High Flexibility Research Articles

DEVELOPMENT OF HIGH-PERFORMANCE THERMOELECTRIC POLYMERS VIA DOPING OR DEDOPING ENGINEERING.

It is of great significance to develop high-performance thermoelectric (TE) materials, because they can be used to harvest waste heat into electricity and there is abundant waste heat on earth. The conventional TE materials are inorganic semimetals or semiconductors like Bi2Te3 and its derivatives. However, they have problems of high cost, scare/toxic elements, high thermal conductivity, and poor mechanical flexibility. Organic TE materials emerged as the next-generation TE materials because of their merits including solution processability, low cost, abundant element, low intrinsic thermal conductivity, and high mechanical flexibility. Organic TE materials are mainly conducting polymers because of their high conductivity. Both the conductivity and Seebeck coefficient depend on the doping level, and they are interdependent. Hence, the TE properties of polymers can be improved through doping/dedoping engineering. There are three types of doping forms, oxidative (or reductive) doping, protonic acid doping, and charge transfer doping. Accordingly, they can be dedoped by different approaches. In this article, we review the methods to dope and dedope p-type and n-type TE polymers and the combination of doping and dedoping to optimize their TE properties. Secondary doping is also covered, since it can significantly enhance the conductivity of some TE polymers.

Analytical Modeling and Validation of New Prismatic Compliant Joints Based on Zero Poisson’s Ratio Lattice Structures

Abstract The design and analysis of prismatic compliant joints have received less attention compared to that given to revolute compliant joints, thus limiting their implementation in compliant mechanisms beyond translational stages. Lattice structures have been used effectively to increase flexibility and stiffness ratios in compliant joints. Considering these, new prismatic compliant joints based on zero Poisson’s ratio lattice structures (ZP-PCJ) are proposed. Lattices with three different cell arrangements are considered: single cells, 2×2, and 3×3 lattices. Additionally, unit cells with three different geometries are studied: triangular, chamfer, and cosine. The compliance matrices of the ZP-PCJs are assembled analytically using Castigliano’s second theorem and compliance series–parallel simplification. The compliance ratios along the three orthogonal axes of the ZP-PCJs are computed varying their geometric parameters. Finite element models are constructed to validate the analytical results. Experimental tests are performed on additively manufactured ZP-PCJs to corroborate the compliance coefficients. Results showed that analytical models can predict the ZP-PCJ’s elastic properties accurately, differences less than 3% and 12% were obtained when compared to computational and experiments, respectively. Based on the compliance ratios obtained, the ZP-PCJs are suitable for two-dimensional applications. Finally, the ZP-PCJs are implemented in a compliant mechanism to evaluate their behavior, analytically and computationally. The ZP-PCJs have advantages such as eliminating axis drift and high flexibility in motion-direction while maintaining stiffness in other directions. The differences observed when comparing the analytically obtained estimations with simulations and experimental data suggest that ZP-PCJ analytical models are reliable for estimating their performance in compliant systems.

Estimation of wind load on supertall buildings using partial output measurements

Supertall buildings possess distinctive characteristics such as high flexibility, low damping, and susceptibility to wind. The impact of the wind load and wind-induced responses plays a critical role in ensuring the safety and functionality of these structures. Consequently, investigating the wind load and wind-induced responses of supertall buildings has immense practical significance and engineering value to guarantee the secure operation of such buildings under strong wind conditions. However, the direct measurement of wind loads and wind-induced responses across all building floors presents substantial challenges, including considerable engineering workload and implementation difficulties. This study proposes a novel approach based on Kalman filtering to estimate wind loads and wind-induced responses in supertall buildings. This approach involves fusing partial acceleration and displacement measurements to estimate wind load and wind-induced response accurately. Additionally, optimized sensor placement was considered based on the iterative process of the effective independence method. Wind-induced responses were obtained through numerical testing and subsequently utilized to estimate the wind loads on a supertall building. Various factors, such as measurement noise, modeling errors of structural dynamic properties, sensor placement, and response synchronization, were thoroughly discussed to assess their impact on the overall analysis.

