Technologies

2025

Jump to: 2024, 2023

43 pages, 15420 KiB

Open AccessReview

Advanced Precision Cutting Titanium Alloy Methods: A Critical Review Considering Cost, Efficiency, and Quality

by Guangping Wang, Xiaoxuan Chen, Zhipeng Xu, Feng Feng, Jianfu Zhang, Xiangyu Zhang and Pingfa Feng

Technologies 2025, 13(5), 172; https://doi.org/10.3390/technologies13050172 - 25 Apr 2025

Viewed by 80

Abstract

This literature review focuses on titanium alloys, which are crucial in modern manufacturing due to their excellent properties. The review covers their classification, machining challenges, and advanced cutting methods. Different alloy types (α-Ti, β-Ti, and α+β-Ti) have distinct characteristics and applications; their machining [...] Read more.

This literature review focuses on titanium alloys, which are crucial in modern manufacturing due to their excellent properties. The review covers their classification, machining challenges, and advanced cutting methods. Different alloy types (α-Ti, β-Ti, and α+β-Ti) have distinct characteristics and applications; their machining challenges include low thermal conductivity and pronounced chemical reactivity. Nowadays, advanced cutting methods of titanium alloys involve innovated tool design, efficient coolant techniques, and ultrasonic vibration cutting. The impact of these methods on cost, quality, and efficiency is analyzed, considering both positive and negative aspects. Lastly, strategies for cost reduction, efficiency improvement, and quality enhancement are explored, highlighting the complex relationship between these factors in titanium alloy processing. Full article

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29 pages, 4181 KiB

Open AccessReview

Using Serious Games and Digital Games to Improve Students’ Computational Thinking and Programming Skills in K-12 Education: A Systematic Literature Review

by Sindre Wennevold Gundersen and Georgios Lampropoulos

Technologies 2025, 13(3), 113; https://doi.org/10.3390/technologies13030113 - 11 Mar 2025

Cited by 1 | Viewed by 1457

Abstract

Computational thinking and problem-solving skills have become vital for students to develop. Digital games and serious games are increasingly being used in educational settings and present great potential to aid students’ learning. This study aims to explore the role and impact of serious [...] Read more.

Computational thinking and problem-solving skills have become vital for students to develop. Digital games and serious games are increasingly being used in educational settings and present great potential to aid students’ learning. This study aims to explore the role and impact of serious games and digital games on students’ computational thinking and programming skills in primary, secondary, and K-12 education through a systematic review of the existing literature. Four research questions were set to be examined. Following the PRISMA framework, 78 studies deriving from IEEE, Scopus, and Web of Science over the period of 2011–2024 are examined. The studies are categorized into Theoretical and Review studies, Proposal and Showcase studies, and Experimental and Case studies. Based on the results, serious games and digital games arose as meaningful educational tools that are positively viewed by education stakeholders and that can effectively support and improve K-12 education students’ computational thinking and programming skills. Among the benefits identified, it was revealed that serious games offer enjoyable and interactive learning experiences that can improve students’ learning performance, engagement, and motivation, enhance students’ confidence and focus, and promote self-regulated learning and personalized learning. Additionally, serious games emerged as an educational means that can effectively support social learning and provide real-time feedback. The challenges identified were related to the selection of games and the game-related design elements, decisions, and approaches. Hence, the study highlights the significance of the design of serious games and the need to cultivate students’ computational thinking, problem-solving, and social skills from a young age. Finally, the study reveals key design principles and aspects to consider when developing serious games and digital games and highlights the need to involve education stakeholders throughout the design and development process. Full article

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18 pages, 641 KiB

Open AccessReview

Exploring the Combination of Serious Games, Social Interactions, and Virtual Reality in Adolescents with ASD: A Scoping Review

by Fabrizio Stasolla, Enza Curcio, Anna Passaro, Mariacarla Di Gioia, Antonio Zullo and Elvira Martini

Technologies 2025, 13(2), 76; https://doi.org/10.3390/technologies13020076 - 12 Feb 2025

Cited by 1 | Viewed by 1483

Abstract

Autism spectrum disorder (ASD) often presents significant challenges for adolescents in developing social interaction skills. Emerging technologies such as Serious Games (SGs) and Virtual Reality (VR) offer promising solutions by providing immersive, interactive learning environments. This scoping review evaluates the potential of VR-based [...] Read more.

