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Nowadays, the demand for high-precision devices is becoming more intense, thanks to the growing complexity and sophistication of modern technology and applications, including microscopy, nanomeasurement and analysis instruments. However, challenges arise because environmental factors such as vibration negatively affect their performance. An active vibration isolation system (AVIS) is one of the most recent solutions for that, but the high degree-of-freedom (DoF) nature results in it strongly suffering from unwanted interactions. Hence, in this paper, a robust decoupling controller is designed to handle the mentioned disadvantages. The system model is first presented, followed by the proposed decoupling techniques, and then, a feedback controller is designed by applying the mixed-sensitivity H∞ control framework. Experimental studies are conducted to investigate the effectiveness of the proposed AVIS and compare it with other systems, namely, a passive vibration isolation system, a proportional–derivative (PD)-controlled AVIS, and a robust controlled AVIS. The robustness and decoupling performance of the proposed controller are guaranteed by suppressing external vibrations and isolating interactions, and, therefore, stabilizing the system.

Highlights A series of non-conjugated acceptor polymers with flexible conjugation-break spacers (FCBSs) of different lengths were synthesized. The effect of FCBSs length on solubility of the acceptor polymers, and their photovoltaic and mechanical properties in all-polymer solar cells were explored. This work provides useful guidelines for the design of semiconducting polymers by introducing FCBS with proper length, which can giantly improved properties that are not possible to be achieved by the state-of-the-art fully conjugated polymers. Abstract All-polymer solar cells (all-PSCs) possess attractive merits including superior thermal stability and mechanical flexibility for large-area roll-to-roll processing. Introducing flexible conjugation-break spacers (FCBSs) into backbones of polymer donor (P D) or polymer acceptor (P A) has been demonstrated as an efficient approach to enhance both the photovoltaic (PV) and mechanical properties of the all-PSCs. However, length dependency of FCBS on certain all-PSC related properties has not been systematically explored. In this regard, we report a series of new non-conjugated P As by incorporating FCBS with various lengths (2, 4, and 8 carbon atoms in thioalkyl segments). Unlike common studies on so-called side-chain engineering, where longer side chains would lead to better solubility of those resulting polymers, in this work, we observe that the solubilities and the resulting photovoltaic/mechanical properties are optimized by a proper FCBS length (i.e., C2) in P A named PYTS-C2. Its all-PSC achieves a high efficiency of 11.37%, and excellent mechanical robustness with a crack onset strain of 12.39%, significantly superior to those of the other P As. These results firstly demonstrate the effects of FCBS lengths on the PV performance and mechanical properties of the all-PSCs, providing an effective strategy to fine-tune the structures of P As for highly efficient and mechanically robust PSCs.

The dimerization of small molecule acceptors (SMAs) is a promising strategy for enhancing the long‐term stability and power conversion efficiency (PCE) of organic solar cells (OSCs). However, the reported DSMAs are primarily limited to end‐linked molecular configurations, highlighting the need for further exploration of various dimer architectures. Herein, the development of two distinct core‐linked dimerized SMAs (DYF‐V and DYF‐E) are reported with tailored linker structures (vinylene and ethynyl, respectively), achieving high‐performance OSCs (PCE = 18.53%). Interestingly, a subtle change in the linker structures results in markedly different molecular properties and photovoltaic performances of the dimer acceptors. DYF‐E with an ethynyl linker exhibits more twisted backbone conformation and mitigated aggregation property compared to DYF‐V, inducing desirable blend morphologies with a polymer donor including high crystallinity, face‐on oriented packing structures, and well‐intermixed domains. Thus, the DYF‐E‐based OSCs exhibit a high PCE (17.02%), which significantly outperforms the DYF‐V‐based OSCs (PCE = 9.98%). Furthermore, the ternary OSCs based on DYF‐E achieve a higher PCE of 18.53%. Thus, this study highlights the significance of selecting an appropriate linker in core‐linked dimerized SMAs for producing high‐performance OSCs. [ABSTRACT FROM AUTHOR]

Coastal erosion poses a significant threat to the infrastructure of the coastal community at the mouth of the Ma River in Thanh Hoa Province, Vietnam. In response, emergency solutions such as hard, protective structures are often implemented. However, this approach exacerbates the problem as the underlying mechanisms of coastal erosion are not adequately investigated and understood. In this study, the long-term configuration of the mouth of the Ma River in Thanh Hoa Province, Central Vietnam, is investigated using Landsat imagery spanning from 1987 to 2023. An analytical solution of a one-line model for shoreline change was also used to examine the sand discharge from the Ma River and the diffusion coefficient for the sand transported along the shore by breaking waves. The results showed an asymmetric configuration of the mouth of the Ma River over the past 37 years. The supply of sand from the Ma River is around 350,000 m3/year. The majority of sand (ranging from 55% to 75%) is mainly transported to the northern beach of the Ma River delta. This uneven distribution of sand from the Ma River has led to the asymmetrical morphology of the delta apex in which the northern part of the Ma River delta is experiencing northward movement while the southern part of the Ma River Delta is moving southward and landward. The asymmetrical morphology of the delta at the mouth of the Ma River has recently been identified as the cause of severe coastal erosion. The diffusion coefficient value determined for the transportation of longshore sand along the deltaic lobes of the Ma River delta corresponds to 90 m2/day. This study offers a practical method for investigating morphological changes in cuspate deltas, especially when measured field data are limited.

