Gupta / Sharma / Rani AI-Driven Technologies for Sustainable Engineering

1. Auflage 2025
ISBN: 979-8-89881-294-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 360 Seiten

Reihe: AI and Emerging Technologies for a Sustainable Future

Learn how artificial intelligence is reshaping sustainable development across engineering domains with AI-Driven Technologies for Sustainable Engineering. The book demonstrates how AI-infused solutions can strengthen resilience, enhance efficiency, and support global sustainability goals. Spanning topics ranging from IoT, healthcare, water systems, smart cities, to nanotechnology, education, and renewable energy, each chapter presents in-depth discussions supported by real-world case studies, illustrating how intelligent systems from automation to predictive analytics are reducing environmental impact and enabling responsible innovation. Challenging the perception that technology contributes primarily to degradation, this book highlights how data-driven intelligence can instead reverse harmful trends and serve as a catalyst for sustainable transformation. Key Features Covers diverse AI applications across engineering fields including renewable energy, healthcare, education, transportation, and smart infrastructure. Aligns AI-enabled solutions with the United Nations Sustainable Development Goals (SDGs). Bridges research and real-world practice through detailed case studies and applied examples. Presents insights from leading experts, offering a multidisciplinary understanding of sustainable engineering.

Autoren/Hrsg.

Gupta, Shilpa

Sharma, Ritika

Rani, Gokana Mohana

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Leseproben

Nanomaterials in the AI Era: Revolutionizing Research, Design, and Applications

Rajni Sharma1, *, Love Singla2, Gulab Singh3

1 Department of Biotechnology, Maharaja Agrasen University, Baddi, Himachal Pradesh, India

2 Department of Microbiology, Maharaja Agrasen University, Baddi, Himachal Pradesh, India

3 Department of Bio-nanotechnology, Chaudhary Charan Singh Haryana Agriculture University, Hisar, Haryana, India

Abstract

Nanomaterials, distinguished for their unique properties and diverse applications, are at the forefront of scientific and technological innovation. A transformative development in this field is integrating Artificial Intelligence (AI) into nanotechnology to discover, design, and apply materials at the nanoscale. By harnessing AI's ability to process complex data sets, researchers can predict material behaviors and develop methods to manufacture nanomaterials with tailored functionalities. AI is also revolutionizing nanomaterial characterization, delivering unparalleled imaging, spectroscopy, and structural analysis precision. Simultaneously, nanomaterials are advancing AI hardware, especially in neuromorphic computing and energy-efficient processes. While this chapter explores various applications such as healthcare innovations, environmental monitoring, sustainable energy solutions, and next-generation electronics, it highlights that these represent only a fraction of the potential where AI and nanomaterials converge. However, this integration raises challenges, including ethical considerations, environmental impacts, and safety regulations. The synergy between AI and nanotechnology holds immense promise for driving the discovery of next-generation nanomaterials across multiple industries, shaping a more sustainable and innovative future.

Keywords: Artificial intelligence (AI), Machine Learning (ML), Material characterization, Nanomaterials, Nanotechnology, Neuromorphic computing, Sustainable energy.

* Corresponding author Rajni Sharma: Department of Biotechnology, Maharaja Agrasen University, Baddi, Himachal Pradesh, India; E-mail: [e-mail]

Introduction

Nanomaterials, characterized by their dimensions in the nanoscale (1–100 nm), exhibit enhanced properties due to quantum effects, high surface area-to-volume ratio, and unique atomic arrangements. These attributes have made nanomaterials

essential across various industries, enhancing electrical, optical, and mechanical performance. Their applications span drug delivery systems, diagnostics, tissue engineering [1], energy storage solutions like batteries and supercapacitors, and sustainable energy technologies, including solar cells and fuel cells [2]. In environmental sustainability, nanotechnology addresses critical challenges, such as water purification, where materials like titanium dioxide play a vital role in photocatalysis, and graphene revolutionizes membrane technology for desalination. Similarly, nanoelectronics, a specialized branch of nanotechnology, has been pivotal in miniaturizing electronic components, enabling advancements in compact and efficient devices [3].

