• 3001-2026

    Raw Material Substitution: High-Quality Petrochemical Development

    At present, China's petrochemical industry is confronted with the dual challenges of global overcapacity and high domestic raw material costs. Particularly, China lacks low-cost raw materials such as associated gas from oil fields and shale gas, which leads to persistently high production costs for core chemical products like ethylene. In 2023, there was a situation where related products in the United States were highly profitable while Chinese enterprises suffered comprehensive losses. How to break this deadlock? The article "Raw Material Substitution Facilitates High-Quality Development of China's Petrochemical Industry" published in the journal "Chemical Industry and Engineering Progress" has pointed out a clear path for us. This article, based on the core viewpoints of the original text, will help you understand the core logic and practical directions of raw material substitution.

  • 1811-2025

    China's Cellulosic Ethanol Development Path Becomes Clearer

    Introduction:With the deepening of the "Dual Carbon" strategy, cellulosic ethanol, as a core direction of second-generation bio-liquid fuels, has regained focus in the energy and chemical industry due to its significant potential in emissions reduction, avoiding competition with food supplies, and waste resource utilization. Through over a decade of technological accumulation and engineering demonstration, China has achieved a series of breakthroughs in core technologies, equipment, and industrial demonstration, moving from the "technology verification" stage to the critical "pre-commercialization" phase.

  • 1011-2025

    Hydrogen-Ammonia Industry Booms: China Leads the Zero-Carbon New Landscape

    As the "green hydrogen-to-ammonia (H2A) - green ammonia-to-hydrogen (A2H)" cycle model proposed in the paper "Research Progress and Prospects of Hydrogen-Ammonia Green Cycle" published in the journal "Chemical Industry Progress" continues to be implemented, China's hydrogen-ammonia green energy industry is experiencing explosive growth. Recently, a series of major developments have emerged one after another: Goldwind Science & Technology plans to invest approximately 18.92 billion yuan in a wind power-to-hydrogen, ammonia and methanol project, the first phase of Envision's Chifeng 1.52 million-ton green ammonia project has been put into production, and Jidian Co., Ltd.'s Da'an green ammonia project has set four global records. These milestones mark that this emerging track, which can solve the problem of hydrogen storage and transportation and promote the decarbonization of traditional industries, has moved from the laboratory to large-scale commercial operation.

  • 2710-2025

    Resource Recovery Pathways for Oily Sludge Treatment

    The efficient and environmentally sound treatment of oily sludge is a critical challenge for the petroleum industry's green transformation. This article systematically reviews the principles and characteristics of mainstream treatment methods, from traditional landfilling and incineration to modern biological and pyrolysis technologies, aiming to provide a clear reference for technology selection within the industry.

  • 1310-2025

    Core Gear: Tackle Solid Waste/High-Viscosity, Boost Industrial Green Shift

    In 2025, with the deepened "dual carbon" policy and upgraded environmental standards, resource utilization of industrial solid waste and harmless treatment of high-viscosity materials have become industry focuses. Per the 2024 White Paper on the Renewable Resources Industry, 32% of SMEs see over 15% raw material loss due to poor sorting accuracy of solid waste equipment, driving urgent demand for high-efficiency, eco-friendly equipment². Against this backdrop, Luoyang Kaizheng Environmental Protection Technology & Equipment Co., Ltd. (hereinafter "Luoyang Kaizheng") offers customized industrial clean production solutions via its three core business segments.

  • 0103-2024

    Good news: Our company has recognized as a "SRDI" enterprise

    Our company has been recognized as a "SRDI Enterprise". We have been focusing on the development of integrated solutions for raw material preparation, batching, solid waste, residual material and recycled material processing. Our goal is to help clients process all kinds of materials more effectively and produce value from them.

  • 0707-2023

    Rotor-Stator Mixers: From Batch to Continuous Mode of Operation—A Review (3)

    Section 6 discussed what this implies when comparing emulsification efficiencies between the two modes of operation. Several different theories have been suggested, but there is of yet no clear consensus in the literature for how continuous mode RSMs should be operated in order to give the same emulsion as in a batch RSM.

  • 3006-2023

    Rotor-Stator Mixers: From Batch to Continuous Mode of Operation—A Review (2)

    This review summarizes and critically compares the current understanding of differences between these two operating modes, focusing on shaft power draw, pumping power, efficiency in producing a narrow region of high intensity turbulence, and implications for product quality differences when transitioning from batch to continuous rotor-stator mixers.

  • 1606-2023

    Rotor-Stator Mixers: From Batch to Continuous Mode of Operation—A Review (1)

    Although continuous production processes are often desired, many processing industries still work in batch mode due to technical limitations. Transitioning to continuous production requires an in-depth understanding of how each unit operation is affected by the shift. This contribution reviews the scientific understanding of similarities and differences between emulsification in turbulent rotor-stator mixers (also known as high-speed mixers) operated in batch and continuous mode.

  • 2605-2023

    Mixing Performance Prediction of Detergent Mixing Process Based on the Discrete Element Method and Machine Learning (2)

    After validating it with experimental test, this model was utilized to study the mixing performance considering the allowable mass fraction range of every formulation component and a mixer speed of 45 rpm, and the dataset generated from this study was employed along with a machine learning algorithm to obtain a model to predict the mixing index. In this sense, twenty-five different combinations of the defined components were simulated and a mixing index of 0.98–0.99 was obtained in a time of 60 s, revealing that all the combinations were completely mixed. In addition, the developed model was validated with results obtained from the DEM model. The model predicts the mixing index in advance and with accuracy.

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