Directed Energy Deposition: A Scientometric Study and Its Practical Implications

Abstract

Directed Energy Deposition is an additive manufacturing subgroup that uses a laser beam to melt the wire or powder to create a melt pool. In the current study, a scientometric analysis has been carried out to analyze the contribution of countries, publication type analysis, distribution of publications over the years, keywords analysis, author analysis, cited journal, categories, institutes of publication, and report the practical implications. Firstly, the database was extracted from the Web of Science and then post-processed with CiteSpace 6.2.R4 and VOSviewer 1.6.20 software. Afterward, the associated results had been extracted and reported. It was found that China is the leader according to publication, followed by the USA and Germany, which mostly published their achievements in article and proceeding paper formats, which are increasing annually. According to the keywords, additive manufacturing, Laser Metal Deposition, and fabrication are the most commonly used. Based on the CiteSapce and VOSviewer results, Lin, Xin and Huang, Weidong are the authors with the highest publication rates. In addition, Additive Manufacturing, Materials & Design, and Materials Science and Engineering: A are the most cited journals, and regarding the categories, materials science, multidisciplinary, applied physics, and manufacturing engineering are the most commonly used DED processes. Northwestern Polytechnical University, Fraunhofer Gesellschaft, and the United States Department of Energy (DOE) have performed the most research in the field of DED.

1. Introduction

Directed Energy Deposition (DED) is an additive manufacturing (AM) process known as 3D printing. In the DED process, the part is built layer-by-layer to fabricate the final part. Firstly, the CAD part is designed and then sliced into a number of layers by slicing software. Next, G-code is extracted and imported to the printer to apply scanning strategies to fabricate the final part [1]. Afterward, to fabricate the part, a source of energy such as a laser or electron beam is used to melt the powder or wire on the previously deposited layer or baseplate [2]. This process is also used to repair or enhance mechanical and microstructural properties. This process does have an array of applications such as oil and gas, automotive, aerospace, and tooling. The concept of DED was coined in 1973 (based on the data from the Web of Science) when engineering started to involve lasers in the manufacturing process. Also, there has been a growing demand for the DED process by researchers and industries year by year. There are some advantages such as high deposition rates [3], different material usage [4], capability to fabricate complex geometries [5], and repair of high-cost parts [6]. On the contrary, there are some challenges to fabricate the parts with DED such as residual stress [7], porosity [8], and surface finish [9], which affect the performance of fabricated samples. Scientometric is a field of knowledge that analyzes the scientific activities, patterns, and trends, quantitively [10]. The main aim of scientometric is to shed light on the dynamics, structure, and evolution of scientific knowledge. So, researchers statistically analyze data such as citation analysis, collaboration analysis, journal and publication analysis, research productivity, such as that of country and institutes, and science mapping.

Although scientometric analyses have been widely applied to broader additive manufacturing and 3D printing research areas [11,12,13,14], a focused scientometric analysis of Directed Energy Deposition is currently lacking. This absence is notable given the increasing industrial relevance and research momentum of DED. To address this gap, this study presents the first dedicated scientometric analysis of the DED field. The data used in this study is sourced from the Web of Science (WoS) database and is processed using CiteSpace and VOSviewer to extract meaningful insights. We conduct a detailed examination of the publication trends, contributing countries and institutions, keyword co-occurrence patterns, journal and category impact, as well as influential authors and collaboration networks. The main contribution of this study lies in uncovering the intellectual landscape and knowledge structure of DED research. It offers a comprehensive and data-driven understanding of how the field has evolved, who its key contributors are, and where research gaps and future opportunities may appear. The motivation for this work stems not only from the growing number of DED publications but also from the lack of prior scientometric efforts dedicated specifically to this process [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35]. By positioning our analysis alongside broader additive manufacturing scientometric efforts, this study provides a comparative and strategic viewpoint for researchers, policymakers, and industry stakeholders.

