In recent years, artificial intelligence has promoted the rapid development of intelligence in various fields, with mechatronics being one of its hot research topics ...
Summary
Modern offshore wind turbines (OWTs) are constructed with increasingly long blades and slender towers to capture wind resources more effectively. Consequently, OWTs have become vulnerable to ...wind and sea wave excitations. Mitigations of unfavorable OWT vibrations have been extensively investigated, with the majority focusing on passive vibration control strategies with control performance sensitive to structural frequency changes. Nonlinear energy sinks (NESs) are regarded as effective vibration control methods because their broadband fashion is robust against variations in structural frequencies. A novel NES with an improved track profile that combines both second‐ and fourth‐order polynomials (Track II NES) is proposed in the present study to improve the vibration mitigation effectiveness of traditional Track I NES with a track profile of a fourth‐order polynomial only. Governing equations of a single‐degree‐of‐freedom system with Track II NES are first established, and an equivalent linearization method is adopted to optimize the track profile and damping of the Track II NES. Moreover, a detailed 3D finite element model of a representative 5‐MW OWT is developed. Control effectiveness of the Track II NES is examined under different structural stiffnesses and mean wind speeds and then compared with that of conventional tuned mass damper (TMD) and Track I NES. Numerical results showed that the Track II NES can effectively suppress displacement and acceleration responses of OWTs and outperform its counterpart Track I NES. Moreover, the Track II NES can obtain reduction ratios close to those of the TMD but with better robustness against the detuning effect.
The exonuclease activity of Apurinic/apyrimidinic endonuclease 1 (APE1) is responsible for processing matched/mismatched terminus in various DNA repair pathways and for removing nucleoside analogs ...associated with drug resistance. To fill in the gap of structural basis for exonucleolytic cleavage, we determine the APE1-dsDNA complex structures displaying end-binding. As an exonuclease, APE1 does not show base preference but can distinguish dsDNAs with different structural features. Integration with assaying enzyme activity and binding affinity for a variety of substrates reveals for the first time that both endonucleolytic and exonucleolytic cleavage can be understood by an induced space-filling model. Binding dsDNA induces RM (Arg176 and Met269) bridge that defines a long and narrow product pocket for exquisite machinery of substrate selection. Our study paves the way to comprehend end-processing of dsDNA in the cell and the drug resistance relating to APE1.
The intermolecular asymmetric radical oxidative C(sp3)−C(sp) cross‐coupling of C(sp3)−H bonds with readily available terminal alkynes is a promising method to forge chiral C(sp3)−C(sp) bonds because ...of the high atom and step economy, but remains underexplored. Here, we report a copper‐catalyzed asymmetric C(sp3)−C(sp) cross‐coupling of (hetero)benzylic and (cyclic)allylic C−H bonds with terminal alkynes that occurs with high to excellent enantioselectivity. Critical to the success is the rational design of chiral oxazoline‐derived N,N,P(O)‐ligands that not only tolerate the strong oxidative conditions which are requisite for intermolecular hydrogen atom ion (HAA) processes but also induce the challenging enantiocontrol. Direct access to a range of synthetically useful chiral benzylic alkynes and 1,4‐enynes, high site‐selectivity among similar C(sp3)−H bonds, and facile synthesis of enantioenriched medicinally relevant compounds make this approach very attractive.
Chiral benzylic alkynes and 1,4‐enynes can be obtained in a straightforward approach from commercially available terminal alkynes and a diverse range of compounds containing benzylic and allylic C−H bonds by using the title reaction. The success of this approach lies in newly designed anionic N,N,P(O)‐ligands bearing a stable chiral oxazoline and a pentavalent phosphine oxide that are generated in situ.
•Singularity analysis of sound signals was correlated to tool wear progression in milling.•The proposed denoising algorithm can improve the SNR while preserving singularity.•HE features are ...correlated to tool conditions and independent of most cutting parameters.
Manufacturing plays an important role since they are among the largest energy consumers in modern societies. With the enhancement of environmental protection and a severe shortage of energy and resources globally, sustainable manufacturing technology has been recognized as an important future trend of manufacturing industries. Tool wear is inevitable in manufacturing and affects the surface quality and geometric tolerance significantly. Therefore, a robust and efficient Tool Condition Monitoring (TCM) system is needed to maximize tool life, ensure work-piece quality and benefit the cost control of manufacturers. Even though lots of tool condition monitoring systems have been established using various sensors, there is still an urgent demand for a low-cost and simple setup system. This article presents a sound singularity analysis approach for TCM in milling; this approach has never been previously employed for milling tools. A de-noising algorithm based on Wavelet Transform Modulus Maxima (WTMM) estimation was proposed to eliminate noises and preserve singularities. Then a wavelet basis selection method was established for optimal sound singularity analysis. The singularity was estimated by Holder Exponents (HE). A full tool life-cycle milling experiments were conducted to obtain the sound signals. The mutual information method was employed to rank HE features. The Means, Standard deviations, Minima of estimated HEs and Quantities of singular points are found most correlated to tool conditions. Then a Support Vector Machine (SVM) model trained by these features for TCM has been proposed, achieving classification accuracy of 85%. Finally, the manufacturing sustainability of the TCM approach was evaluated by tracking and improving the usages of ten same type cutters in the CNC manufacturing plant. Experimental results indicate that this approach is efficient and capable of providing effective guidance on tool replacement, and can enhance the manufacturing sustainability.
