpretable. Findings in this study support the application of PointGAT as a powerful and versatile tool for quantum chemical property prediction that can facilitate high-accuracy modeling for fundamental exploration of chemical space as well as drug design and molecular engineering.

Experimental research on the impact pressure of tidal bore fronts.

Tidal bore impact can be strong and destructive, placing estuarine infrastructures under great threat. However, there is a lack of research focusing on accurately estimating the impact pressure exerted by tidal bores. Herein new experiments were conducted to investigate the pressure of tidal bore fronts in a glass flume. Through analysis of instantaneous pressure of three forms of tidal bore, it was observed that the pressure fluctuation of weak and strong breaking bore fronts is characterized by impact pressure. The vertical distribution and maximum impact pressure of tidal bore were studied.The maximum impact pressure of breaking bore fronts appeared around 0.46 times height of it. The relationship between relative impact pressure and height of the tidal bore fronts was found to closely follow a normal probability density function. Through nonlinear regression analysis, an empirical equation was derived to calculate impact pressure, which was validated using observation data from the Qiantang River in China. This equation can be utilized to predict the impact pressure of tidal bore fronts and provide valuable support for estuarine engineering design.

Measurement of true tensile strength from Brazilian tensile strength laboratory tests

Brazilian tensile strength (BTS) testing in standard practice is a practical method to approximate tensile strength for rock core using the conversion of axial compressive vertical and diametral loading to horizontal tensile stress in the centre of the core disk. The method, however, routinely inflates tensile strength, using peak tensile stress calculated from the BTS, versus true tensile stress (TTS) from direct tensile strength (DTS) tests. This study presents a novel technique to measure TTS directly from the BTS test via the onset of nonlinearity in horizontal strain response. TTS is equivalent to the peak strength of a DTS test. While not yet standardized, the modification to achieve TTS measurements is to instrument the BTS specimen with a horizontal strain gauge on each flat side. Over 100 BTS specimens of varying lithologies were instrumented, tested, and analyzed to measure their TTS and compare to peak BTS. Results demonstrate the average measured TTS is 0.81BTS, 0.75BTS, 0.85BTS for granitoid, carbonate, and metamorphic rocks, respectively. This concurs with previous studies, validating the proposed novel TTS measurement method. We recommend measurement of TTS be adopted into standard practice for BTS laboratory testing to improve accuracy of tensile strength data in rock engineering design.

Digitalisation of engineering design education: structured freedom, flipped engagement, hybridity, and transparency

ABSTRACT This paper contributes to current discussions of digital teaching and technology within the field of engineering design education. We enter this dialogue by analysing a hybrid digital learning design for a 15-ECTS engineering design course. The course design pedagogically integrates principles from networked learning research, Problem-Based learning (PBL), as well as established pedagogical traditions. Specifically, we analyse and discuss the case based on four pedagogical principles underpinning the course: structured freedom, flipped engagement, hybridity, and transparency. The purpose of our discussions is to understand and contribute knowledge of digitalising engineering design education. Specifically, our pedagogical approach to hybrid and digital modes of learning rethink and expand the integration of digital technologies in physical design studios in a PBL context by employing networked learning principles. Following this, we draw out interesting contributions that have emerged and use the discussions to feed into the ongoing research on digitalising engineering design education.

Engineering design and manufacturing of a radio frequency plasma driver without Faraday shield for NBI application

A radio frequency (RF) driven ion source is favorable for high-power and long-pulse neutral beam injection (NBI) system. To reduce the damage caused by the isotropic heat and particle fluxes from the plasma, the traditional RF plasma driver of the NBI ion source introduces a Faraday shield (FS) for protection. However, the simulations and experiments show that the FS seriously affects the RF coupling and around 50 % of the input power deposits on the FS. The water-cooled discharge tubes with a double-layer ceramic structure have been developed to avoid using the FS structure. It's expected to improve the RF power transfer efficiency and to promote the development of high-power and long-pulse RF ion source. To verify the feasibility of the double-layer ceramic structure, the paper has carried out the fluid-thermal-structural coupling analysis and the fracture mechanical analysis on two proposed types: the alumina ceramic brazing structure and the silicon nitride ceramic bonding structure. The sample tests and the prototype manufacturing have been completed. Preliminary tests of the plasma discharge on the prototype of the alumina ceramic brazing structure have been launched. A plasma discharge of 30 kW and 20 s have been achieved.

Multi-index fusion database and intelligent evaluation modelling for geostress classification

Accurate evaluation of geostress levels is crucial for the investigation, design, and construction of underground engineering. However, existing methods for geostress classification are limited by their reliance on singular indexes, leading to discrepancies between the evaluation results and the actual observations in engineering. The discrepancies have resulted in casualties and economic losses. To address the above issues, 204 sets of geostress levels data were collected from numerous documents in the study. Six indexes related to geostress levels have been identified by analyzing the collected data and traditional criteria. Additionally, an orthogonal experimental design was carried out on the range-based indexes to obtain a multi-index fusion database. Furthermore, an intelligent evaluation model for the geostress levels was established in combination with the AutoGluon automatic machine learning framework. Subsequently, software has been developed from this model for ease of use in practical engineering. After on-site data verification, the proposed model demonstrated an accuracy of 95%, outperforming five traditional criteria, with the highest accuracy among them being 70%. The research could provide an effective basis for geostress classification, thereby enhancing the safety of on-site construction personnel.

Predicting the fire-induced structural performance of steel tube columns filled with SFRC-enhanced concrete: using artificial neural networks approach

Predicting the axial Shortening strength of concrete-filled steel tubular (CFST) columns is an important problem that this study attempts to solve for civil engineering projects. We suggest using a deep learning-based artificial neural network (ANN) model to address this issue, taking into account the intricate relationship between steel tube and core concrete. The model, called ANN-SFRC (Steel Fibre Reinforced Concrete), surpasses an R2 threshold of 0.90 and achieves impressive R2 values across different types of CFST columns. Compared to traditional linear regression methods, the ANN-SFRC model significantly improves accuracy, with an observed inaccuracy of less than 3% compared to actual values. With its reliable approach to forecasting the behavior of CFST columns under axial compression, this high-performance instrument enhances safety and accuracy during the design and planning stages of civil engineering.

Boosting External Quantum Efficiency to 12.0% of an Ultraviolet OLED by Engineering the Horizontal Dipole Orientation of a Hot Exciton Emitter

Currently, much research effort has been devoted to improving the exciton utilization efficiency and narrowing the emission spectra of ultraviolet (UV) fluorophores for organic light‐emitting diode (OLED) applications, while almost no attention has been paid to optimizing their light out‐coupling efficiency. Here, we developed a linear donor‐acceptor‐donor (D‐A‐D) triad, namely CDFDB, which possesses high‐lying reverse intersystem crossing (hRISC) property. Thanks to its integrated narrowband UV photoluminescence (PL) (λPL: 397 nm; FWHM: 48 nm), moderate PL quantum yield (φPL: 72%, Tol), good triplet hot exciton (HE) conversion capability, and large horizontal dipole ratio (Θ//: 92%), the OLEDs based on CDFDB not only can emit UV electroluminescence with relatively good color purity (λEL: 398 nm; CIEx,y: 0.161, 0.040), but also show a record maximum external quantum efficiency (EQEmax) of 12.0%. This study highlights the important role of horizontal dipole orientation engineering in the molecular design of HE UV‐OLED fluorophores.