Flexible Conversion Research Articles

Flexible switchable mid-infrared metalens optical tweezer based on VO2

Metasurface has developed rapidly since its advent because of its powerful control over electromagnetic waves, but most traditional metasurface can only passively realize a single fixed function, which limits its application and development in integrated systems. To modulate electromagnetic waves more flexibly and efficiently, here, we first propose what we believe to be a novel scheme to design a switchable metalens by utilizing the phase change materials VO2 and double-layer metasurface modulation. The metalens designed by the proposed scheme can achieve flexible conversion between the transmitted focusing and reflected focusing through changing the phase state of VO2. Then, we investigate the optical force phenomenon of these metalenses, the simulation results indicating that the proposed switchable metalens can achieve stable particle manipulation under both the transmission and reflection modes. This makes it a promising device in flexible optical manipulation, and this reversible tuning will also show significant application potentials in biology, medicine, optical communication and other fields.

Two-stage low-carbon economic dispatch of an integrated energy system considering flexible decoupling of electricity and heat on sides of source and load

Under the goal of "double carbon", in order to further enhance the level of new energy consumption and solve the problem of restricting the flexibility of the system by "ordering power by heat" of combined heat and power (CHP) units, a low-carbon economic planning strategy with flexible decoupling of electricity and heat is proposed, by introducing a new type of electric-thermal coupling equipment on both sides of the source and load. Firstly, Consideration of the low-carbon and environmentally friendly characteristics of green ammonia production and ammonia-doped combustion technologies, a wind power(WT) – power to ammonia(P2A) - CHP units - thermal power (TH) units joint operation strategy is proposed on the source side. This strategy realizes the conversion of abandoned wind to green ammonia to ammonia coal hybrid generation, the decoupled operation of CHP units and promotes the consumption of wind power and the low-carbon operation of the system. Secondly, A dynamic incentive demand response model is developed to meet the demand of high proportion distributed PV in situ consumption on the load side. The dynamic incentive price guides the distributed power-to-heat load to change the response capacity, tracks the abandonment of wind and light, realizes the flexible conversion of power and heat load, and cooperates with the source side to promote the coupling operation of electric pyrolysis. On this basis, consider the flexible decoupling capability of electric-heat coupling equipment on both sides of the source and load to establish a two-phase low-carbon scheduling model for the day-before and day-after phases. In the day-ahead phase, the source-side electric-thermal-ammonia joint operation strategy is considered, and the electric and thermal energy supply plans are adjusted centrally; In the intra-day phase, the flexible adjustment range of power-to-heat devices and the heat load inertia on the load side are taken into account, and the electricity and heat planning strategies are adjusted in a distributed-centralised manner in conjunction with the source side. Finally, through the simulation of different cases, the results show that compared with the traditional electric heating system, the total cost of the system considering the scheduling strategy proposed in this paper decreases by ￥826,900, the carbon emission decreases by 1.2 t, and basically realises the consumption of wind power and distributed photovoltaic power output. The proposed scheme reduces carbon emissions, promotes the consumption of wind power and distributed photovoltaic output, and is able to reach the goal of low-carbon economic dispatch.

Nanofiber Space-Confined Fabrication of High-Performance Perovskite Films for Flexible Conversion of Fluorescence Quantum Yields in LED Applications.

Perovskite is an advanced optoelectronic semiconductor material that has garnered significant attention in recent years. However, its drawback lies in its environmental instability, limiting its practical applications. To tackle this issue, this research delved into the idea of creating a space-confined structure and used electrospinning to produce a film of perovskite nanocomposite fibers. By effectively encapsulating perovskite nanocrystals into a polymer matrix, the perovskite could be shielded from water and oxygen in the environment, thereby reducing the likelihood of perovskite decomposition and enhancing the stability of its structure and properties. This study examined the influence of material composition and the spinning process on the nanofiber structure to create good spatial confinement. This strategy resulted in a high photoluminescence quantum yield of over 80% and a long-term environmental stability of as long as 1000 h over 90% of the original PLQY. By harnessing the flexibility of the composite fibers, this study demonstrated the potential applications and performance of this nanocomposite film in flexible quantum fluorescence conversion for LED applications.