2. Methodology

The most important step in the current research is to find a suitable database for analysis. In the current study, Web of Science (WoS) was chosen as the database to extract information in the field of DED because it covers widely known publishers such as Wiley Online Library, Elsevier, Springer, Emerald, Taylor & Francis, IEEE Explorer, EBSCO, and ASCE Library. Because it is considered the most extensive database for high-quality scientific publications and contains the most prominent journals and articles, ISI WoS was chosen because it ensures a high level of scientific robustness of WoS [36,37,38]. To gather information, the WoS search engine’s advanced search was used with keywords including Ti = (Laser Metal Deposition) OR Ti = (Direct Energy Deposition). It is worth noting that *Ti* stands for title in the WoS search engine. Then the research period was chosen for all records, and based on the WoS database, the period was shown from 1973 to July 2023 and March 2025. Figure 1 shows the flow chart of the current study. Then the keywords, namely document type, publication year, country of implemented research, author, and number of citations had been used.

Then the achieved results were exported as a plain text file with full record and cited references. To analyze the data, CiteSpace Software (6.2.R4) and VOSviewer were used. Then, the database was saved in two different folders namely data and project. Afterward, the database is imported to the CiteSpace and VOS to analyse the data and extract the results. Next, the criteria for analysis [10], keywords, categories, author, publication per year, publication type, and journal were used, and the results were extracted and discussed. Afterwards, citation burst, centrality, and sigma values were extracted for some of the mentioned parameters via CiteSpace, which are explained in the following paragraphs. It is worth noting that, to check the accuracy of achieved results via CiteSpace and VOSviewer, each output was extracted three times.

2.1. Burst Citation

Burst citation declares the phenomenon when a certain scientific paper acquires much more citations in a certain period of time than its immediate surroundings, as shown in Equation (1) which was calculated by Price’s Law in 1963 [39]. This huge surge in citations points to the publication’s sudden rise in popularity and impact among academics [40]. CiteSpace can detect instances where an article has had a significant rise in citations, which represents a sign of its influence on the subject or particular field of research [41]. B, C, T, and α stand for citation burst, total quantity of citations for the work, how long ago the paper was published, and scaling exponent, which is mostly considered 0.5, respectively.

B = C/(T^α)

(1)

2.2. Betweenness Centrality

The number of shortest distances between two of the nodes that navigate through a specific node serves as the basis for the network centrality metric known as betweenness centrality, which assesses the significance or centrality of a node within a network [42]. High betweenness centrality nodes are generally seen as possible major factors or network “brokers” since they are so important in linking various areas of the network [43]. Equation (2) shows the betweenness centrality formula. In Equation (2), Δ_ij is the number of shortest connections that pass through the node K, while ij is the sum of the shortest links between nodes i and j.

$$BC\left(k\right)={\displaystyle \sum }_{\begin{array}{c}i\\ i\ne j\ne k\end{array}}{\displaystyle \sum }_{\begin{array}{c}i\\ i\ne j\ne k\end{array}}{\displaystyle \frac{{∆}_{ij}\left(k\right)}{{∆}_{ij}}}$$

(2)

2.3. Sigma

Sigma, a combined metric that takes into account both the BC and the burst of node citations, can be used to assess the significance of a scientific node inside a particular network. In reality, this metric assesses the combined potency of a node’s BC and CB, which are its structural and temporal properties [44]. It is worth mentioning that the full explanation of associated parameters related to the scientometric has been provided in the Supplementary Materials (Table S1).

3. Results and Discussion

3.1. Contribution Countries

The data from WoS was utilized to determine the countries contributing the most. Figure 2a,b shows the countries contributing to the field of DED. Based on Figure 2 and

Table 1. Countries contributing in DED process.