Autism spectrum disorder (ASD) often presents significant challenges for adolescents in developing social interaction skills. Emerging technologies such as Serious Games (SGs) and Virtual Reality (VR) offer promising solutions by providing immersive, interactive learning environments. This scoping review evaluates the potential of VR-based SGs to enhance social skills in adolescents with ASD by identifying current applications, benefits, limitations, and research gaps. A systematic search of the literature was conducted on Scopus, focusing on empirical studies published between 2013 and 2024. Studies were included based on their relevance to the use of SGs and VR in promoting social interactions in children and adolescents with ASD. The review highlights that VR-based SGs can effectively support the development of social skills, such as communication and collaboration, by providing structured, safe environments for children and adolescents to practice and refine their abilities. However, challenges remain, including the high cost of VR equipment, the need for greater customization, and the limited scope of long-term efficacy studies. While VR-based SGs show considerable promise, further research is needed to explore their long-term impacts and improve accessibility. Addressing these challenges could solidify VR’s role in ASD interventions, enhancing social skill development and improving the quality of life for children and adolescents with ASD. Full article

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22 pages, 14692 KiB

Open AccessReview

A Systematic Review of Locomotion Assistance Exoskeletons: Prototype Development and Technical Challenges

by Weiqi Lin, Hui Dong, Yongzhuo Gao, Wenda Wang, Yi Long, Long He, Xiwang Mao, Dongmei Wu and Wei Dong

Technologies 2025, 13(2), 69; https://doi.org/10.3390/technologies13020069 - 5 Feb 2025

Cited by 2 | Viewed by 2116

Abstract

Exoskeletons can track the wearer’s movements in real time, thereby enhancing physical performance or restoring mobility for individuals with gait impairments. These wearable assistive devices have demonstrated significant potential in both rehabilitation and industrial applications. This review focuses on the major advancements in [...] Read more.

Exoskeletons can track the wearer’s movements in real time, thereby enhancing physical performance or restoring mobility for individuals with gait impairments. These wearable assistive devices have demonstrated significant potential in both rehabilitation and industrial applications. This review focuses on the major advancements in exoskeleton technology published since 2020, with particular emphasis on the development of structural designs for lower-limb exoskeletons employed in locomotion assistance. We employed a systematic literature review methodology, categorizing the included studies into three main types: rigid exoskeleton, soft exoskeleton, and tethered platform. The current development status of robotic exoskeletons is analyzed based on publication year, system weight, target assistive joints, and main effects. Furthermore, we examine the factors driving these advancements and their implications for the field. The key challenges and opportunities that may influence the future development of exoskeleton technologies are also highlighted in this review. Full article

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32 pages, 1348 KiB

Open AccessReview

Vision Transformers for Image Classification: A Comparative Survey

by Yaoli Wang, Yaojun Deng, Yuanjin Zheng, Pratik Chattopadhyay and Lipo Wang

Technologies 2025, 13(1), 32; https://doi.org/10.3390/technologies13010032 - 12 Jan 2025

Cited by 2 | Viewed by 6700

Abstract

Transformers were initially introduced for natural language processing, leveraging the self-attention mechanism. They require minimal inductive biases in their design and can function effectively as set-based architectures. Additionally, transformers excel at capturing long-range dependencies and enabling parallel processing, which allows them to outperform [...] Read more.

Transformers were initially introduced for natural language processing, leveraging the self-attention mechanism. They require minimal inductive biases in their design and can function effectively as set-based architectures. Additionally, transformers excel at capturing long-range dependencies and enabling parallel processing, which allows them to outperform traditional models, such as long short-term memory (LSTM) networks, on sequence-based tasks. In recent years, transformers have been widely adopted in computer vision, driving remarkable advancements in the field. Previous surveys have provided overviews of transformer applications across various computer vision tasks, such as object detection, activity recognition, and image enhancement. In this survey, we focus specifically on image classification. We begin with an introduction to the fundamental concepts of transformers and highlight the first successful Vision Transformer (ViT). Building on the ViT, we review subsequent improvements and optimizations introduced for image classification tasks. We then compare the strengths and limitations of these transformer-based models against classic convolutional neural networks (CNNs) through experiments. Finally, we explore key challenges and potential future directions for image classification transformers. Full article

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2024

Jump to: 2025, 2023

28 pages, 771 KiB

Open AccessReview

Formal Verification of Code Conversion: A Comprehensive Survey

by Amira T. Mahmoud, Ahmad A. Mohammed, Mahitap Ayman, Walaa Medhat , Sahar Selim , Hala Zayed, Ahmed H. Yousef and Nahla Elaraby

Technologies 2024, 12(12), 244; https://doi.org/10.3390/technologies12120244 - 26 Nov 2024

Viewed by 2792

Abstract

Code conversion, encompassing translation, optimization, and generation, is becoming increasingly critical in information systems and the software industry. Traditional validation methods, such as test cases and code coverage metrics, often fail to ensure the correctness, completeness, and equivalence of converted code to its [...] Read more.

