Emerging Manufacturing Strategies: Additive, Nano and Composite Fabrication of Functional Materials

Special Issue Editors


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Guest Editor
Department of Mechanical Engineering, Wichita State University, 1845 Fairmount St., Wichita, KS 67260-0113, USA
Interests: additive manufacturing (3D/4D); sustainable manufacturing systems; composite manufacturing; nanomanufacturing; aircraft manufacturing; advanced materials; nanomaterials; biomaterials; recycling; life cycle assessment; energy systems; energy storage; biodiesel; wastewater treatment

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Guest Editor
Division of Engineering, Texas A&M University-Texarkana, 7101 University Ave, Texarkana, TX 75503, USA
Interests: design and advanced manufacturing; nanomaterials; polymer-based nanocomposites; renewable energy and environmental systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting you to submit your research for this Special Issue of the Journal of Manufacturing and Materials Processing published by MDPI, entitled “Emerging Manufacturing Strategies: Additive, Nano and Composite Fabrication of Functional Materials”.

The Special Issue, “Emerging Manufacturing Strategies: Additive, Nano and Composite Fabrication of Functional Materials”, is intended to focus on recent progress in new manufacturing methods that allow the design and production of the next generation of functional materials. The topic will concentrate on studies that involve three main areas: additive manufacturing, nanomanufacturing, and composite fabrication, both as independent dealing techniques and as integrated or hybrid manufacturing strategies.

The Issue may explore the different ways these new technologies could be used individually to customize material properties, increase process efficiency, or enable complex geometries. It will also examine how the combination of these technologies can lead to the creation of multifunctional materials with enhanced mechanical, thermal, electrical, or biomedical performance—for instance, through nano-enabled additive manufacturing or nanostructured composite systems.

The Special Issue receives experimental, computational, and review studies on process development, structure–property relationships, scalable manufacturing, and applications in aerospace, electronics, energy systems, and biomedical devices. The Issue aims to provide a platform for researchers by bringing together these complementary manufacturing paradigms to explore both distinct and synergistic pathways towards the fabrication of advanced functional materials.

Dr. Eylem Asmatulu
Dr. Md Nizam Uddin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Manufacturing and Materials Processing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • additive manufacturing
  • nanomanufacturing
  • composite materials
  • functional materials
  • nanocomposites
  • hybrid manufacturing processes
  • process–structure–property relationships
  • advanced material fabrication

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Published Papers (1 paper)

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Review

37 pages, 10005 KB  
Review
Intelligent Non-Destructive Evaluation of Additively Manufactured Metal Parts: From Advanced Inspections to Data-Driven Quality Predictions
by Abdulcelil Bayar, Fatih Altun, Gozde Altuntas, Ramazan Asmatulu, Odessa Engram and Eylem Asmatulu
J. Manuf. Mater. Process. 2026, 10(5), 175; https://doi.org/10.3390/jmmp10050175 - 16 May 2026
Viewed by 151
Abstract
This review paper presents a comprehensive and system-oriented analysis of advanced non-destructive testing (NDT) technologies for metal additive manufacturing (AM), including X-ray computed tomography (XCT), ultrasonic testing (UT), infrared thermography, acoustic emission (AE), and electromagnetic techniques. While the existing literature often focuses on [...] Read more.
This review paper presents a comprehensive and system-oriented analysis of advanced non-destructive testing (NDT) technologies for metal additive manufacturing (AM), including X-ray computed tomography (XCT), ultrasonic testing (UT), infrared thermography, acoustic emission (AE), and electromagnetic techniques. While the existing literature often focuses on the physical principles of individual NDT methods, this work addresses a critical knowledge gap by analyzing NDT as a digitally integrated “quality intelligence layer” rather than a standalone post-process inspection tool. The primary motivation is to bridge the disconnect between raw inspection data and cyber–physical production systems. Particular focus is given to NDT data analytics and digitalization, where machine learning (ML) and digital twin (DT) integration are discussed as fundamental enablers of intelligent manufacturing. The review systematically examines image and signal processing pipelines required for quantitative defect characterization, highlighting challenges related to voxel resolution, signal-to-noise ratio, anisotropic microstructures, and operator dependency. It further analyzes supervised learning, deep learning, and multi-sensor data fusion approaches for automated defect classification and predictive quality assessment. Furthermore, the role of digital twins in coupling in situ monitoring data, ex situ NDT results, and physics-based models is discussed as a transformative pathway toward closed-loop process control and evidence-based certification. By synthesizing NDT science with digital manufacturing architectures, this review contributes a unique framework for transitioning from traditional inspection-centric quality control to a predictive, adaptive, and digital twin-enabled quality assurance paradigm. The work concludes by identifying key research gaps in data standardization and computational scalability, providing a strategic roadmap for the future of smart AM production. Full article
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