Countries	Number of Publications	Percentage
China	1349	35.012%
Usa	779	20.218%
Germany	341	8.850%
South Korea	235	6.099%
India	220	5.710%
Japan	209	5.424%
England	180	4.672%
France	126	3.270%
Italy	126	3.270%
Australia	111	2.881%
Spain	104	2.699%
Russia	102	2.647%
Canada	97	2.518%
Sweden	84	2.180%
Singapore	78	2.024%
Brazil	52	1.350%
Netherlands	42	1.090%
Portugal	42	1.090%
Iran	41	1.064%
Switzerland	35	0.908%
Belgium	34	0.882%
South Africa	34	0.882%
Czech Republic	32	0.831%
Austria	26	0.675%
Taiwan	23	0.597%

, China (with 1349 publications) is the leading country in the field of DED, followed by the USA (779), Germany (341), South Korea (235), India (220), Japan (209), and UK (180). China leads publications in the field of Direct Energy Deposition (DED), a rise owing to significant investment in R&D, initiatives like the “Made in China 2025” plan [24], and a robust industrial sector with rising demand for innovative manufacturing technology. The United States, which has a long history of technological innovation and an established academic and industrial infrastructure, comes in second. Germany, known for its engineering expertise, makes significant contributions to the field of DED, while South Korea, Japan, India, and UK also play chromatic roles demonstrating their respective technical prowess and research emphasis on advanced manufacturing techniques like DED. It is worth noting that these dynamics are subject to change over time, influenced by evolving research economic conditions, priorities, and governmental strategies.

3.2. Publication Type Analysis

On the DED technique, a variety of materials including basic research articles, proceedings papers, meeting abstracts, and review papers have been published. As can be seen in Figure 3 of this research article, it has the highest contribution compared to other publication types, with about 86%. There are a number of reasons confirming that research articles about Direct Energy Deposition (DED) predominate in journals.

Firstly, in academic environment, research publications are mostly the main format for publishing new and novel achievements. Researchers like to share their original results in the format of research articles in the case of DED, which includes novel and changing technology. This structure enables a thorough and in-depth investigation of the topic, allowing researchers to present their results in a solid and academic way. Research publications also benefit from the peer review process, which guarantees a level of quality and credibility that may be lacking in other forms of publication. Research articles are particularly important in furthering the cutting-edge techniques and understanding related to DED, although proceedings papers, meeting abstracts, and review papers have their own significance in summarizing and contextualizing current knowledge. This emphasis on research articles likely stems from the field’s aspiration for continuous innovation and the need to establish a robust foundation for further advancements.

3.3. Distribution of Publications over the Years

The number of publications per year helps to evaluate the overall progress in the field of DED technique all around the world. Figure 4 elucidates the annual number of publications extracted from the WoS database. The achieved results reveal that from 1973 to 2015, there was moderate growth, and from 2015 to 2024, there was a severe enhancement in the number of publications. From 2024 until 2025, there has been a sharp decrease because the mentioned year (March 2025) is not yet over, and the data was extracted for 3 months. Based on the achieved results, it is expected that the number of publications will increase in 2025; because till March 2025, it has about one-fourth of 2024’s publications and has also kept the previous upward trend, and is expected to continue following the trend from 2024. Also,

Table 2. Number of publications per year.

Year	Number of Publications	Percentage
2025	190	4.931%
2024	870	22.580%
2023	609	15.806%
2022	471	12.224%
2021	399	10.356%
2020	265	6.878%
2019	193	5.009%
2018	157	4.075%
2017	77	1.998%
2016	54	1.402%
2015	20	0.519%
2014	29	0.753%
2013	22	0.571%
2012	28	0.727%
2011	49	1.272%
2010	29	0.753%
2009	29	0.753%
2008	18	0.467%
2007	39	1.012%
2006	23	0.597%
2005	25	0.649%
2004	18	0.467%
2003	23	0.597%
2002	10	0.260%
2001	11	0.285%
2000	19	0.493%

shows the number of publications per year in detail.

3.4. Keywords Analysis

By using CiteSpace, the co-occurrence of keywords in academic papers on the DED technique was also examined; the results are given in

Table 3. Keyword co-occurrence analysis via CiteSpace.