Two-stage optimization model for day-ahead scheduling of electricity- heat microgrids with solid electric thermal storage considering heat flexibility

Traditional electricity-heat microgrid (EHM) is limited in flexibility due to real-time balancing between the supply and demand of electric and heat system. The heat flexibility (HF) can be released by thermal inertia and heat storage characteristics of district heating systems (DHS) and heat storage units, and it can be used to increase the electric power flexibility (EF) of EHM. In this paper, the quantitative relationship between HF and EF is investigated, and a two-stage optimization model for day-ahead scheduling of EHM with solid electric thermal storage (SETS) is established. Firstly, the electric-heat flexibility conversion coefficient (EHFC) is developed to decide the allocation of HF among different electricity-heat coupling units, such as CHP and SETS, and EF supply model of EHM based on HF is built. Secondly, a two-stage optimization model is proposed for day-ahead scheduling of EHM to improve EF and economy of EHM by optimizing the heating power and HF's allocation. Thirdly, the equivalent energy storage of the DHS is quantitatively analyzed, providing a reference for planning and operating of EHM's flexibility resource. Finally, the case study shows that by considering HF and deploying SETS, the total cost can be reduced by 18.8 % and 22.6 %, respectively.

Low-carbon economic scheduling for AIES considering flexible load coordination and multiple uncertainties

The disordered energy use in traditional agricultural production has resulted in high energy purchase costs and carbon emissions. The coupling of integrated energy systems with agriculture offers the potential for flexible coordination of agricultural loads while agricultural loads are highly influenced by changes in the natural environment. In this context, this paper proposes a low-carbon and economic scheduling optimization method for agricultural integrated energy system (AIES), which comprehensively takes temperature, light intensity, and the coordination of agricultural loads into consideration. Firstly, solar and biomass resources are integrated through energy conversion equipment to support energy supply from both the electrical distribution network (EDN) and the gas network. At the same time, the modelling process of agricultural load is refined, which is divided into crop irrigation, greenhouse temperature control and residential consumption. The models of agricultural multi-energy complementary and energy storage equipment are established to achieve flexible conversion between different energy sources. In addition, the distributionally robust optimization (DRO) method based on multiple discrete scenarios is adopted to deal with the uncertainties arising from environmental condition fluctuations during the optimization process. Finally, the proposed model is tested on 4 various regions and 2 different seasons. Numerical results show that the proposed model can effectively enhance the economic and environmental performance of the AIES.

Coexistence of analog and digital memristive behaviors in MoO3 based devices for artificial synaptic and logic display applications

In-memory logic operations and neuromorphic computing inspired by the brain based on memristors are promising computing modes that can improve computational efficiency and avoid additional power consumption. However, implementing these two functions within the memristor same cell is often limited by the flexible conversion between digital and analog memristive behaviors. In this work, a memristive device with Ag/MoO3/Ti structure was developed using hydrothermal methods, which presents the evolution from capacitance-coupled memristive effect to self-rectifying non-zero crossing analog memristive behavior and then to digital memristive effect by adjusting the amplitude of applied voltage. Under low voltage region (Vamplitude ≤ 1.2 V), the non-zero crossing analog memristive effect with self-rectifying behavior is mainly attributed to the potential barrier at the interface and built-in electric field, while the digital memristive effect under high voltage region (Vamplitude ≥ 1.5 V) is mainly attributed to the formation and fracture of Ag conductive filaments (CFs). Moreover, the mechanism for the non-zero-crossing characteristic of device was proven by parallel connection of memristors and capacitors. Finally, the artificial synaptic and logic display functions were implemented using the as-prepared memristive unit. Therefore, this work provided guidance for understanding the non-zero-crossing memristive effect and the development of high-density multifunctional devices.

Magnetic-actuated hydrogel microrobots with multimodal motion and collective behavior.