Code conversion, encompassing translation, optimization, and generation, is becoming increasingly critical in information systems and the software industry. Traditional validation methods, such as test cases and code coverage metrics, often fail to ensure the correctness, completeness, and equivalence of converted code to its original form. Formal verification emerges as a crucial methodology to address these limitations. Although numerous surveys have explored formal verification in various contexts, a significant research gap exists in pinpointing appropriate formal verification approaches to code conversion tasks. This paper provides a detailed survey of formal verification techniques applicable to code conversion. This survey identifies the strengths and limitations of contemporary adopted approaches while outlining a trajectory for future research, emphasizing the need for automated and scalable verification tools. The novel categorization of formal verification methods provided in this paper serves as a foundational guide for researchers seeking to enhance the reliability of code conversion processes. Full article

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14 pages, 1707 KiB

Open AccessReview

Influence of Insulin Pen Needle Geometry on Pain Perception and Patient’s Acceptability: A Review

by Francesca De Tommasi and Sergio Silvestri

Technologies 2024, 12(11), 233; https://doi.org/10.3390/technologies12110233 - 19 Nov 2024

Viewed by 2367

Abstract

Diabetes is one of the most common diseases worldwide, with an increasing number of people affected. Insulin therapy is still the major treatment for both Type 1 and Type 2 diabetes and has evolved from bulky syringes to modern insulin pens introduced in [...] Read more.

Diabetes is one of the most common diseases worldwide, with an increasing number of people affected. Insulin therapy is still the major treatment for both Type 1 and Type 2 diabetes and has evolved from bulky syringes to modern insulin pens introduced in 1985. An insulin pen consists of three major parts: a cartridge, a single-use pen needle (PN), and a precision dosing mechanism. Initially, PNs were long and thick, causing great discomfort and concern. Thanks to advances in design, shorter and thinner needles have appeared on the market, improving patient acceptability and pain perception. Studies highlight the influence of PN geometry and other characteristics on injection-related pain, including length, diameter, bevel design, and hub. Despite a lack of specific international regulations for PN geometry, scientific publications have focused on exploring different PNs’ characteristics to optimize patient comfort and reduce pain. To guide the selection of suitable PNs, this review provides a round-up of literature research findings on the impact of PN geometry on pain perception and patient acceptability. Specifically, it provides an overview of the PN manufacturing process, current international regulations, and the state-of-the-art research on PN geometry affecting pain perception. Full article

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34 pages, 4573 KiB

Open AccessReview

Revolutionary Integration of Artificial Intelligence with Meta-Optics-Focus on Metalenses for Imaging

by Nikolay L. Kazanskiy, Svetlana N. Khonina, Ivan V. Oseledets, Artem V. Nikonorov and Muhammad A. Butt

Technologies 2024, 12(9), 143; https://doi.org/10.3390/technologies12090143 - 28 Aug 2024

Cited by 6 | Viewed by 4749

Abstract

Artificial intelligence (AI) significantly enhances the development of Meta-Optics (MOs), which encompasses advanced optical components like metalenses and metasurfaces designed to manipulate light at the nanoscale. The intricate design of these components requires sophisticated modeling and optimization to achieve precise control over light [...] Read more.