Rank	Freq	Burst	Burst Begin	Burst Begin	Degree	Centrality	Sigma	Label	Year
1	625	15.69	2014	2018	43	0.13	7.29	Additive Manufacturing	2014
2	335	32.3	2012	2019	24	0.03	2.47	Laser Metal Deposition	2012
3	113	16.33	2010	2018	31	0.07	2.99	Fabrication	2010
4	109	4.06	2012	2018	19	-	1.01	Components	2012
5	53	4.44	2018	2020	14	-	1	Optimization	2018
6	52	7.7	2005	2019	17	0.01	1.08	Direct Metal Deposition	2005
7	46	5.53	2020	2021	10	0.01	1.05	Ti-6al-4v	2020
8	45	0			15	-	1	Tensile Property	2020
9	45	7.44	2010	2019	13	0.01	1.07	Laser Cladding	2010
10	45	5.88	2020	2021	9	-	1.02	Prediction	2020
11	28	9.54	1991	2007	31	0.49	44.41	Growth	1991
12	27	9.71	2009	2020	7	0.01	1.13	Laser Deposition	2009
13	25	16.36	1991	2011	12	0.08	3.58	Thin Films	1991
14	24	5.41	2021	2023	12	0.01	1.06	Mechanical Property	2021
15	23	5.18	2021	2023	3	-	1	Directed Energy Deposition (DED)	2021
16	22	14.35	1992	2013	17	0.18	10.41	Films	1992
17	16	6.58	2018	2020	6	-	1	Wear Resistance	2018
18	14	7.78	2018	2019	11	-	1.01	Inconel 625	2018
19	6	4.05	1994	2006	9	0.01	1.05	Surface	1994
20	6	4	1998	2011	2	-	1	Pulsed Laser Deposition	1998

. It is worth noting that 20 of the most-used keywords are given in the table because the frequency of the other keywords was negligible compared to the mentioned keywords. As shown in Table 3, “Additive Manufacturing”, ” Laser Metal Deposition”, and “Fabrication” are the most widely used keywords compared to other keywords with 635,313 and 113 frequencies, respectively, in most publications. Afterwards, keywords such as “Components”, “Optimization”, and “Direct Metal Deposition” gained the most frequencies with 109, 53, and 52, respectively, which are highlighted in yellow. In terms of citation burst, “Thin films” has the highest score (16.33) compared to the other keywords starting in 1991 and finishing in 2011 that are highlighted in green. Moreover, keywords such as “Growth”, “Additive Manufacturing”, and “Films” achieved the highest centrality.

Also, it is seen that the most important keywords appeared after 2013. Due to their widespread applicability and transformational potential, “Additive Manufacturing” and “Laser Metal Deposition” are recognized as crucial developments in manufacturing. The increase in frequency between 2015 and 2022 probably reflects a time of greater interest and research activity fueled by advancements in technology and more industrial use. The attention on keywords like “Component” and “Optimization” demonstrates a trend toward improving particular manufacturing operations indicating the field’s development. A considerable period of innovation or advancements in thin film deposition processes or applications is also indicated by the popularity of “Thin films” in citation bursts from 1991 to 2011. Last but not least, the dominance of terms like “Growth,” “Additive Manufacturing,” and “Films” emphasizes how important they are to the discourse surrounding additive manufacturing and related technologies. These terms play critical roles in connecting various concepts within the field.

It is worth noting that Figure 5 a shows the early research (1990s to early 2000s) focused on foundational technologies and processes such as “laser,” “decomposition,” and “thin films.” As the field matured around the mid-2000s, terms like “direct metal deposition,” “fabrication,” and “microstructure” began to emerge, reflecting a shift toward specific DED techniques and material behaviors. In more recent years (2015–2023), research has increasingly emphasized application-driven and performance-oriented topics such as “mechanical properties,” “strength,” and “evolution,” indicating a focus on optimization and practical implementation.

3.5. Author Analysis

The effects of authors and their collaborations were evaluated using their citation counts, citation bursts, betweenness centrality, and citation sigma after the completion of analysis on scientometry via CiteSpace software. The results achieved are given in

Table 4. Statistical analysis of most cited author via CiteSpace.