To fabricate high‐performance organic solar cells (OSCs) by green solvent processing, it is essential to control the aggregation behavior and processability of constituent small‐molecule acceptors (SMAs). Herein, a series of SMAs (A1–A4) with enhanced aggregation behavior and processability is developed by replacing the linear alkyl outer side chains of BTP‐eC9 with 2D functional groups. The PM6:A1 SMA blend exhibits appropriate crystallinity, favorable blend morphology, superior electrical properties, and affords an OSC with a high power conversion efficiency (PCE) of 16.8%. Importantly, the OSC is fabricated using a nonhalogenated solvent (ortho‐xylene), annealing‐free process. In contrast, the reference PM6:BTP‐eC9‐based OSC exhibits a lower PCE of 15.3%. Structural analyses reveal that the 2D outer side chains of A1 induce steric hindrance between its dithienothiophen[3,2‐b]‐pyrrolobenzothiadiazole (BTP) core and the 2‐(3‐oxo‐2,3‐dihydroinden‐1‐ylidene)malononitrile end groups, optimizing its molecular planarity and aggregation property. It is further found that the SMAs with chlorinated IC end groups afford OSCs with higher PCEs than SMAs with fluorinated end groups.

The global demand for energy has been steadily increasing due to population growth, urbanization, and industrialization. Numerous researchers worldwide are striving to create precise forecasting models for predicting energy consumption to manage supply and demand effectively. In this research, a time-series forecasting model based on multivariate multilayered long short-term memory (LSTM) is proposed for forecasting energy consumption and tested using data obtained from commercial buildings in Melbourne, Australia: the Advanced Technologies Center, Advanced Manufacturing and Design Center, and Knox Innovation, Opportunity, and Sustainability Center buildings. This research specifically identifies the best forecasting method for subtropical conditions and evaluates its performance by comparing it with the most commonly used methods at present, including LSTM, bidirectional LSTM, and linear regression. The proposed multivariate, multilayered LSTM model was assessed by comparing mean average error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values with and without labeled time. Results indicate that the proposed model exhibits optimal performance with improved precision and accuracy. Specifically, the proposed LSTM model achieved a decrease in MAE of 30%, RMSE of 25%, and MAPE of 20% compared with the LSTM method. Moreover, it outperformed the bidirectional LSTM method with a reduction in MAE of 10%, RMSE of 20%, and MAPE of 18%. Furthermore, the proposed model surpassed linear regression with a decrease in MAE by 2%, RMSE by 7%, and MAPE by 10%.These findings highlight the significant performance increase achieved by the proposed multivariate multilayered LSTM model in energy consumption forecasting.

High power conversion efficiency (PCE) and long‐term stability are prerequisites for commercialization of organic solar cells (OSCs). Herein, two dimer acceptors (DYTVT and DYTCVT) are developed with different properties through linker engineering, and study their effects as alloy‐like acceptors on the photovoltaic performance and photostability of OSCs. These ternary OSCs effectively combine the advantages of both dimer acceptors. DYTVT, characterized by its high backbone planarity, ensures elevated electron mobility and high glass‐transition temperature (Tg), leading to efficient charge transport and enhanced photostability of OSCs. Conversely, DYTCVT, with its significant dipole moment and electrostatic potential, enhances compatibility of the alloy acceptors with donors and refines the blend morphology, facilitating efficient charge generation in OSCs. Consequently, D18:DYTVT:DYTCVT OSCs exhibit higher PCE (18.4%) compared to D18:MYT (monomer acceptor, PCE = 16.5%), D18:DYTVT (PCE = 17.4%), and D18:DYTCVT (PCE = 17.0%) OSCs. Furthermore, owing to higher Tg of alloy acceptors (133 °C) than MYT (Tg = 80 °C) and DYTCVT (Tg = 120 °C), D18:DYTVT:DYTCVT OSCs have significantly higher photostability (t80% lifetime = 4250 h under 1‐sun illumination) compared to D18:MYT (t80% lifetime = 40 h) and D18:DYTCVT OSCs (t80% lifetime = 2910 h). [ABSTRACT FROM AUTHOR]

Nowadays, the demand for high-precision devices is becoming more intense, thanks to the growing complexity and sophistication of modern technology and applications, including microscopy, nanomeasurement and analysis instruments. However, challenges arise because environmental factors such as vibration negatively affect their performance. An active vibration isolation system (AVIS) is one of the most recent solutions for that, but the high degree-of-freedom (DoF) nature results in it strongly suffering from unwanted interactions. Hence, in this paper, a robust decoupling controller is designed to handle the mentioned disadvantages. The system model is first presented, followed by the proposed decoupling techniques, and then, a feedback controller is designed by applying the mixed-sensitivity H ∞ control framework. Experimental studies are conducted to investigate the effectiveness of the proposed AVIS and compare it with other systems, namely, a passive vibration isolation system, a proportional–derivative (PD)-controlled AVIS, and a robust controlled AVIS. The robustness and decoupling performance of the proposed controller are guaranteed by suppressing external vibrations and isolating interactions, and, therefore, stabilizing the system. [ABSTRACT FROM AUTHOR]