Artificial intelligence (AI) significantly enhances the development of Meta-Optics (MOs), which encompasses advanced optical components like metalenses and metasurfaces designed to manipulate light at the nanoscale. The intricate design of these components requires sophisticated modeling and optimization to achieve precise control over light behavior, tasks for which AI is exceptionally well-suited. Machine learning (ML) algorithms can analyze extensive datasets and simulate numerous design variations to identify the most effective configurations, drastically speeding up the development process. AI also enables adaptive MOs that can dynamically adjust to changing imaging conditions, improving performance in real-time. This results in superior image quality, higher resolution, and new functionalities across various applications, including microscopy, medical diagnostics, and consumer electronics. The combination of AI with MOs thus epitomizes a transformative advancement, pushing the boundaries of what is possible in imaging technology. In this review, we explored the latest advancements in AI-powered metalenses for imaging applications. Full article

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25 pages, 3396 KiB

Open AccessReview

Technology in Forensic Sciences: Innovation and Precision

by Xavier Chango, Omar Flor-Unda, Pedro Gil-Jiménez and Hilario Gómez-Moreno

Technologies 2024, 12(8), 120; https://doi.org/10.3390/technologies12080120 - 26 Jul 2024

Cited by 7 | Viewed by 19203

Abstract

The advancement of technology and its developments have provided the forensic sciences with many cutting-edge tools, devices, and applications, allowing forensics a better and more accurate understanding of the crime scene, a better and optimal acquisition of data and information, and faster processing, [...] Read more.

The advancement of technology and its developments have provided the forensic sciences with many cutting-edge tools, devices, and applications, allowing forensics a better and more accurate understanding of the crime scene, a better and optimal acquisition of data and information, and faster processing, allowing more reliable conclusions to be obtained and substantially improving the scientific investigation of crime. This article describes the technological advances, their impacts, and the challenges faced by forensic specialists in using and implementing these technologies as tools to strengthen their field and laboratory investigations. The systematic review of the scientific literature used the PRISMA^® methodology, analyzing documents from databases such as SCOPUS, Web of Science, Taylor & Francis, PubMed, and ProQuest. Studies were selected using a Cohen Kappa coefficient of 0.463. In total, 63 reference articles were selected. The impact of technology on investigations by forensic science experts presents great benefits, such as a greater possibility of digitizing the crime scene, allowing remote analysis through extended reality technologies, improvements in the accuracy and identification of biometric characteristics, portable equipment for on-site analysis, and Internet of things devices that use artificial intelligence and machine learning techniques. These alternatives improve forensic investigations without diminishing the investigator’s prominence and responsibility in the resolution of cases. Full article

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41 pages, 2860 KiB

Open AccessReview

Analysis of the Use of Artificial Intelligence in Software-Defined Intelligent Networks: A Survey

by Bayron Jesit Ospina Cifuentes, Álvaro Suárez, Vanessa García Pineda, Ricardo Alvarado Jaimes, Alber Oswaldo Montoya Benitez and Juan David Grajales Bustamante

Technologies 2024, 12(7), 99; https://doi.org/10.3390/technologies12070099 - 2 Jul 2024

Cited by 6 | Viewed by 4731

Abstract

The distributed structure of traditional networks often fails to promptly and accurately provide the computational power required for artificial intelligence (AI), hindering its practical application and implementation. Consequently, this research aims to analyze the use of AI in software-defined networks (SDNs). To achieve [...] Read more.

The distributed structure of traditional networks often fails to promptly and accurately provide the computational power required for artificial intelligence (AI), hindering its practical application and implementation. Consequently, this research aims to analyze the use of AI in software-defined networks (SDNs). To achieve this goal, a systematic literature review (SLR) is conducted based on the PRISMA 2020 statement. Through this review, it is found that, bottom-up, from the perspective of the data plane, control plane, and application plane of SDNs, the integration of various network planes with AI is feasible, giving rise to Intelligent Software Defined Networking (ISDN). As a primary conclusion, it was found that the application of AI-related algorithms in SDNs is extensive and faces numerous challenges. Nonetheless, these challenges are propelling the development of SDNs in a more promising direction through the adoption of novel methods and tools such as route optimization, software-defined routing, intelligent methods for network security, and AI-based traffic engineering, among others. Full article

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26 pages, 6974 KiB

Open AccessReview

Energy Efficiency in Additive Manufacturing: Condensed Review

by Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra and Khalid Tantawi

Technologies 2024, 12(2), 21; https://doi.org/10.3390/technologies12020021 - 5 Feb 2024

Cited by 12 | Viewed by 6173

Abstract

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the [...] Read more.