Rank	Author	Freq	Burst	Burst Begin	Burst End	Year
1	Lin, Xin	45	11.91	2019	2023	2019
2	Huang, Weidong	25	9.51	2020	2023	2020
3	Liou, Frank	23	0			2009
4	Paul, C P	16	7.11	2019	2021	2019
5	Bindra, K S	16	7.11	2019	2021	2019
6	Jinoop, A N	15	6.66	2019	2021	2019
7	Chen, Jing	12	4.49	2020	2023	2020
8	Liu, Weijun	12	6.37	2007	2014	2007
9	Tsuchiya, T	11	6.82	2004	2007	2004
10	Kumagai, T	11	6.82	2004	2007	2004
11	Tan, Hua	11	4.11	2020	2023	2020
12	Li, Wei	11	0			2022
13	Koike, Ryo	11	6.26	2018	2019	2018
14	Landers, Robert G	10	5.65	2009	2014	2009
15	Dzugan, Jan	10	0			2022
16	Kakinuma, Yasuhiro	10	5.69	2018	2019	2018
17	Kaplan, Alexander F H	9	4.18	2021	2023	2021
18	Hu, Yunlong	8	0			2021
19	Daoudi, K	8	5.07	2005	2007	2005
20	Noda, M	8	5.2	1999	2001	1999

and Figure 6. Based on the results achieved, the top-ranked author is Lin, Xin with a citation count of 45 in 2019. The second one is Huang, Weidong with a citation count of 25 in 2020. The third one is Liou, Frank with a citation count of 23 in 2009. The fourth is Paul, C P with a citation count of 16 in 2019. The fifth is Bindra, K S with a citation count of 16 in 2019. The sixth is Jinoop, A N with citation count of 15 in 2019. This map indicates that the LMD/DED field has several central author hubs with Lin Xin’s team playing a dominant role in pushing the field forward. The reduced threshold allows emerging researchers to be visualized, indicating a growing base of contributing authors and international involvement. Then burst analysis was implemented, and the results are as follows: Lin, Xin has the highest burst rate with 11.91 within the period of four years from 2019 to 2023, followed by Huang, Weidong with 9.51 burst rate in the period of three years from 2020 to 2023. It is worth noting that authors with the highest citation count are highlighted in yellow, and the burst was highlighted in green. It worth noting that the full table is provided in the Supplementary Materials.

3.6. Cited Journal

In this section, the most cited journal is analyzed by CiteSpace and VOSviewer. The analysis was carried out according to the main characteristics, namely citation number, citation burst, citation sigma, and betweenness centrality, shown in

Table 5. Statistical analysis of cited journal and its characteristic via CiteSpace.

Rank	Freq	Burst	Burst Begin	Burst End	Centrality	Sigma	Journal	Year
1	1121	0			0.06	1	Addit Manuf	2015
2	900	8.46	2014	2018	0.06	1.66	Mater Design	2011
3	892	4.96	2009	2016	0.25	2.98	Mat Sci Eng A-Struct	2005
4	716	15.78	2013	2018	0.04	1.97	J Mater Process Tech	2003
5	656	0			0.08	1	Opt Laser Technol	2007
6	628	0			0.07	1	Acta Mater	2012
7	620	0			0.04	1	J Alloy Compd	2013
8	605	0			0.06	1	Int J Adv Manuf Tech	2013
9	521	0			0.05	1	J Manuf Process	2006
10	427	0			0.04	1	Materials	2016
11	398	17.45	2009	2017	0.04	1.96	Surf Coat Tech	2006
12	365	0			0.06	1	Metals-Basel	2017
13	353	0			0.01	1	Prog Mater Sci	2015
14	294	0			0	1	Mater Charact	2012
15	293	0			0.01	1	J Mater Sci Technol	2012
16	293	18.37	2005	2018	0.03	1.68	J Laser Appl	2001
17	265	0			0.06	1	Mater Lett	1996
18	264	0			0.02	1	Scripta Mater	2014
19	254	58.71	1995	2017	0.18		Appl Surf Sci	1995
20	253	6.17	2017	2019	0.02	1.13	Jom-Us	2015

