Conceptual methods for synthesis of reactive distillation processes: recent developments and perspectives

Reactive distillation (RD) is a process intensification technique that offers major advantages over conventional technologies by enabling the integration of reaction and separation into a single apparatus. This integration introduces and exploits complex interaction between mass transfer, chemical reaction and hydrodynamics within an RD...

Digitally Intensive Frequency Synthesis and Modulation Exploiting a Time-mode Arithmetic Unit

Reducing power consumption is becoming increasingly important for the sustainability of the communication industry because it is expected to consume a significant portion of the global electricity in the face of the exponentially increasing demands on the volume and rate of data transmission. As the scope narrows to the individual wireless...

A Low-Spur Fractional-N PLL Based on a Time-Mode Arithmetic Unit

This article introduces a low-jitter low-spur fractional-N phase-locked loop (PLL) adopting a new concept of a time-mode arithmetic unit (TAU) for phase error extraction. The TAU is a time-signal processor that calculates the weighted sum of input time offsets. It processes two inputs - the period of a digitally controlled oscillator (DCO)...

Investigation on the technical performance and workability of hot-melting road marking materials using for the high-altitude area

The special environment conditions in high altitude areas leads to serious cracking and peeling of road hot-melt marking coatings. In order to improve the durability of marking paint, a durable hot-melt marking paint was designed by modifying the paint with toughening-agent, rheological agent, and anti-aging agent. The modification mechanism...

Transfer learning for process design with reinforcement learning

Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automating process design by integrating data-driven models that learn to build process flowsheets with process...

Improving the strength-ductility balance of medium-Mn Q&P steel by controlling cold-worked ferrite microstructure

The phase transformations, microstructure and properties of two Medium-Mn processed via quenching and partitioning steels were compared in this contribution and a new strategy for controlling mechanical properties by introducing and controlling cold-worked ferrite prior to heat treatment is proposed. It was found that during heating, the...

Nanowire-based integrated photonics for quantum information and quantum sensing

At the core of quantum photonic information processing and sensing, two major building pillars are single-photon emitters and single-photon detectors. In this review, we systematically summarize the working theory, material platform, fabrication process, and game-changing applications enabled by state-of-the-art quantum dots in nanowire...

Flowsheet generation through hierarchical reinforcement learning and graph neural networks

Process synthesis experiences a disruptive transformation accelerated by artificial intelligence. We propose a reinforcement learning algorithm for chemical process design based on a state-of-the-art actor-critic logic. Our proposed algorithm represents chemical processes as graphs and uses graph convolutional neural networks to learn from...

A contactless measuring speed system of belt conveyor based on machine vision and machine learning

During the operation of the belt conveyor, measuring speed of the belt conveyor is vital to the safe and efficient operation. In the existing measuring speed system, the measurement instrument is required contacting with the surface of the belt. The contact measurement method cannot avoid the occurrence of measuring error caused by slipping...