The digitalization of the global landscape of electricity consumption, combined with the impact of the pandemic and the implementation of lockdown measures, has required the development of a precise forecast of energy consumption to optimize the management of energy resources, particularly in pandemic contexts. To address this, this research introduces a novel forecasting model, the robust multivariate multilayered long- and short-term memory model with knowledge injection ( Robust - mv - M - LSTM - CI ), to improve the accuracy of forecasting models under uncertain conditions. This innovative model extends the capabilities of mv - M - LSTM - CI by incorporating an additional branch to extract energy consumption from adversarial noise. The experiment results show that Robust - mv - M - LSTM - CI demonstrates substantial improvements over mv - M - LSTM - CI and other models with adversarial training: multivariate multilayered long short-term memory (adv-M-LSTM), long short-term memory (adv-LSTM), bidirectional long short-term memory (adv-Bi-LSTM), and linear regression (adv-LR). The maximum noise level from the adversarial examples is 0.005. On average, across three datasets, the proposed model improves about 24.01% in mean percentage absolute error (MPAE), 18.43% in normalized root mean square error (NRMSE), and 8.53% in R 2 over mv - M - LSTM - CI . In addition, the proposed model outperforms "adv-" models with MPAE improvements ranging from 35.74% to 89.80% across the datasets. In terms of NRMSE, improvements range from 36.76% to 80.00%. Furthermore, Robust - mv - M - LSTM - CI achieves remarkable improvements in the R 2 score, ranging from 17.35% to 119.63%. The results indicate that the proposed model enhances overall accuracy while effectively mitigating the potential reduction in accuracy often associated with adversarial training models. By incorporating adversarial noise and COVID-19 case data, the proposed model demonstrates improved accuracy and robustness in forecasting energy consumption under uncertain conditions. This enhanced predictive capability will enable energy managers and policymakers to better anticipate and respond to fluctuations in energy demand during pandemics, ensuring more resilient and efficient energy systems. [ABSTRACT FROM AUTHOR]

In many countries, motorcycles have become a primary and popular mode of transportation, driven by increasing demand due to their convenience. However, as fossil fuel sources deplete, there's a pressing need to enhance engine performance, efficiency, fuel economy, and reduce emissions. Improving ignition systems is crucial in achieving these goals. This study compares the performance of the Honda Future FI 125cc engine between a laser ignition system (LIS) and a conventional ignition system (CIS) using simulation. CATIA software was utilized to design the engine's intake manifold, ANSYS Fluent software for simulating and determining the optimal swirl and tumble ratio, and Matlab/Simulink for modeling and simulating engine performance with both LIS and CIS. Detailed discussions and comparisons were made on parameters such as cylinder air mass, ignition energy, engine power and torque, specific fuel consumption (SFC), and mass fraction burned (MFB) between LIS and CIS. Overall, LIS demonstrated superior engine performance compared to CIS. This finding is significant for evaluating the advantages of LIS in motorcycles, especially in the Honda Future FI 125cc engine. [ABSTRACT FROM AUTHOR]

High power conversion efficiency (PCE), eco-friendly processing, and long-term stability are essential for the commercialization of polymer solar cells (PSCs). In this study, we develop PM6-based terpolymer donors (PM6-DTzBX, where X = 5-20), by substituting the benzodithiophene-dione (BDD) unit with the benzobisthiazole (DTzB) unit, which aims to tune the crystalline properties of the polymers as well as achieving a blend morphology with sufficient intermixed domains. The DTzB-incorporating polymer donors (PDs) demonstrate stronger intermolecular interactions with a Y6-BO small molecule acceptor (SMA) and exhibit more pronounced crystalline properties than the reference PM6 PD. Consequently, PM6-DTzB10 PD-based PSCs achieve a higher PCE of 16.8% compared to that of PM6-based PSCs (15.6%) when processed in a non-halogenated ortho-xylene solvent. Furthermore, under thermal stress at 100 °C for 100 h, PM6-DTzB10-based PSCs maintain 88% of the initial PCE and exhibit enhanced thermal stability compared to PM6-based PSCs, which retain 72% of the initial PCE. Additionally, the PM6-DTzB10:Y6-BO blend films demonstrate a 7-fold increase in stretchability with a crack onset strain (COS) of 11.7%, compared to the PM6:Y6-BO blend films (COS = 1.7%). These enhancements in the PCE, thermal stability, and mechanical robustness can be mainly ascribed to the formation of a wellintermixed PD:SMA blend morphology and enhanced crystalline properties of PM6-DTzB PDs. This study highlights the potential of the terpolymer strategy in developing efficient, thermally stable, and mechanically robust PSCs. [ABSTRACT FROM AUTHOR]