Magnetic-actuated miniature robots have sparked growing interest owing to their promising potential in biomedical applications, such as noninvasive diagnosis, cargo delivery, and microsurgery. Innovations are required to combine biodegradable materials with flexible mobility to promote the translation of magnetic robots towards in vivo application. This study proposes a biodegradable magnetic hydrogel robot (MHR) with multimodal locomotion and collective behavior through magnetic-assisted fabrication. The MHRs with aligned magnetic chains inside their structures have more significant maximum motion speeds under rotating magnetic fields than the robots without magnetic alignment. By reconfiguring the external magnetic fields, three types of stable motion modes (tumbling, spinning, and wobbling modes) of the individual MHRs can be triggered, while flexible conversion can be achieved between each motion mode. The motion mechanism of each motion mode under diverse rotating magnetic fields has been analyzed. The collective behavior of the MHRs, which is triggered by the magnetic dipole force, can enhance the motion performance and pass through sophisticated terrains. Furthermore, the experimental results demonstrate that the assembled MHRs can execute complicated tasks such as targeted cargo delivery. The proposed MHRs with multimodal locomotion and assembled behavior show effective motion efficiency, flexible maneuverability, and remarkable targeting ability, providing a new choice for magnetic robots in biomedical applications.

Design optimization method of heating and cooling full cycle storage air conditioning in integrated energy system

Heating and cooling storage air conditioning is an important part of the integrated energy system, which can play an important role in the flexible conversion of thermoelectric coupling systems. Because storage air conditioning involves the dynamic characteristics of power supply on the source side and cold and heat demand on the load side, system capacity allocation is a problem of technical and economic optimization. This paper breaks through the traditional design method based on the hourly load distribution law of typical design days and proposes a performance-oriented design method for the bidirectional full-cycle dimension storage air conditioning system based on the system’s annual operation performance, which can take into account the hourly dynamic load distribution law of every day in the full heating season and the full cooling season coupled with the bidirectional demand of cold and heat loads. A more scientific and reasonable capacity configuration scheme for the storage air conditioning system is obtained. The design is presented with a concrete case.

The evaluation of innovation ability of China's information technology application innovation enterprises based on cloud modeling

This paper adopts the theoretical method of the cloud model to establish the evaluation index system. It tests it through examples, and the results show that the cloud model has a flexible conversion function in qualitative description and quantitative expression, and the evaluation results obtained can be visualized through graphs. It is concluded that the evaluation of the technology application innovation industry (ITAI) enterprise's innovation power by using the cloud modeling method can reflect the current level of the ITAI enterprise's innovation power more realistically, which is helpful to find out the innovation path of the ITAI enterprise.

Synthesis-Kinetics of Violet- and Blue-Emitting Perovskite Nanocrystals with High Brightness and Superior Stability toward Flexible Conversion Layer.

The low photoluminescence (PL) efficiency and unstable features of small blue-emitting CsPbX3 nanocrystals (NCs) greatly limit their applications in optoelectronics field. Herein, the synergistic and post-treatment kinetics are studied to create highly bright and anomalous stable violet (peak position of ≈408nm) and blue (peak position of ∼ 466nm) emitting perovskite NCs. Ligand and ion exchange mechanism are systematic studied by the evolution of absorption, PL, and fluorescence lifetime to evaluate ligand bonding, defect engineering, and non-radiative recombination. Didodecyl dimethyl mmonium chloride (DDAC) and CuX2 post-synergistictreatment created DDAC-CsPbCl3-CuCl2 and DDAC-CsPbCl3-CuBr2 NCs that remained the phase composition, morphology, and size of CsPbCl3 NCs. The PL efficiencies are drastically increased to 42 and 85% for violet- and blue-emitting NCs, respectively. The stability test indicated that the NCs enable against various harsh conditions (e.g., ultraviolet light irradiation and heat-treatment). The NCs retained their initial PL efficiency after 2 months under ambient conditions and UV light irradiation. These NCs also exhibited high stability after heat-treatment at 120°C. The emitting NCs embedded in flexible films still revealed bright PL and high stability, suggesting current results provide a new avenue for the application in the field of optoelectronics.