. Also, Figure 7 shows the graphical observation of the cited journal. It is seen that Additive Manufacturing journal (2015) is the top-ranked journal among the other journals in Cluster #2 with a citation count of 1121. The second one is the Materials & Design journal (2011), with a citation count of 900 in Cluster #1. Materials Science and Engineering: A (2005), which received 892 citations in Cluster #1, came in third. The fourth, with 716 citations, is Journal of Materials Processing Technology (2003) in Cluster #1. The journal distribution shows a transition from core physics and metallurgical journals to a more applied, interdisciplinary publishing environment reflecting the technological and industrial maturity of DED. It is worth noting that the highest frequency, burst, and centrality were highlighted in yellow, green, and red, respectively. The Additive Manufacturing journal’s popularity in Cluster #2 is a sign of the journal’s substantial influence and contributions to the field. This may be linked to its emphasis on cutting-edge manufacturing methods like DED, which have attracted a lot of attention recently due to their potential to change several industries. Similar to this, the Materials & Design journal in Cluster #1 with 900 citations has probably made significant contributions to the larger field of materials science and design, which frequently overlaps with DED technologies. The publications in Cluster #1, Materials Science and Engineering: A and the Journal of Materials Processing Technology, are both well-known in the field of materials science and are known for publishing high-quality research, which includes studies on DED. This timeline clearly reflects a three-decade evolution from basic research to industrial application, paralleling the technological maturation of DED. The explosion of AM journals post-2015 suggests a commercialization phase in the field. The full table is provided in the Supplementary Materials.

3.7. Category

In this section, the category of publication is investigated. The results achieved are shown in Figure 8 and

Table 6. Statistical analysis of categories in DED process via CiteSpace.

Freq	Burst	Begin	End	Degree	Centrality	Sigma	Category	Year
1250	0			26	0.33	1	Materials Science, Multidisciplinary	1989
645	66.81	1977	2010	20	0.15		Physics, Applied	1977
624	0			19	0.23	1	Engineering, Manufacturing	1996
521	0			12	0.04	1	Metallurgy And Metallurgical Engineering	2000
300	20.65	2005	2018	17	0.13	12.31	Optics	1979
211	4.78	1994	2007	11	0.12	1.69	Chemistry, Physical	1985
198	12.58	2006	2018	23	0.41	73.46	Engineering, Mechanical	2004
184	29.05	1989	2007	12	0.03	2.23	Physics, Condensed Matter	1989
142	0			14	0.04	1	Nanoscience And Nanotechnology	1987
141	22.78	1985	2012	11	0.04	2.41	Materials Science, Coatings And Films	1973
136	0			8	0.01	1	Automation, And Control Systems	2009
91	30.94	1978	2014	19	0.14	60.59	Engineering, Electrical And Electronic	1978
79	10.39	2013	2018	5	0.01	1.06	Engineering, Industrial	2011
45	0			17	0.25	1	Engineering, Multidisciplinary	2016
38	0			6	0.01	1	Chemistry, Multidisciplinary	1996
32	0			16	0.19	1	Instruments And Instrumentation	1991
32	0			10	0.09	1	Mechanics	2018
28	0			7	0.01	1	Materials Science, Characterization And Testing	2020
14	0			2	0.03	1	Engineering, Chemical	2012
14	0			0	0	1	Materials Science, Ceramics	2009

. The most used categories are classified as follows: Multidisciplinary Materials Science, (burst rate 0 and frequency of 1250), Applied Physics (burst rate 66.81 and frequency of 645), Manufacturing Engineering (burst rate 0 and frequency of 624), Metallurgy and Metallurgical Engineering (burst rate 0 and frequency of 521), Optics (burst rate 20.65 and frequency of 300), Physical Chemistry (burst rate 4.78 and frequency of 211), Mechanical Engineering (burst rate 12.58 and frequency of 198), Physics, Condensed Matter (burst rate 29.05 and frequency of 148), and Nanoscience and Nanotechnology (burst rate 0 and frequency of 142). It is worth noting that categories with the highest frequency, burst, and centrality were highlighted in yellow, green, and red, respectively. “Multidisciplinary Materials Science” emerges as a prominent category due to its broad applicability in understanding and developing materials for DED processes.