Harnessing leather waste in polymer matrix for sustainable smart shape‐stable phase change materials

AbstractThe utilization of leather waste (LW) in a polyurethane (PU) matrix makes a smart and novel shape stable phase change material (SSPCM). This is essential for sustainability as it reduces landfill waste after use. The PU is synthesized in bulk with a 90% yield, using biodegradable polycaprolactone diol and bio‐based polyol (castor oil), along with tolylene‐2,4‐diisocyanate. PL and PLG composites are prepared by blending of constituent components PU (P), LW (L), and poly(glycidyl methacrylate) (PGMA, G), as specified by their code names. Role of LW (hydrogen bonding and chemical crosslinking) and morphology are elucidated by FTIR and SEM, respectively. Self‐healing time (2 h), shape fixity ratios (Rf) (PL: 60–80% and PLG: 60–70%) and shape recovery ratios (Rr) (100% for both) are determined at 60°C. PLG displays faster shape recovery in water (<30 s) compared to air (>300 s). Shape stability and thermal properties of the SSPCM are examined using the temperature responsive leakage study, TGA, and DSC. This research introduces a new approach for using leather waste (LW) in SSPCM, with self‐healing and 100% Rr. This material may find application where SSPCM with high durability and flexibility is essential such as textile and footwear materials.

Machine Learning Prediction and Evaluation for Structural Damage Comfort of Suspension Footbridge

To investigate the impact of structural damages on the comfort level of suspension footbridges under human-induced vibrations, this study addresses the limitations of traditional manual testing, which often entails significant manpower and material resources. The aim is to achieve rapid estimation and health monitoring of comfort levels during bridge operation. To accomplish this, the study combines finite-element simulation results to establish a data-driven library and introduces three distinct machine learning algorithms. Through comparative analysis, a machine learning-based method is proposed for quick evaluation of bridge comfort levels. Focusing on the Yangjiadong Suspension Bridge, the study evaluates and researches the comfort level of the structure under the influence of human-induced vibrations. The findings revealed a relatively low base frequency and high flexibility. Additionally, when considering the mass of individuals, peak acceleration decreased. The predictive performance of the Artificial Neural Network (ANN) model was found to be superior when accounting for multi-parameter damages, yielding root mean square error (RMSE), mean absolute percentage error (MAPE), and R-squared (R2) values of 0.03, 0.02, and 0.98, respectively. Moreover, the error ratio of the generalization performance analysis was below 5%. Furthermore, the study identified a damage coefficient of 0.13 for the bridge’s main cable, hanger, and steel longitudinal beam. Under a crowd density of 0.5 people per square meter, the predicted peak acceleration was 1.098 m/s2, with a model error of less than 10% compared to the observed value of 1.004 m/s2. These results underscore the model’s effectiveness in swiftly evaluating bridge comfort levels, thereby offering valuable insights for the health monitoring of bridge comfort levels.

Magnetic cobalt metal organic framework for photocatalytic water splitting hydrogen evolution

Using water as a renewable and safe energy source for hydrogen generation has reduced the need to use toxic fossil fuels. Photocatalytic approaches provide a worthy solution to avoid the high expenditure on complicated electrochemical pathways to promote Hydrogen Evolution Reactions. However, several types of photocatalysts including noble metal-based catalysts have already been in use for this purpose, which are generally considered high-cost as well. The present study aims to use the benefits of metal–organic frameworks (MOFs) with semiconductor-like characteristics, highly porous structures and high design flexibility. These properties of MOFs allow more efficient and effective mass transport as well as exposure to light.in this paper, using MOF technology and benefiting from the characteristics of Fe3O4 nanoparticles as catalyst support for more efficient separation of catalyst, we have synthesized a novel composite. Our proposed photocatalyst demonstrates efficient harvest of light in all wavelengths from UV to visible to generate electron/hole pairs suitable for water splitting with a turnover frequency of 0.222 h−1 at ambient conditions without requiring any additives.Graphical abstract

Thermodynamic analysis of liquid air energy storage system integrating LNG cold energy