Resource Scheduling Method for Equipment Maintenance Based on Dynamic Pricing Model in Cloud Manufacturing

Cloud manufacturing, as a novel service mode in the manufacturing field with the features of flexible resource assignment, timely service, and quantity-based pricing, has attracted extensive attention in recent years. The cloud manufacturing industry uses a significant amount of smart equipment. In this context, equipment maintenance resource scheduling (EMRS) is an important subject that needs to be studied. Cloud manufacturing platforms must provide effective services for equipment maintenance in a timely manner. In order to improve the efficiency of cloud manufacturing platforms and meet the needs of users, an effective EMRS scheme is required. In this paper, we propose a dynamic resource allocation model for cloud manufacturing to meet the needs of users and maximize the benefit of a cloud manufacturing platform. The model takes into account the needs of users and the benefits of a cloud production platform. The contributions of this paper are divided into the following three aspects. First, the E-CARGO model using role-based collaboration theory is introduced to formally model EMRS activities, forming a solvable optimization model. Second, a dynamic pricing model with a center symmetric curve is designed to realize the flexible conversion between time, cost, and price. Third, the concept of satisfaction in fuzzy mathematics is introduced, in order to meet the different needs of users and platforms, in terms of time, price, and cost, while ensuring service quality and the platform’s benefits. Finally, an improved genetic algorithm is used to solve the cloud manufacturing resource scheduling problem, and good experimental results are obtained. These results demonstrate that the proposed dynamic pricing model is reasonable, and the allocation scheme obtained through a genetic algorithm is feasible and effective.

Biodegradable Magnetic Hydrogel Robot with Multimodal Locomotion for Targeted Cargo Delivery.

Recent strides in the development of untethered miniature robots have shown the advantages of diverse actuation methods, flexible maneuverability, and precise locomotion control, which has made miniature robots attractive for biomedical applications such as drug delivery, minimally invasive surgery, and disease diagnosis. However, biocompatibility and environmental adaptability are among the challenges for further in vivo applications of miniature robots due to the sophisticated physiological environment. Herein, we propose a biodegradable magnetic hydrogel robot (BMHR) that possesses precise locomotion with four stable motion modes, namely tumbling mode, precession mode, spinning-XY mode, and spinning-Z mode. Using a homemade vision-guided magnetic driving system, the BMHR can achieve flexible conversion between the different motion modes to cope with changes in complex environments, and its superior ability to cross obstacles is demonstrated. In addition, the transformation mechanism between different motion modes is analyzed and simulated. Benefiting from the diverse motion modes, the proposed BMHR has promising applications in drug delivery, showing remarkable effectiveness in targeted cargo delivery. The BMHR's biocompatible property, multimodal locomotion, and functionality with drug-loaded particles can provide a new perspective to combine miniature robots with biomedical applications.

Multi compression–expansion process for chemical energy conversion: Transformation of methane to unsaturated hydrocarbons and hydrogen

With the global energy system moving towards renewable energies, there is an increasing demand for flexible conversion processes which can cope with the temporally and locally fluctuating nature of energy supply and energy demand. Promising candidate processes are based on coupled chemical/energy conversion. In this work, the pyrolytic conversion of methane to valuable high-energy content substances like hydrogen and unsaturated hydrocarbons by the compression/expansion process of a piston engine is investigated. In particular, the potential of running this conversion in a multi-compression–expansion (MCE) mode where a gas sample is subject to multiple compression–expansion strokes, is assessed. The methane conversion and target species yields of this multi-compression mode relative to a single compression–expansion mode are assessed. Experimental studies with a rapid compression–expansion machine are used for this. The experiments are complemented by numerical simulations, which help to interpret the experimental findings. We found that both conversion and target species yields can be increased significantly by the multi-compression–expansion processes relative to a single compression–expansion. For instance, at typical engine operation conditions, ten compression–expansion cycles increase the methane conversion by a factor of three to four (from approx. 15 % to 68 %), the hydrogen yield by a factor of five, and the unsaturated hydrocarbon yields by a factor of three, compared to a single compression–expansion process. The results encourage considering a new role for piston-engines as work-to-chemical energy converters, in addition to their conventional heat-engine (chemical energy to work) operation.

An Interlinking Converter for Renewable Energy Integration into Hybrid Grids

With the rise in global warming, distributed generators (DGs) based on renewable energy sources have become increasingly important in the power sector. Due to their small size and the capacity to 'island' while providing most of their loads during situations, microgrids provide an excellent framework to build smart grids, which increases system resilience. Given that renewable-based DGs dominate microgrids and are defined by their statistical properties and unpredictable power, sustaining load-generation balance is a significant challenge. Although microgrids are now widely used and researched, there is still considerable contention over whether they should use alternating current (AC) or direct current (DC), with the majority opinion leaning toward a combination of the two. nIn order to facilitate the flexible incorporation of renewable energy into hybrid grids, this article offers an interlinking converter design. The suggested converter may be configured as a DC-DC converter, a DC-AC inverter, or a DC-DC/AC multiport converter thanks to its one AC port and two DC ports, making it a versatile option for combining multiple DC and AC sources. Flexible conversion, high power density, low leakage currents, and tunable power flow are all features validated by the MATLAB/SIMULINK simulation results, proving the idea.