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the cost of production, fabricate light weight and complex parts in a short period of time, and respond to the manufacturing needs of customers. It is clear that the AM technologies consume energy to complete the production tasks of each part. Therefore, it is imperative to know the impact of energy efficiency in order to economically and properly use these advancing technologies. This paper provides a holistic review of this important concept from the perspectives of process, materials science, industry, and initiatives. The goal of this research study is to collect and present the latest knowledge blocks related to the energy consumption of AM technologies from a number of recent technical resources. Overall, they are the collection of surveys, observations, experimentations, case studies, content analyses, and archival research studies. The study highlights the current trends and technologies associated with energy efficiency and their influence on the AM community. Full article

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40 pages, 12154 KiB

Open AccessFeature PaperReview

A Review of Machine Learning and Deep Learning for Object Detection, Semantic Segmentation, and Human Action Recognition in Machine and Robotic Vision

by Nikoleta Manakitsa, George S. Maraslidis, Lazaros Moysis and George F. Fragulis

Technologies 2024, 12(2), 15; https://doi.org/10.3390/technologies12020015 - 23 Jan 2024

Cited by 61 | Viewed by 30035

Abstract

Machine vision, an interdisciplinary field that aims to replicate human visual perception in computers, has experienced rapid progress and significant contributions. This paper traces the origins of machine vision, from early image processing algorithms to its convergence with computer science, mathematics, and robotics, [...] Read more.

Machine vision, an interdisciplinary field that aims to replicate human visual perception in computers, has experienced rapid progress and significant contributions. This paper traces the origins of machine vision, from early image processing algorithms to its convergence with computer science, mathematics, and robotics, resulting in a distinct branch of artificial intelligence. The integration of machine learning techniques, particularly deep learning, has driven its growth and adoption in everyday devices. This study focuses on the objectives of computer vision systems: replicating human visual capabilities including recognition, comprehension, and interpretation. Notably, image classification, object detection, and image segmentation are crucial tasks requiring robust mathematical foundations. Despite the advancements, challenges persist, such as clarifying terminology related to artificial intelligence, machine learning, and deep learning. Precise definitions and interpretations are vital for establishing a solid research foundation. The evolution of machine vision reflects an ambitious journey to emulate human visual perception. Interdisciplinary collaboration and the integration of deep learning techniques have propelled remarkable advancements in emulating human behavior and perception. Through this research, the field of machine vision continues to shape the future of computer systems and artificial intelligence applications. Full article

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2023

Jump to: 2025, 2024

24 pages, 8416 KiB

Open AccessReview

Recent Technological Progress of Fiber-Optical Sensors for Bio-Mechatronics Applications

by Mohomad Aqeel Abdhul Rahuman, Nipun Shantha Kahatapitiya, Viraj Niroshan Amarakoon, Udaya Wijenayake, Bhagya Nathali Silva, Mansik Jeon, Jeehyun Kim, Naresh Kumar Ravichandran and Ruchire Eranga Wijesinghe

Technologies 2023, 11(6), 157; https://doi.org/10.3390/technologies11060157 - 7 Nov 2023

Cited by 15 | Viewed by 4305

Abstract

Bio-mechatronics is an interdisciplinary scientific field that emphasizes the integration of biology and mechatronics to discover innovative solutions for numerous biomedical applications. The broad application spectrum of bio-mechatronics consists of minimally invasive surgeries, rehabilitation, development of prosthetics, and soft wearables to find engineering [...] Read more.

Bio-mechatronics is an interdisciplinary scientific field that emphasizes the integration of biology and mechatronics to discover innovative solutions for numerous biomedical applications. The broad application spectrum of bio-mechatronics consists of minimally invasive surgeries, rehabilitation, development of prosthetics, and soft wearables to find engineering solutions for the human body. Fiber-optic-based sensors have recently become an indispensable part of bio-mechatronics systems, which are essential for position detection and control, monitoring measurements, compliance control, and various feedback applications. As a result, significant advancements have been introduced for designing and developing fiber-optic-based sensors in the past decade. This review discusses recent technological advancements in fiber-optical sensors, which have been potentially adapted for numerous bio-mechatronic applications. It also encompasses fundamental principles, different types of fiber-optical sensors based on recent development strategies, and characterizations of fiber Bragg gratings, optical fiber force myography, polymer optical fibers, optical tactile sensors, and Fabry–Perot interferometric applications. Hence, robust knowledge can be obtained regarding the technological enhancements in fiber-optical sensors for bio-mechatronics-based interdisciplinary developments. Therefore, this review offers a comprehensive exploration of recent technological advances in fiber-optical sensors for bio-mechatronics. It provides insights into their potential to revolutionize biomedical and bio-mechatronics applications, ultimately contributing to improved patient outcomes and healthcare innovation. Full article