Given that DED involves the deposition of various materials, including metals and alloys, a comprehensive understanding of material properties is paramount. “Applied Physics” garners significant attention, particularly during bursts, indicating periods of intense interest likely driven by groundbreaking advancements in applying physical principles to optimize DED techniques. This is especially relevant as DED often relies on precise control of energy deposition, making applied physics a critical discipline. The roots of the manufacturing process are formed by “Manufacturing Engineering” and “Metallurgy and Metallurgical Engineering,” especially in the context of DED, which includes detailed layer-by-layer deposition of materials. Due to the critical role that lasers and optical systems play in DED, “Optics” becomes more significant. Optics innovations may improve the deposition process’ accuracy and efficiency. While “Mechanical Engineering” focuses on the mechanical aspects including the design and optimization of DED processes, “Physical Chemistry” plays an important role in knowing and manipulating chemical processes related to material deposition.

The field’s structure, Figure 8a, is technically dense and engineering-centric, built on foundational materials science and physics but expanding into automation and advanced controls. The overlap between categories shows a rich cross-disciplinary knowledge flow. The timeline, Figure 8b, demonstrates a clear disciplinary progression moving from theoretical foundations in physics and chemistry to advancements in materials and mechanical engineering, and eventually transitioning to automation, sensors, and intelligent systems. This evolution reflects the real-world shift from work conducted in experimental laboratories to practical industrial applications culminating in the current phase of Industry 4.0 integration. The full table is provided in the Supplementary Materials.

3.8. Institute of Publication

In this part, the institute with the highest number of research outputs is given and elaborated in Figure 9 and

Table 7. Statistical analysis of institutional analysis via CiteSpace.

Rank	Freq	Burst	Burst Begin	Burst End	Centrality	Sigma	Institute	Year
1	79	8.23	2012	2019	0.14	2.9	Fraunhofer Gesellschaft	2012
2	76	12.68	2020	2023	0.12	4.01	Northwestern Polytechnical University	2019
3	51	4.09	2021	2023	0.12	1.59	United States Department of Energy (DOE)	1973
4	44	6.53	2019	2021	0.04	1.26	Northeastern University—China	2019
5	40	5.79	2005	2017	0.01	1.08	Missouri University of Science & Technology	2005
6	37	8.86	1991	2014	0.06	1.73	Chinese Academy of Sciences	1991
7	35	13.41	2015	2018	0	1	Pennsylvania Commonwealth System of Higher Education (PCSHE)	2015
8	29	7.42	2020	2021	0.03	1.21	Indian Institute of Technology System (IIT System)	2020
9	27	0			0.02	1	Dalian University of Technology	2020
10	26	7.79	2017	2019	0.04	1.34	Russian Academy of Sciences	1996
11	25	13.04	2015	2018	0	1	Pennsylvania State University	2015
12	24	7.96	2009	2019	0	1	University of Missouri System	2009
13	23	6.95	2021	2023	0	1	Central South University	2021
14	22	0			0	1	Korea Institute of Industrial Technology (KITECH)	2016
15	22	6.64	2021	2023	0	1	National Institute of Technology (NIT System)	2021
16	21	5.33	2019	2020	0	1	University of California System	2019
17	21	11.63	2003	2014	0	1	N8 Research Partnership	2003
18	20	10.36	2015	2018	0	1	Pennsylvania State University—University Park	2015
19	20	0			0	1	Harbin Institute of Technology	2016
20	17	10.84	2004	2010	0	1	National Institute of Advanced Industrial Science & Technology (AIST)	2004

. As it can be observed, Fraunhofer Gesellschaft in Germany is the top-ranked institute compared to other countries, with a frequency of 79 and a burst rate of 8.23. In second place, Northwestern Polytechnical University in China has a frequency of 76 and a burst of 12.68. The United States Department of Energy (DOE) follows with 51 frequencies, a burst rate of 4.09, and a centrality rate of 0.12. It is worth noting that categories with the highest frequency, burst, and centrality were highlighted with yellow, green, and red, respectively. It is observed that based on the countries contributing, China, the USA, and Germany are the leaders, which is verified by the statistical analysis of institutional observation. According to the statistical analysis for institutes, Fraunhofer Gesellschaft (in Germany), Northwestern Polytechnical University (in China), and the United States Department of Energy (in the USA) stand out as top contributors.