Solid oxide electrolysis cells – Interplay between operating conditions, fuel electrode overpotential and degradation

With the integration of increased share of energy from renewable, but fluctuating, energy sources there will be an increased demand for large-scale flexible conversion of electrical energy into easily storable chemical fuels. Electrolysis will be a key component in the future of energy conversion and storage solutions. Solid oxide cells (SOC) can provide the most efficient electrolysis technology. Furthermore, solid oxide electrolysis cell (SOEC) technology has improved tremendously in terms of initial performance, long-term durability, and up-scaling of cell and stack sizes; and with respect to commissioning and operation of SOEC plants. Nevertheless, it is evident that further improvement of electrochemical performance and especially long-term durability is crucial for the coming up-scaling and integrated SOEC systems as part of our energy grid. This calls for research within 1) thorough mapping of degradation mechanisms, 2) determination of thresholds for the onset of irreversible degradation processes, 3) safe operating conditions and means to mitigate known degradation processes, etc. However, degradation is not a simple singular property and there is often a puzzling interplay between parameters such as: the chosen electro-catalysts, the manufacturing of cell components, obtained microstructures, the resulting initial electrochemical performance, operating conditions, and the nature and extent of different degradation processes. This work will present11This work has been presented as invited keynote speak at symposium E01.07 as part of the 23rd International Conference on Solid State Ionics, MRS Meeting, Boston (US), July 2022. an overview of the puzzling interplay between initial electrochemical performance and long-term durability. It will then provide examples of multiple complementary characterization techniques applied for the analyses of these features and processes (e.g., SEM, TEM, Raman spectroscopy and electrochemical impedance spectroscopy). Furthermore, strategies to mitigate and/or limit specific degradation processes and insight into data required to establish degradation wise safe operating conditions are discussed. The present work will touch upon multiple performance characteristics and degradation processes: 1) triple-phase-boundaries (TPB) and critical micro/nano-structural parameters of the porous nickel/yttria-stabilized-zirconia (Ni/YSZ) electrode; 2) the perception of electrode overpotential and why this parameter is more important than the set current density or operating cell/stack voltage, 3) the effect of impurities, 4) the interplay between impurities and carbon deposition and 5) the degradation caused by Ni migration and actions to mitigate this degradation process.

Low-carbon economic dispatching of microgrid considering generalized integrated demand response and nonlinear conditions

With the depletion of fossil fuels and the deterioration of the ecological environment, it is crucial to realize the low-carbon economic dispatching of microgrids (MG). In previous studies, the Demand Response (DR) can reduce microgrid operating costs and CO2 emissions by optimizing the load curve, under this background, this paper considers the coupling relationship between electricity, heat, and gas. And by the introduction of Power-to-Gas (P2G) and Organic Rankine Cycles (ORC), the flexible conversion of electricity-gas and heat-electricity is realized. In addition, based on the characteristics of the time-shifting load, interruptible load, and alternative load, the Generalized Integrated Demand Response (GIDR) model is constructed. Secondly, to restore the non-linear status of energy conversion equipment efficiency under different partial loads, this paper adopts data-driven modeling and uses Multilayer Perceptron (MLP) to fit the curves of key parameters, with the help of the Soft Actor–Critic (SAC) algorithm, the solution of the model is realized. In the case study section, this paper verifies the rationality of the proposed method by using real data from Northwest China. The results show that GIDR can reduce the cost by 16.40% and reduce the CO2 emissions by 32.26%, and compared with not considering nonlinear conditions, the method in this paper can reduce the operating cost by 23.16% and carbon emissions by 33.00%.

Theta-phase connectivity between medial prefrontal and posterior areas underlies novel instructions implementation.