Liquid air energy storage (LAES) presents a promising solution to effectively manage intermittent renewable energy and optimize power grid peaking. This paper introduces a LAES system integrating LNG cold energy to flexibly manage power peaking, including intermediate energy storage, power generation using organic Rankine cycle, multi-stage direct expansion, and solar energy for heating. Aiming to maximize the electrical round-trip efficiency, a genetic algorithm is employed to optimize the operational parameters of the proposed LAES system. The results indicate that the combined design of cold energy utilization, multi-stage direct expansion and solar heating for proposed LAES system significantly improve the power performance, achieving an energy capacity of 0.125 kWh/kgLNG and an electrical round-trip efficiency of 376.7 %. The exergy losses of heat exchange equipment are far larger than mechanical equipment in the LAES system, so the optimization design of heat exchange equipment is preferred to improve the exergy performance. The proposed system achieves both high efficiency and flexibility and hence contributes to the development of liquid air energy storage systems.

Tailoring hole density and nitriding in graphene membranes for enhanced gas separation and selectivity

Sour gas, containing acidic gases like hydrogen sulfide and carbon dioxide, has a characteristic odor, and toxic effects, and reduces the overall energy content of the gas. Moreover, the presence of these acid gases in water leads to the formation of highly corrosive acid compounds, increasing transportation costs. Membrane technology is widely used for gas separation due to its low energy consumption, ability to operate at ambient temperatures, lightweight and compact equipment, ease of access to all separated phases, and high process flexibility. Computer simulation bridges the gap between microscopic temporal and spatial scales and the macroscopic laboratory environment. Molecular dynamics is a technique for analyzing the physical motion of atoms and molecules. By simulating the interactions between atoms and molecules over time, insights into the dynamic evolution of the system can be obtained. This research investigates the CO2/CH4 separation performance of modified graphene membranes (C3N) using molecular dynamics simulations under various operating conditions. First, cavities with different geometrical shapes and edge atoms were created, and gas separation was examined at 300 K. A cavity with a diameter of 4.9 Å exhibited the highest selectivity (infinity) and a carbon dioxide flux of 365.65 mol/m2·s, while methane molecules were completely blocked. This cavity was selected as the optimal structure. Next, the effects of pressure, and hole density on gas separation were studied. The results showed that the flux is directly proportional to the feed pressure, reaching 503.7845 mol/m2·s at a pressure of 328.0424 atm while maintaining infinite selectivity. Finally, examining the impact of cavity density on the separation process revealed that drilling four holes in the membrane area was the optimal density, achieving infinite selectivity, zero methane flux, and a carbon dioxide flux of 292.601 mol/m2·s.

RFX-mod2 as a flexible device for reversed-field-pinch and low-field tokamak research

Abstract The RFX-mod2 installation is planned to be completed by 2024 and the start of operations is expected in 2025. The high flexibility of the machine (already tested in the previous RFX-mod experiment) allows operation in Reversed Field Pinch and tokamak configuration as well as ultra-low q pulses. In this work we present predictive analysis on transport, performances and plasma control in RFX-mod2 in view of the first experimental campaigns.

Aminated nanocellulose-mediated synthesis of polyaniline/nanocellulose hybrid materials for sustainable conductive and supercapacitors nanopapers

Diamine-functionalized cellulose nanocrystals (DamCNCs) prepared by periodate oxidation and reductive amination were used as a scaffold for the in-situ oxidative polymerization of polyaniline (PANI). Unlike unmodified CNCs, the hybrid PANI/DamCNC particles formed a stable colloidal suspension over a large pH domain, PANI particles having nucleated and grown from the nanocrystals. The hybridization of PANI was validated by transmission electron microscopy images, along with Fourier-transform infrared, Raman, and UV–Vis spectra. By taking advantage of the colloidal stability of the PANI/DamCNC nanohybrids, flexible and freestanding thin nanopapers were prepared, with different contents in PANI/DamCNCs, using cationic or anionic cellulose nanofibrils (CCNFs or ACNFs, respectively). Conductive nanopapers were obtained by mixing CCNFs with PANI/DamCNCs at a content higher than 20 wt%, exhibiting high flexibility, mechanical integrity, transparency, and stability over time. This work proposes a simple process to fabricate a novel class of biobased conductive hybrid nanofiller based on PANI grafted on DamCNCs, stable in water, that may be used as an additive in nanocellulose suspensions to produce green flexible thin nanopapers, with potential use in different types of electronic devices such as electronic displays, smart packaging, or paper-based supercapacitors for energy storage.