The fact that Fraunhofer Gesellschaft is the foremost organization in Germany is probably due to the nation’s longstanding reputation for precision engineering and cutting-edge manufacturing techniques. Being a recognized applied research institution that places a high value on innovation and industrial partnership, the Fraunhofer Gesellschaft is a role model in a cutting-edge industry like DED. China has made a concerted effort to invest extensively in research and development, notably in high-tech fields like additive manufacturing, and this has resulted in the rise of Northwestern Polytechnical University. Research institutions like Northwestern Polytechnical University have been inspired to play a leading role in the development of innovative manufacturing technologies as a result of China’s strategic initiatives such as the “Made in China 2025” plan. Due to its vast resources and research infrastructure, the US Department of Energy (DOE) is a prominent player.

4. Practical Implications

This scientometric analysis of Directed Energy Deposition (DED) provides several key insights with practical implications for the additive manufacturing industry.

• Leading Countries:

China emerges as the most significant contributor to DED research, highlighting its central role in advancing the field. This leadership position suggests opportunities for international collaboration, particularly in forming research partnerships and knowledge exchange programs with Chinese institutions. For global stakeholders, understanding China’s dominance enables more strategic engagement in joint ventures and technology-sharing initiatives.

• Core Keywords and Research Trends:

The frequent appearance of keywords such as “Additive Manufacturing”, “Laser Metal Deposition”, and “Fabrication” underscores the current focus areas within the DED domain. These terms reflect both the technological emphasis and evolving priorities in the field. Researchers and industry leaders can use these insights to prioritize investments and allocate resources toward high-impact areas, particularly laser-based deposition technologies and advanced fabrication methods that align with market and research trends.

• Influential Researchers:

Prominent authors like Lin Xin and Huang Weidong have been identified as the most prolific contributors. Their work represents valuable reference points for future studies and applied research. These individuals could be considered for expert consultations, keynote speaking roles, or collaborative research projects, especially for organizations looking to deepen expertise in DED.

• Key Institutions and Publication Venues:

Highly cited journals such as Additive Manufacturing and Materials Science and Engineering: A are pivotal publication outlets in the DED space. Furthermore, leading institutions including the U.S. Department of Energy, Fraunhofer Gesellschaft, and Northwestern Polytechnical University stand out as central hubs of knowledge. These organizations may serve as strategic partners for industrial R&D, prototype development, and applied training programs, reinforcing the importance of institutional collaboration in DED innovation.

• Policy and Strategic Recommendations:

The study’s analysis of clustering patterns, co-authorship networks, and country-level collaborations offers actionable insights for policymakers and funding bodies. By identifying strong regional hubs and existing gaps in international cooperation, this data supports more balanced and globally integrated research strategies. Targeted investments in underrepresented areas and reinforcement of high-collaboration regions could enhance global innovation capacity.

Overall, this study functions as a valuable decision-support tool for academics, businesses, and policy planners. It not only maps the current landscape of DED innovation but also highlights where future opportunities and collaborations are most likely to emerge. Through its comprehensive analysis, the research supports strategic planning across academic, industrial, and policy-making sectors within the additive manufacturing ecosystem.

5. Conclusions

In the current study, a scientometric analysis of the DED process has been carried out using CiteSpace and VOS software. A total of 3853 documents was used as a database from WoS to analyze the database. It was observed that China, the USA, and Germany are the leaders in global scientific contributions with the highest number of publications and institutes. Also, most documents were published in the article and are proceeding in paper format with increasing frequency each year. Regarding the keywords, “Additive Manufacturing”, “Laser Metal Deposition”, and “Fabrication” are the most commonly used keywords in the published papers. According to the journal, Additive Manufacturing, Materials & Design, and Materials Science and Engineering A are the most cited journals in the field of DED. Lastly, the most used categories are Material Engineering and Physics.