Implementing novel instructions is a complex and uniquely human cognitive ability, which requires the rapid and flexible conversion of symbolic content into a format that enables the execution of the instructed behavior. Preparing to implement novel instructions, as opposed to their mere maintenance, involves the activation of the instructed motor plans, and the binding of the action information to the specific context in which this should be executed. Recent evidence and prominent computational models suggest that this efficient configuration of the system might involve a central role of frontal theta oscillations in establishing top-down long-range synchronization between distant and task-relevant brain areas. In the present EEG study (human subjects, 30 females, 4 males), we demonstrate that proactively preparing for the implementation of novels instructions, as opposed to their maintenance, involves a strengthened degree of connectivity in the theta frequency range between medial prefrontal and motor/visual areas. Moreover, we replicated previous results showing oscillatory features associated specifically with implementation demands, and extended on them demonstrating the role of theta oscillations in mediating the effect of task demands on behavioral performance. Taken together, these findings support our hypothesis that the modulation of connectivity patterns between frontal and task-relevant posterior brain areas is a core factor in the emergence of a behavior-guiding format from novel instructions.

One-to-one career conversations in UK higher education: practical approaches and professional challenges

ABSTRACT One-to-one work with students remains at the core of many higher education career services in the UK, but there is limited empirical evidence detailing the nature of these interactions. Drawing together existing strands of literature on the process and effectiveness of one-to-one career conversations, career decision-making difficulties, and career practice training, we report the findings of interviews with 22 career professionals in HE in the UK who were invited to reflect on their one-to-one practice with university students, describe their approaches and techniques and to identify any challenges they face. Through template analysis, we identified three key aspects to the career professionals’ practice: the relationship, the structure of the conversation and specific techniques. The participants described aspects of their practice which diverge from the approaches they were taught during their initial professional training, notably the use of a flexible conversation structure and limited use of career development theories. We identified that the key challenge practitioners reported was feeling that they disappoint some of their clients. We highlight some theoretical implications and offer some recommendations for practitioner training.

Online education satisfaction assessment based on cloud model and fuzzy TOPSIS

During the COVID-19, colleges organized online education on a massive scale. To make better use of online education in the post-epidemic era, this paper conducts an online education satisfaction survey with four types of colleges and 129,325 students propose a fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method based on the cloud model to rank the satisfaction of different colleges. Firstly, based on the characteristics of online education during the COVID-19, we build an evaluation indicator system from four dimensions: technology, instructor, learner and environment including, 10 indicators and 94 sub-indicators. Secondly, the cloud model is used to quantitatively describe the natural language and uncertainty in a large amount of assessment information. The cloud model generator is used for sub-indicators and achieves an effective and flexible conversion between linguistic information and quantitative values. The cloud model of indicators are presented by integrating the corresponding sub-indicators. The weights of indicators are determined by the entropy method based on the cloud model and possibility degree matrix, which eliminates the judgment of decision-makers and has great power for handling practical problems with unknown weight information. Finally, a fuzzy TOPSIS method based on the cloud model is proposed to rank the satisfaction of online education of different colleges. The proposed method is compared with other existing methods to shown its merits. The experimental result is consistent with the proportion of students who accept online education in the post-epidemic era. According to the second questionnaire, as the qualitative evaluation of the cloud model of indicators increases, the qualitative evaluation of satisfaction of different types of colleges will also increase. It indicates that the method proposed in this paper is practical.

Evaluation of the turn‐off transient controllability for high‐power IGBT modules

The efficient and flexible conversion of electrical energy is increasingly accomplished by megawatt insulated gate bipolar transistor (IGBT) modules. Their dynamic performance is influenced by the gate driver control, operating points and the switching loop parasitics, which are crucial to their optimized operational behaviours, efficiency and field reliability. This paper investigates the controllability of the transient voltage and current slopes of megawatt IGBT modules during their turn-off transitions and proposes an efficient assessment method accordingly. Firstly, the causal relationship of transient characteristic variations and controllability is investigated analytically. Then, major factors impacting the controllability are analysed and validated, including the charge carrier profile, the operating points (i.e. the load voltage, the load current, and the junction temperature), and the gate resistance. Finally, an efficient method using the MOS-channel turn-off point on calibrated gate voltage waveform is proposed for the controllability evaluation, which can guide the IGBT, gate driver, and converter design.