Metal-Halogen Interactions Inducing Phase Separation for Self-Healing and Tough Ionogels with Tunable Thermoelectric Performance.

Ionic liquid-based thermoelectric gels become a compelling candidate for thermoelectric power generation and sensing due to their giant thermopower, good thermal stability, high flexibility, and low-cost production. However, the materials reported to date suffer from canonical trade-offs between self-healing ability, stretchability, strength and ionic conductivity. Herein, we develop a self-healing and tough ionogel (PEO/LiTFSI/EmimCl) with tunable thermoelectric properties by tailoring metal-halogen bonding interactions. Different affinities between polymer matrix and salts are exploited to induce phase separation, resulting in simultaneous enhancement of ionic conductivity and mechanical strength. Molecular dynamics simulations and spectroscopic analyses show that Cl- ions impair the lithium-ether oxygen coordination, leading to changes in chain conformation. The migration difference between cations and anions is thus widened and a transition from n-type to p-type thermoelectric ionogels is realized. Furthermore, the dynamic interactions of metal-ligand coordination and hydrogen bonding yield autonomously self-healing capability, large stretchability (2000%) and environment-friendly recyclability. Benefiting from these fascinating properties, we apply the multifunctional PEO-based ionogels in sensors, supercapacitors, and thermoelectric power generation modules. The strategy of tuning solvation dominance to address the trade-offs in thermoelectric ionogels and optimize their macroscopic properties offers new possibilities for the design of advanced ionogels. This article is protected by copyright. All rights reserved.

Enantioselective synthesis of chiral α,α-dialkyl indoles and related azoles by cobalt-catalyzed hydroalkylation and regioselectivity switch

General, catalytic and enantioselective construction of chiral α,α-dialkyl indoles represents an important yet challenging objective to be developed. Herein we describe a cobalt catalyzed enantioselective anti-Markovnikov alkene hydroalkylation via the remote stereocontrol for the synthesis of α,α-dialkyl indoles and other N-heterocycles. This asymmetric C(sp3)−C(sp3) coupling features high flexibility in introducing a diverse set of alkyl groups at the α-position of chiral N-heterocycles. The utility of this methodology has been demonstrated by late-stage functionalization of drug molecules, asymmetric synthesis of bioactive molecules, natural products and functional materials, and identification of a class of molecules exhibiting anti-apoptosis activities in UVB-irradiated HaCaT cells. Ligands play a vital role in controlling the reaction regioselectivity. Changing the ligand from bi-dentate L6 to tridentate L12 enables CoH-catalyzed Markovnikov hydroalkylation. Mechanistic studies disclose that the anti-Markovnikov hydroalkylation involves a migratory insertion process while the Markovnikov hydroalkylation involves a MHAT process.

Design of a Hand-held Multi-fire Clip Applier with Multiple Dofs for Minimally Invasive Surgery

Abstract Hemorrhage can lead to shock and even death of patients, making one of the main risks in surgical procedures. With the increasing complexity of bleeding during surgical procedures, there is a growing demand for the clip appliers with more functions. However, most traditional clip appliers are rigid, have limited flexibility, and can only fire a single clip within each insertion, which cannot meet the needs of surgeons to efficiently and flexibly control bleeding vessels. In this study, a novel hand-held Hem-o-lok clip applier is proposed, which is designed to have a high flexibility and allow multiple fires of clips. The wrist at the end-effector consists of discrete joints and a flexible shaft, allowing bending in two directions. The tong head at the end-effector enables multiple fires of hemostats, and can be delivered to different positions for clamping blood vessels and human tissues. And it also can be driven to rotate by the flexible shaft. Additionally, an ergonomic handle is designed to control the multi-degree-of-freedom movements of the instrument tip. Finally, the effectiveness of the entire system is evaluated through performance experiments. The design method of this paper can also provide theoretical guidance for other hand-held surgical instruments.

