A Decade of Digital Twins in Materials Science and Engineering
Source abstract
Abstract
Digital twins (DTs) are rapidly emerging as transformative tools in materials science and engineering, enabling real-time data integration, predictive modeling, and virtual testing. This study presents a systematic bibliometric review of 1106 peer-reviewed articles published in the last decade in Scopus and Web of Science. Using a five-stage methodology, the review examines publication trends, thematic areas, citation metrics, and keyword patterns. The results reveal exponential growth in scientific output, with Materials Theory, Computation, and Data Science as the most represented area. A thematic analysis of the most cited documents identifies four major research streams: foundational frameworks, DTs in additive manufacturing, sector-specific applications, and intelligent production systems. Keyword co-occurrence and strategic mapping show a strong foundation in modeling, simulation, and optimization, with growing links to machine learning and sustainability. The review highlights current challenges and proposes future research directions for advancing DTs in materials science.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Learning in Materials Science · Technology Assessment and Management · Digital Transformation in Industry
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (57)
Show source-provided references
1. Visualisation of the Digital Twin data in manufacturing by using Augmented Reality10.1016/j.procir.2019.03.223 ↗
2. Interactive virtual platform for simulating a concrete compression test10.4028/www.scientific.net/KEM.572.582 ↗
3. Technologies for digital twin applications in construction10.1016/j.autcon.2023.104931 ↗
4. Virtual reality and digital twins for enhanced learning in chemical engineering10.1016/B978-0-443-28824-1.50590-1 ↗
5. The technological obsolescence of virtual reality learning environments10.3390/app10030915 ↗
6. A categorization of digital twin and model-based system engineering interactions10.3390/app15105333 ↗
7. The digital twin paradigm for future NASA and U.S. Air force vehicles
8. Digital Twin in manufacturing: a categorical literature review and classification10.1016/j.ifacol.2018.08.474 ↗
9. Autonomous, context-aware, adaptive Digital Twins—state of the art and roadmap10.1016/j.compind.2021.103508 ↗
10. Agile construction digital twin engineering10.3390/buildings15030386 ↗
11. An approach integrating model-based systems engineering, IoT, and digital twin for the design of electric unmanned autonomous vehicles10.3390/systems13020073 ↗
12. Digital twin for civil engineering systems: an exploratory review for distributed sensing updating10.3390/s22093168 ↗
13. Digital twins to predict crack propagation of sustainable engineering materials under different loads10.3390/machines12020125 ↗
14. Digital twins in software engineering—a systematic literature review and vision10.3390/app14030977 ↗
15. OPC UA NodeSet ontologies as a pillar of representing semantic digital twins of manufacturing resources
16. Real-time combination of material flow simulation, digital twins of manufacturing cells, an AGV and a mixed-reality application10.1016/j.procir.2021.11.271 ↗
17. A microstructural electrochemo-mechanical model of high-nickel composite electrodes towards digital twins to bridge the particle and electrode-level characterizations10.1039/D4EE04856C ↗
18. Towards the digitalisation of porous energy materials: evolution of digital approaches for microstructural design10.1039/D1EE00398D ↗
19. Digital twin Bayesian entropy framework for corrosion fatigue life prediction and calibration of bridge suspender10.1016/j.ress.2024.110456 ↗
20. Digital twins-boosted intelligent maintenance of ageing bridge hangers exposed to coupled corrosion-fatigue deterioration10.1016/j.autcon.2024.105697 ↗
21. Materials Research Society—2025 MRS Fall Meeting & Exhibit n.d. [cited 2025 May 11]. Available from: https://www.mrs.org/meetings-events/annual-meetings/2025-mrs-fall-meeting.