The rapid integration of Artificial Intelligence (AI) into nanotechnology has further transformed the field. AI excels in processing massive and complex datasets, enabling breakthroughs in predictive modeling, optimization, and materials discovery. While AI has revolutionized domains like biology, chemistry, and materials science, its specific integration into nanotechnology is particularly impactful. AI-driven Machine Learning (ML) models have significantly improved property predictions, optimized synthesis conditions, and accelerated the discovery of new materials [4]. Such advancements address the limitations of traditional material design approaches, which are often manual, slow, and costly. In nanomaterials research, AI enhances High-Throughput Experimentation (HTE) by efficiently analyzing intricate datasets from simulations or experiments, reducing the time required to identify materials with desired functionalities [5]. AI-based computational models also predict material behavior under specific conditions, minimizing costs associated with trial-and-error processes. These innovations enable the discovery of functional nanomaterials tailored for particular applications in healthcare, electronics, and energy [6]. By focusing on unique benefits, such as the functionalization of nanomaterials for optimized biological, electronic, and energy applications, AI-driven research promises to redefine the future of nanotechnology. This convergence of AI and nanotechnology accelerates discovery and addresses pressing challenges in sustainability and innovation [7].

Nanomaterials and their Applications

Nanomaterials are materials that have been engineered to be extremely small at the scale of nanometers and, therefore, possess new functional properties vastly superior to bulk materials due to quantum effects and very high surface-area-to-volume ratios. This demonstration of properties such as increased strength, conductivity, and reactivity has made them very useful in many contexts [8].

There are several types of nanomaterials, which include:

• Nanoparticles: Spherical particles, commonly metal (gold, silver), oxides (zinc oxide, titanium dioxide), or polymers, have applications in catalysis, biomedicine, and energy storage [9].
• Nanocomposites: Hybrid materials with nanoparticles within a matrix improve their mechanical, thermal, or electrical properties. Nanocomposite materials are used in a broad range of applications, such as in the automobile, aerospace, and building industries [10].
• 2D Materials: Thin sheets of materials such as graphene, molybdenum disulfide (MoS2), and hexagonal boron nitride display unique electronic, optical, and sensing properties [11].

Nanoparticles also have potential applications in nanoscale technology, including components of quantum dots and other nanostructures. They exhibit different properties from the bulk material, which are generally expected to alter depending upon a specific size, such as Nanowires and nanotubes (such as carbon nanotubes). Nanorods (Dimensional structures) have beneficial properties like mechanical strength and high electrical conductivity, increased surface area for catalyzing reactions, and sensors, which make them attractive for use in certain application types like flexible electronics, energy storage, and drug delivery.

Applications of Nanomaterials in Various Sectors

Nanomaterials are used in various spheres of daily life, as shown in Fig. (1). Some of them are described below:

Fig. (1))
Applications of nanomaterials in different fields.

1. Medicines: Nanomaterials have revolutionized medical applications, mainly drug delivery through various types of nanoparticles like liposomes, micelles, and polymer-drug conjugates that offer targeted and controlled drug release, thereby reducing side-effects and improving therapeutic results, such as gold nanoparticles, which are currently being used for treatment in cancer, both imaging and treatment. In medical diagnostics, quantum dots are essential nanomaterials for bioimaging with improved contrast and sensitivity [1].
2. Electronics: One industry that is gaining significant dividends in yield enhancers through the use of nanomaterials is the electronics industry, with carbon nanotubes and graphene being only a pair among many others. Their improved electrical conductivity, strength, and flexibility make them essential in developing future transistors, sensors, and conductive films [12]. For instance, transistors based on carbon nanotubes are predicted to outperform silicon-based transistors in speed and energy efficiency, whereas the application of graphene into flexible electronics leads to abundant possibilities [13].
3. Energy: The application areas of nanomaterials in energy management and conversion technologies are nanostructured electrodes like silicon nanoparticles and graphene, which improve the energy density and charging rates in batteries. Materials at the nanoscale are also applied in solar cells to enhance light absorption by exploiting nanomaterials, known as developments in renewable applications (e.g., quantum dot solar cells and perovskite-based photovoltaics) [14].
4. Environment: Nanomaterials are widely used for applications such as water purification, pollution control, and waste management. Together with the ability to filter out heavy metals and organic pollutants from water, carbon-based...