Terahertz wave radiation simulation in the Fe thin film*

Femtosecond laser (FL) induced terahertz (THz) source is a new type of THz source based on injecting FL beams into ferromagnetic thin films by nonlinear effects to generate THz wave. It has a wider bandwidth compared to the traditional THz source, which provides higher flexibility and tunability in the application. In this paper, the three-temperature model and the stochastic Landau Lifshitz Gilbert equation at the atomic level are applied to simulate THz wave generation in Fe thin film induced by FL. Simulation results show that under a FL irradiance of 2 J m−2, the maximum demagnetization of the Fe thin film reaches 8.7%. The electromagnetic waves generated completely cover the THz band (0.1–10 THz), which fully satisfied the application requirements of the THz technology, verifying the feasibility of FL inducing the Fe thin film as a THz source. However, when the Fe thin film is overheated, it will be difficult for FL to excite valuable THz waves. Therefore, additional cooling devices are needed to keep the THz source in a workable temperature state, or to use ferromagnetic materials with magnetic moments that can quickly recover to saturation.

Seeding Atomic Silver into Internal Lattice Sites of Transition Metal Oxide for Advanced Electrocatalysis.

Transition metal oxides (TMOs) are widely studied for loading of various catalysts due to their low cost and high structure flexibility. However, the prevailing close-packed nature of most TMOs crystals has restricted the available loading sites to surface only, while their internal bulk lattice remains unactuated due to the inaccessible narrow space that blocks out most key reactants and/or particulate catalysts. Herein, using tunnel-structured MnO2, this study demonstrates how TMO's internal lattice space can be activated as extra loading sites for atomic Ag in addition to the conventional surface-only loading, via which a dual-form Ag catalyst within MnO2 skeleton is established. In this design, not only faceted Ag nanoparticles are confined onto MnO2 surface by coherent lattice-sharing, Ag atomic strings are also seeded deep into the sub-nanoscale MnO2 tunnel lattice, enriching the catalytically active sites. Tested for electrochemical CO2 reduction reaction (eCO2RR), such dual-form catalyst exhibits a high Faradaic efficiency (94%), yield (67.3mol g-1 h-1) and durability (≈48h) for CO production, exceeding commercial Ag nanoparticles and most Ag-based electrocatalysts. Theoretical calculations further reveal the concurrent effect of such dual-form catalyst featuring facet-dependent eCO2RR for Ag nanoparticles and lattice-confined eCO2RR for Ag atomic strings, inspiring the future design of catalyst-substrate configuration.

Urbanization does not increase ‘object curiosity’ in vervet monkeys, but semi-urban individuals selectively explore food related anthropogenic items

Abstract Urban environments expose animals to abundant anthropogenic materials and foods that facilitate foraging innovations in species with opportunistic diets and high behavioural flexibility. Neophilia and exploration tendency are believed to be important behavioural traits for animals thriving in urban environments. Vervet monkeys (Chlorocebus pygerythrus) are one of few primate species that have successfully adapted to urban environments, thus making them an ideal species to study these traits. Using a within-species cross-habitat approach, we compared neophilia and exploration of novel objects (jointly referred to as ‘object curiosity’) between semi-urban, wild, and captive monkeys to shed light on the cognitive traits facilitating urban living. To measure ‘object curiosity’, we exposed monkeys to various types of novel stimuli and compared their approaches and explorative behaviour. Our results revealed differences in the number of approaches and explorative behaviour towards novel stimuli between the habitat types considered. Captive vervet monkeys were significantly more explorative than both semi- urban and wild troops, suggesting that positive experiences with humans and lack of predation, rather than exposure to human materials per se, influence object curiosity. Across habitats, juvenile males were the most explorative age-sex class. This is likely due to males being the dispersing sex and juveniles being more motivated to learn about their environment. Additionally, we found that items potentially associated with human food, elicited stronger explorative responses in semi-urban monkeys than non-food related objects, suggesting that their motivation to explore might be driven by “anthrophilia” i.e., their experience of rewarding foraging on similar anthropogenic food sources. We conclude that varying levels of exposure to humans, predation and pre-exposure to human food packaging explain variation in ‘object curiosity’ in our sample of vervet monkeys.

