Revolutionizing liquid processing with smart membrane technologies: Automation, AI, and sustainability

About this Research Topic

Background

Membrane technologies lie at the heart of modern separation science, offering scalable, energy-efficient, and high-selectivity solutions for the separation and purification of liquids across a wide array of industries. Beyond their extensive use in water treatment, pharmaceutical production, and food processing, there is a growing impetus to innovate towards sustainability. The latest research in this field is directed not only at enhancing the efficiency and selectivity of membrane processes but also at integrating pioneering automation and artificial intelligence (AI) systems. Such innovations aim to address persistent challenges like membrane fouling and high energy consumption, while also optimizing resource utilization to achieve superior environmental outcomes.

This Research Topic seeks to delve into the ever-evolving landscape of membrane technologies, with a sharp focus on the transformative potential wielded by automation and AI. Key aims of this research include evaluating how AI-driven optimization impacts process efficiency and longevity, as well as understanding how automated systems bolster operational reliability. Other critical focal points are the development of advanced materials that boast enhanced fouling resistance, the integration of machine learning models to forecast process outcomes, and overarching aspirations for sustainability within liquid processing applications. These align tightly with the mission of the Liquid journal to advance liquid processing science, emphasizing innovations and real-world applicability.

To gain deeper insights into the confluence of membrane technologies and smart systems, we invite articles that address, but are not limited to, the following expanded themes:

Smart Membrane Design and Novel Material Development

• Advanced fabrication techniques (e.g., interfacial polymerization, electrospinning) are enabling membranes with enhanced selectivity, permeability, and anti-fouling properties.
Integration of nanomaterials and responsive polymers leads to membranes that can self-regulate or respond to stimuli such as pH, temperature, or pressure changes.
•Self-healing materials are emerging, allowing membranes to repair minor damages autonomously and extend service life.
•AI models assist in predicting material performance during early-stage design, accelerating the development cycle.
•Emphasis on membranes with bio-inspired surfaces to mimic natural filtration functions with higher efficiency.

Automation Strategies in Industrial Applications of Membrane Systems

•Automation enables continuous monitoring and adaptive control, reducing downtime and human intervention.
•Integration with real-time sensors allows systems to automatically adjust flow rate, pressure, and chemical dosing based on dynamic feedwater conditions.
•Deployment of Supervisory Control and Data Acquisition (SCADA) systems and Programmable Logic Controllers (PLCs) enhances precision in process control and data logging. Industrial case studies show that automation reduces operational costs by up to 35% and increases system uptime significantly.
•Digital twins are being developed to simulate operations, predict failures, and optimize design and operation workflows.

AI-Driven Process Optimization and Predictive Maintenance

•Machine learning algorithms are used to predict fouling trends, enabling proactive maintenance scheduling and minimizing membrane degradation.
•AI supports dynamic optimization of backwashing cycles, chemical cleaning schedules, and energy use, improving overall process efficiency.
•Reinforcement learning models enable systems to self-learn and improve operational decisions over time.
•Real-time filtration models powered by AI enhance early fault detection and alarm generation, improving safety and reliability. •Predictive analytics reduce membrane failure and extend membrane lifespan by 20–40%, based on case studies.

Case Studies on the Integration of Membrane Technologies with Internet-of-Things (IoT) and AI

•In real-world systems, embedded sensors and AI algorithms are used to remotely monitor transmembrane pressure, turbidity, and flow metrics.
•Cloud-based platforms enable centralized control of distributed membrane systems, improving data accessibility and system responsiveness.
•IoT frameworks have been implemented in smart cities and public water systems to ensure continuous supply, quality assurance, and leak detection.
•Pilot projects show enhanced data acquisition, visualization, and decision-making using AI-IoT fusion.
•Integration of edge computing with membrane sensors reduces latency and allows real-time on-site decisions.

Innovations in Pore-Based and Electrochemical Membranes for Sustainability

•Pore-engineered membranes with nano-structured channels enhance separation efficiency while reducing energy input.
•Electrochemical membranes support in-situ degradation of contaminants, reducing the need for secondary treatments.
•Designs emphasize recyclable materials and lower environmental impact through reduced chemical use and sludge production.
•Electroactive membranes enable simultaneous separation and pollutant transformation, e.g., breaking down pharmaceuticals or PFAS.
•Smart membranes are being optimized for resource recovery (e.g., nutrients, metals) from wastewater streams, contributing to circular economy goals.

Regulatory and Compliance Challenges in Integrating Advanced Technologies

•Many regulatory frameworks lag behind current AI and IoT advancements, creating uncertainty in implementation.
•AI-assisted compliance tools are being developed to automatically generate environmental reports and audit trails.
•Standards for data security, interoperability, and sensor calibration are needed to support full digital integration in membrane systems.
•Legal concerns include accountability for AI-driven decisions in autonomous system operations.
•Cross-agency collaborations are essential to ensure that innovation and regulatory alignment move forward together.

We invite submissions of Original Research, Review, Mini Review, and Perspective articles. This special issue offers an opportunity for contributors to help shape future sustainable practices and foster collaborations among academia, industry, and technology providers to push the boundaries of membrane technologies.

Frontiers in Membrane Science and Technology is a gold open access journal. All published articles are freely accessible to the global community, ensuring maximum visibility and impact. Authors should be aware that article processing charges apply to cover the costs of publication. Information on APCs, fee support and institutional partnerships, will be provided to authors.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Mini Review
• Original Research
• Perspective
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Mini Review
• Original Research
• Perspective
• Review

Keywords: Membrane Technologies, Liquid Processing, Waste Recovery, Sustainability, Artificial Intelligence (AI), Machine Learning

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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