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31 pages, 6176 KiB

Open AccessReview

Advancements in Doping Strategies for Enhanced Photocatalysts and Adsorbents in Environmental Remediation

by Pramita Sen, Praneel Bhattacharya, Gargi Mukherjee, Jumasri Ganguly, Berochan Marik, Devyani Thapliyal, Sarojini Verma, George D. Verros, Manvendra Singh Chauhan and Raj Kumar Arya

Technologies 2023, 11(5), 144; https://doi.org/10.3390/technologies11050144 - 17 Oct 2023

Cited by 22 | Viewed by 6240

Abstract

Environmental pollution poses a pressing global challenge, demanding innovative solutions for effective pollutant removal. Photocatalysts, particularly titanium dioxide (TiO₂), are renowned for their catalytic prowess; however, they often require ultraviolet light for activation. Researchers had turned to doping with metals and [...] Read more.

Environmental pollution poses a pressing global challenge, demanding innovative solutions for effective pollutant removal. Photocatalysts, particularly titanium dioxide (TiO₂), are renowned for their catalytic prowess; however, they often require ultraviolet light for activation. Researchers had turned to doping with metals and non-metals to extend their utility into the visible spectrum. While this approach shows promise, it also presents challenges such as material stability and dopant leaching. Co-doping, involving both metals and non-metals, has emerged as a viable strategy to mitigate these limitations. Inthe fieldof adsorbents, carbon-based materials doped with nitrogen are gaining attention for their improved adsorption capabilities and CO₂/N₂ selectivity. Nitrogen doping enhances surface area and fosters interactions between acidic CO₂ molecules and basic nitrogen functionalities. The optimal combination of an ultramicroporous surface area and specific nitrogen functional groups is key to achievehigh CO₂ uptake values and selectivity. The integration of photocatalysis and adsorption processes in doped materials has shown synergistic pollutant removal efficiency. Various synthesis methods, including sol–gel, co-precipitation, and hydrothermal approaches had been employed to create hybrid units of doped photocatalysts and adsorbents. While progress has been made in enhancing the performance of doped materials at the laboratory scale, challenges persist in transitioning these technologies to large-scale industrial applications. Rigorous studies are needed to investigate the impact of doping on material structure and stability, optimize process parameters, and assess performance in real-world industrial reactors. These advancements are promising foraddressing environmental pollution challenges, promoting sustainability, and paving the way for a cleaner and healthier future. This manuscript provides a comprehensive overview of recent developments in doping strategies for photocatalysts and adsorbents, offering insights into the potential of these materials to revolutionize environmental remediation technologies. Full article

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39 pages, 25112 KiB

Open AccessEditor’s ChoiceReview

Recent Advances in the 3D Printing of Pure Copper Functional Structures for Thermal Management Devices

by Yue Hao Choong, Manickavasagam Krishnan and Manoj Gupta

Technologies 2023, 11(5), 141; https://doi.org/10.3390/technologies11050141 - 15 Oct 2023

Cited by 10 | Viewed by 4925

Abstract

Thermal management devices such as heat exchangers and heat pipes are integral to safe and efficient performance in multiple engineering applications, including lithium-ion batteries, electric vehicles, electronics, and renewable energy. However, the functional designs of these devices have until now been created around [...] Read more.

Thermal management devices such as heat exchangers and heat pipes are integral to safe and efficient performance in multiple engineering applications, including lithium-ion batteries, electric vehicles, electronics, and renewable energy. However, the functional designs of these devices have until now been created around conventional manufacturing constraints, and thermal performance has plateaued as a result. While 3D printing offers the design freedom to address these limitations, there has been a notable lack in high thermal conductivity materials beyond aluminium alloys. Recently, the 3D printing of pure copper to sufficiently high densities has finally taken off, due to the emergence of commercial-grade printers which are now equipped with 1 kW high-power lasers or short-wavelength lasers. Although the capabilities of these new systems appear ideal for processing pure copper as a bulk material, the performance of advanced thermal management devices are strongly dependent on topology-optimised filigree structures, which can require a very different processing window. Hence, this article presents a broad overview of the state-of-the-art in various additive manufacturing technologies used to fabricate pure copper functional filigree geometries comprising thin walls, lattice structures, and porous foams, and identifies opportunities for future developments in the 3D printing of pure copper for advanced thermal management devices. Full article

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