This study investigates the compressive mechanical properties and energy absorption characteristics of three types of triply periodic minimal surface (TPMS) Ti6Al4V cellular structures fabricated by ...selective laser melting (SLM). Based on the SEM observation, the morphology of Ti6Al4V alloy sheet-based TPMS structures was observed, and imperfections of SLM-fabricated cellular structures were investigated. The quasi-static uniaxial compression tests were carried out, and the deformation behavior was recorded by a camera. The result indicated that the compressive mechanical properties had an approximately positive relationship with the relative density of TPMS structures. In addition, the revised Gibson-Ashby prediction models of three sheet-based TPMS structures were established by fitting the compression test results. Furthermore, finite element analysis (FEA) of the compression process was also conducted to facilitate analysis and understanding of the deformation mechanism for TPMS structures. The results also revealed that the energy absorption capacity of TPMS structures increased with the increase in the actual relative density. The mechanical properties, energy absorption, and relative density diagram of sheet-based Ti6Al4V alloy TPMS structures were established to systematically obtain the optimal relative densities of TPMS structures for specific load-bearing and energy absorption applications.
•The mechanical properties and deformation mechanisms of three types of TPMS sheet-based structures were investigated.•The Gibson and Ashby's models for the cellular structure were modified by re-fitting the compression results.•The energy absorption characteristics of Ti6Al4V alloy sheet-based TPMS cellular structures were studied.•Numerical simulations were conducted to calculate the strength and deformation mechanisms of sheet-based TPMS structures.
Monofluoroalkanes are important in many pharmaceuticals, agrochemicals and functional materials. However, the lack of easily available and transformable monofluoroalkylating reagents that facilitate ...a broad array of transformations has hampered the application of monofluoroalkylation. Herein, we report a general and efficient method of preparing diverse aliphatic monofluorides with monofluoroalkyl triflate as the synthetic scaffold. Using both nickel‐catalyzed hydromonofluoroalkylation of unactivated alkenes and copper‐catalyzed C−C bond formation, the general diversification of the monofluoroalkylating scaffold has been exhibited. The broad utility of this monofluoroalkylating reagent is shown by concise conversion into various conventional fluoroalkylating reagents and construction of monofluoro‐alkoxy, ‐alkylamino motifs with commercially available heteroatom‐based coupling partners.
A general method allows preparation of diverse monofluorides based on the monofluoroalkyl triflate scaffold. Both nickel‐catalyzed hydromonofluoroalkylation of unactivated alkenes and copper‐catalyzed monofluoroalkylation of Grignard reagents were studied. Further utilities including conversion into conventional fluoroalkylating reagents and construction of monofluoro‐alkoxy, ‐alkylamino motifs.
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•Pseudomonas putida strain NP5 possessed simultaneous N and P removal ability.•Strain NP5 showed an excellent heavy metal and nanoparticles resistance.•Negligible emission of N2O ...occurred during heterotrophic nitrification.•An alternating anaerobic/aerobic condition markedly improved the nutrient removal.
A novel strain NP5 with efficient heterotrophic nitrification, aerobic denitrification and phosphorus accumulation ability was isolated and identified as Pseudomonas putida strain NP5. The removed ammonium and phosphate were mainly converted into intracellular components by assimilation, and negligible nitrification intermediates and N2O were accumulated during heterotrophic nitrification. In addition, the optimal conditions for nutrient removal were: succinate as carbon source, C/N 10, P/N 0.2, temperature 30 °C, salinity 0% and shaking speed 160 rpm. Besides, strain NP5 possessed an exceptional heavy metal and nanoparticles resistance. Cr6+ was found to be the most toxic among the tested metals, and it could be removed simultaneously. Moreover, an obvious phosphorus release was observed under anaerobic condition, and repeated exposure to the anaerobic/aerobic conditions could significantly improve the nutrient removal. Furthermore, the successful expression of key enzymes for nitrogen and phosphorous removal provided additional evidence for possibility of simultaneous nitrification, denitrification and phosphorus removal.
Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its ...power to predict materials properties, design de novo materials and discover new mechanisms beyond intuitions. As the structural complexity of novel materials soars, the material design problem to optimize mechanical behaviors can involve massive design spaces that are intractable for conventional methods. Addressing this challenge, ML models trained from large material datasets that relate structure, properties and function at multiple hierarchical levels have offered new avenues for fast exploration of the design spaces. The performance of a ML-based materials design approach relies on the collection or generation of a large dataset that is properly preprocessed using the domain knowledge of materials science underlying chemical and physical concepts, and a suitable selection of the applied ML model. Recent breakthroughs in ML techniques have created vast opportunities for not only overcoming long-standing mechanics problems but also for developing unprecedented materials design strategies. In this review, we first present a brief introduction of state-of-the-art ML models, algorithms and structures. Then, we discuss the importance of data collection, generation and preprocessing. The applications in mechanical property prediction, materials design and computational methods using ML-based approaches are summarized, followed by perspectives on opportunities and open challenges in this emerging and exciting field.
Here, a photocatalytic asymmetric multicomponent cascade Minisci reaction of β‐carbolines with enamides and diazo compounds is reported, enabling an effective enantioselective radical C─H ...functionalization of β‐carbolines with high yields and enantioselectivity (up to 83% yield and 95% ee). This enantioselective multicomponent Minisci protocol exhibits step economy, high chemo‐/enantio‐selective control, and good functional group tolerance, allowing access to a variety of valuable chiral β‐carbolines. Notably, diazo compounds are suitable radical precursors in enantioselective cascade radical reactions. Moreover, the efficiency and practicality of this approach are demonstrated by the asymmetric synthesis of bioactive compounds and natural products.
The study presents a photocatalytic asymmetric cascade Minisci reaction of β‐carbolines with enamides and diazo compounds, allowing for effective enantioselective radical C─H functionalization of β‐carbolines with high yields and enantioselectivity (up to 83% yield and 95% ee). The effectiveness and viability of this strategy are demonstrated through the asymmetric synthesis of bioactive compounds and natural product.
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