22. The PRISMA, 2020 statement: an updated guideline for reporting systematic reviews10.1016/j.ijsu.2021.105906 ↗
23. PRISMA2020: an R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis10.1002/cl2.1230 ↗
24. Energy storage in carbon fiber-based batteries: trends and future perspectives10.3390/app142110034 ↗
25. Titanium additive manufacturing with powder bed fusion: a bibliometric perspective10.3390/app142210543 ↗
26. Nanocomposites for multifunctional sensors: a comprehensive bibliometric exploration10.3390/nano15010034 ↗
27. Digital twin: values, challenges and enablers from a modeling perspective10.1109/ACCESS.2020.2970143 ↗
28. C2PS: a digital twin architecture reference model for the cloud-based cyber-physical systems10.1109/ACCESS.2017.2657006 ↗
29. Fast charging of energy-dense lithium-ion batteries10.1038/s41586-022-05281-0 ↗
30. Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system10.1080/00207543.2018.1471243 ↗
31. Building blocks for a digital twin of additive manufacturing10.1016/j.actamat.2017.06.039 ↗
32. Building a digital twin for additive manufacturing through the exploitation of blockchain: a case analysis of the aircraft industry10.1016/j.compind.2019.04.011 ↗
33. Study on city digital twin technologies for sustainable smart city design: a review and bibliometric analysis of geographic information system and building information modeling integration10.1016/j.scs.2022.104009 ↗
34. A digital twin for rapid qualification of 3D printed metallic components10.1016/j.apmt.2018.11.003 ↗
35. Digital twin modeling method based on biomimicry for machining aerospace components10.1016/j.jmsy.2020.04.014 ↗
36. Development of the simulation model for Digital Twin applications in historical masonry buildings: the integration between numerical and experimental reality10.1016/j.compstruc.2020.106282 ↗
37. Reality-virtuality technologies in the field of materials science and engineering10.3390/app12104968 ↗
38. Artificial intelligence reinventing materials engineering: a bibliometric review10.3390/app14188143 ↗
39. From the real device to the digital twin: a coupled experimental-numerical strategy to investigate a novel bioresorbable vascular scaffold10.1371/journal.pone.0252788 ↗
40. Synthesizing controlled microstructures of porous media using generative adversarial networks and reinforcement learning
41. Aluminum alloy development for wheel production by low pressure die casting with new generation computational materials engineering approaches10.24425/afe.2021.138677 ↗
42. Integrating materials model-based definitions into design, manufacturing, and sustainment: a digital twin demonstration of incorporating residual stresses in the lifecycle analysis of a turbine disk10.1115/1.4048426 ↗
43. Probabilistic learning and updating of a digital twin for composite material systems10.1002/nme.6430 ↗
44. Integrating machine learning and characterization in battery research: toward cognitive digital twins with physics and knowledge10.1002/adfm.202422601 ↗
45. A digital twin approach to a quantitative microstructure-property study of carbon fibers through HRTEM characterization and multiscale FEA10.3390/ma13194231 ↗
46. Digital twin of a high-energy system using aluminum hydride as a fuel10.1007/s10891-021-02374-x ↗
47. Current theoretical and applied research on energy- and resource-saving highly reliable chemical process systems engineering10.1134/S004057952104031X ↗
48. Enhanced solar photovoltaic system management and integration: the digital twin concept10.3390/solar5010007 ↗
49. Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning
50. A breakthrough in producing personalized solutions for rehabilitation and physiotherapy thanks to the introduction of AI to additive manufacturing10.3390/app15042219 ↗
51. Microstructure simulation of maraging steel 1.2709 processed by powder bed fusion of metals using a laser beam: a cellular automata approach with varying process parameters10.1016/j.rinma.2025.100667 ↗
52. Applications, design methods, and challenges for additive manufacturing of thermal solutions for heterogeneous integration of electronics10.1115/1.4067649 ↗
53. A proof of concept of a structural supercapacitor made of graphene coated woven carbon fibers: EIS study and mechanical performance10.1016/j.electacta.2021.137746 ↗
54. Ultrasensitive and highly stretchable sensors for human motion monitoring made of graphene reinforced polydimethylsiloxane: electromechanical and complex impedance sensing performance10.1016/j.carbon.2022.02.043 ↗
55. Technologies used by general electric to create digital twins for energy industry10.1007/s10749-024-01839-2 ↗
56. Advancements and challenges of digital twins in industry10.1038/s43588-024-00603-w ↗
57. Digital twin in manufacturing: transient thermo-mechanical simulations