Coherent two-dimensional micro-spectroscopy: An investigation of plasmon propagation

A well-known bottleneck for cutting-edge nano-electronic circuits which enable broadband data-processing, is their miniaturization. In the last decade the opto-electronic approach of using surface plasmon-polaritons [1] became a promising concept to achieve this goal due to the deep subwavelength confinement [2] of electromagnetic fields and their propagation velocity near the speed of light. By combining fs laser pulses with optical or photoemission electron microscopy, several spatio-temporally coupled processes in designed nanostructures could be demonstrated, e.g., coherent control of plasmon propagation in nano-circuits [3] and strong coupling of widely separated nano-antennas [4]. Nano-antennas have the unique ability to channel far-field radiation to sub-wavelength dimensions. The resulting strongly confined and enhanced electromagnetic fields boost nonlinear optical effects at the nanoscale [5]. For this purpose, we introduce coherent two-dimensional (2D) micro-spectroscopy which probes the nonlinear optical response of the nano-antennas with sub-micron spatial resolution [6]. An LCD-based pulse shaper in 4f geometry is used to create collinear trains of 12-fs visible/NIR laser pulses in the focus of a numerical aperture of a 1.4 immersion-oil microscope objective [7]. We motivate this new method for getting nonlinear third-order information of the ultrafast dynamics of plasmon propagation via phase cycling, e.g., for the local spatial investigation of the strong coupling between a transition metal dichalcogen-ide (TMD) monolayers and a nano-antenna on top of it. References [1] M. L. Brongersma et al. “The case for plasmonics”. Science, 328 (5977): 440-441, 2010. [2] J.A. Schuller et al. “Plasmonics for extreme light concentration and manipulation”. Nat. Mater., 9 (3):1 93-204, 2010. [3] C. Rewitz et al. “Coherent Control of Plasmon Propagation in a Nanocircuit”. Phys. Rev. Applied., 1: 014007, 2014. [4] M. Aeschlimann et al. “Cavity-assisted ultrafast long-range periodic energy transfer between plasmonic nanoantennas”. Light-Sci. Appl., 6: e17111, 2017. [5] B. Metzger et al. “Ultrafast Nonlinear Plasmonic Spectroscopy: From Dipole Nanoantennas to Complex Hybrid Plasmonic Structures”. ACS Photonics, 3 (8):1336–1350, 2016 [6] S. Goetz et al. “Coherent two-dimensional fluorescence micro-spectroscopy”. Opt. Express, 26 (4):3915-3925, 2018 [7] M. Pawłowska et al. “Shaping and spatiotemporal characterization of sub-10-fs pulses focused by a high-NA objective”. Opt. Express, (22):31496-31510, 2014</p

Reduced Graphene Oxide/Cellulose Sodium Aerogel-Supported Eutectic Phase Change Material Gel Demonstrating Superior Energy Conversion and Storage Capacity toward High-Performance Personal Thermal Management

By virtue of their capacity to absorb and release energy during the phase change process, phase change materials (PCMs) are ideal for personal thermal management (PTM). The combination of reduced graphene oxide/cellulose sodium aerogel (rGCA) and lauric acid/myristic acid binary eutectic phase change gel (LMG) creates a composite phase change material that possesses outstanding photothermal conversion capabilities, electro-thermal conversion capabilities, energy storage capabilities, and shape-stable performance. The results showed that rGCA had a maximum adsorption efficiency of 99.7% with a melting latent heat of 124.6 J g–1. The high absorption rate of rGCA to LMG is a result of the capillary force, pore characteristics, hydrogen bonding, and the π–π interaction. Notably, rGCA and LMG composite material (rGCG) exhibited an excellent photothermal conversion efficiency of 96.5% and electro-thermal conversion of 82.3%. Results indicate that binary eutectic phase change materials are more suitable for temperature regulation than single phase change materials, making them more suitable for PTM. It is anticipated that the innovative thermal comfort solution, which provides thermal shielding, thermal energy storage, self-supporting characteristics, and wearability, will offer new possibilities for the next generation of wearable PTMs

A Practical Multivariable Control Approach Based on Inverted Decoupling and Decentralized Active Disturbance Rejection Control

Conventional multivariable controls may face challenges in industrial implementation due to their computation intensity, controller complexity, and/or poor robustness. To this end, this paper developed a practical multivariable control method, consisting of inverted decoupling and decentralized active disturbance rejection controller (ADRC). Strong robustness is achieved with negligible computation and simple forms of the decoupler and controller. Moreover, the disturbance rejection is markedly accelerated. On the basis of the two-input–two-output (TITO) system description, first discussed are the practical advantages of inverted decoupling that can be easily extended to high dimensional systems. Particularly, a compensation method is proposed to make the inverted decoupling applicable for the processes with right-half plane zeros. Then, the ADRC is bridged to the PI controller and the internal stability and robustness are analyzed. The feasibility of implementing ADRC in industrial distributed control system (DCS) is verified experimentally. Moreover, the qualitative tuning rules are discussed and packaged as an interactive tool. Also addressed are the compatibility and complementarity of the combination of ADRC and inverted decoupling. Finally, simulation and experimental results demonstrate the efficacy of the proposed method

Table3_A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant.docx

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.</p

Image1_A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant.pdf

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.</p

On Tuning and Practical Implementation of Active Disturbance Rejection Controller: A Case Study from a Regenerative Heater in a 1000 MW Power Plant

Active disturbance rejection controller (ADRC) is emerging as a promising approach to deal with uncertainties, which has received many practical applications in motion controls. This paper discusses the issues that should be taken into account when applying ADRC in process industry. First, the strategies of bumpless transfer and anti-windup are introduced to make ADRC applicable for continuous production processes. Second, an automatic tuning tool, based on robust loop shaping, is developed to obtain a group of reasonable parameters that can guarantee the system safety when ADRC is put in loop. For robustness concerns, the maximum sensitivity function is introduced in tuning the bandwidth of the extended state observer (ESO). Third, a quantitative retuning strategy is introduced to avoid the proportional kick in set-point tracking. The simulation and laboratory experiments confirm the effectiveness of the proposed strategies. Finally, it is attempted to apply the ADRC controller to a regenerative heater in an in-service 1000 MW power plant. The field test well demonstrates the virtues of ADRC and indicates promising prospects for ADRC in industrial applications

Table2_A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant.docx

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.</p

Table1_A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant.docx

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.</p

Table4_A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant.docx

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants.Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID).Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.</p

Correlated High-Frequency Molecular Motions in Neat Liquid Probed with Ultrafast Overtone Two-Dimensional Infrared Spectroscopy

In this work, an overtone two-dimensional infrared (2D IR) method is shown to allow correlated molecular motions at the frequencies of overtone transitions to be studied. Waiting-time-dependent overtone 2D IR results of the C–O stretching in neat liquid methanol reveal that the autocorrelation of the <i>v</i> = 0 → 2 transition and the cross correlation of the <i>v</i> = 0 → 2/<i>v</i> = 2 → 4 transitions differ considerably (relaxation time being 700 fs and 2 ps, respectively), suggesting different spectral diffusion dynamics. Quantum-chemical computations in combination with ab initio molecular dynamics simulations show that the overtone transition frequency of the C–O stretching mode in liquid methanol is of more structural sensitivity than the fundamental frequency. This work demonstrates a new 2D IR approach to examining the structural sensitivities of the anharmonic potential parameters of higher vibrational states, which can be used to gain new insight into the ultrafast structural dynamics particularly for neat liquids