Hybrid Multiple Access Techniques Performance Analysis Of Dynamic Resource Allocation

The Non-Orthogonal Multiple Access (NOMA) and the Orthogonal Frequency Division Multiple Access (OFDMA) are promising techniques for next-generation wireless systems. Although much attention in the literature considered these techniques, an effective combination between such systems as hybrid multiple access (HMA) needs more attention. For this reason, this paper devotes to proposing two different scenarios of HMA using multi-user OFDM (MU-OFDM) and power domain (PD) NOMA for downlink transmission to overcome the limitations of both Orthogonal Multiple Access (OMA) and NOMA. Due to the randomness of a wireless channel, different user grouping strategies and dynamic power allocation (DPA) strategies are employed to satisfy users’ requirements. The proposed systems give high flexibility utilizing bitrate allocation and user fairness. System results show superior performance to traditional OMA and NOMA systems. The achieved variety of fairness is helpful for the diversity of applications which is a principal requirement for beyond-fifth-generation (B5G) networks. The next step in this analysis is to enhance the proposed systems’ spectral efficiency (SE) by introducing beamforming for massive Multiple-Input Multiple-Output (MIMO) systems. The bit error rate (BER) result of the proposed system achieves almost the same error floor with a benefit of approximately 10 dB signalto-noise ratio (SNR) when 90 resource blocks (RBs) are used.  

Highly Flexible and Superelastic Graphene Nanofibrous Aerogels for Intelligent Sign Language.

Highly flexible and superelastic aerogels at large deformation have become urgent mechanical demands in practical uses, but both properties are usually exclusive. Here a trans-scale porosity design is proposed in graphene nanofibrous aerogels (GNFAs) to break the trade-off between high flexibility and superelasticity. The resulting GNFAs can completely recover after 1000 fatigue cycles at 60% folding strain, and notably maintain excellent structural integrity after 10000 cycles at 90% compressive strain, outperforming most of the reported aerogels. The mechanical robustness is demonstrated to be derived from the trans-scale porous structure, which is composed of hyperbolic micropores and porous nanofibers to enable the large elastic deformation capability. It is further revealed that flexible and superelastic GNFAs exhibit high sensitivity and ultrastability as an electrical sensors to detect tension and flexion deformation. As proof, The GNFA sensor is implemented onto a human finger and achieves the intelligent recognition of sign language with high accuracy by multi-layer artificial neural network. This study proposes a highly flexible and elastic graphene aerogel for wearable human-machine interfaces in sensor technology.

Chaos generation of superconducting quantum bits coupled with LC resonant circuits

Abstract The dynamics of chaos have been widely used in nonlinear science, such as neural networks, extreme event statistics, and the biophysics of chaos self-organization. Superconducting qubits are artificial atoms based on the Josephson junction structure of nonlinear superconducting devices, offering high design flexibility and ease of coupling and control. In this paper, the generation of chaos through the coupling between superconducting qubits and LC resonant circuits is investigated. By varying the ratio of Josephson energy to charge energy, the coupling coefficient, and the energy of the external driving field, the generation and control of chaos within the system are numerically analyzed. This study provides theoretical support for parameter selection ensuring the confidentiality and fidelity of quantum information transmission based on the chaotic dynamics of superconducting qubits.

Stretch Goals and Radical Creativity: Cognitive Flexibility as a Key Contingency

Abstract Although some organizations encourage employees to generate radical ideas by implementing stretch goals, the relationship between stretch goals and radical creativity is complicated. Unfortunately, existing research has not adequately addressed this issue. Therefore, we integrate signaling theory with creativity-related research and propose that the interaction between stretch goals and cognitive flexibility predicts employees' willingness to take risks, thereby influencing their engagement in radical creative activities and ultimately affecting their radical creativity. To test our hypotheses, we conduct two empirical studies. The results suggest that, for employees with high cognitive flexibility, stretch goals increase their willingness to assume risks, thus leading to improved engagement in radical creative activities and enhancing their radical creativity. Conversely, for employees with low cognitive flexibility, stretch goals decrease their willingness to take risks, which hampers their engagement in radical creative activities and their radical creativity. The theoretical contributions and practical implications of this study are also discussed.