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Open research questions in Additive Manufacturing Materials and Processes

39 unresolved questions extracted from the limitations and future-work sections of 387 Additive Manufacturing Materials and Processes papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Future work should investigate the differences in strengthening mechanisms between thick and thin layers by quantifying microstructural features across multiple length scales, such as grain size, primary dendrite arm spacing, dislocation density, and segregation coarseness, as well as the microstructural evolution within transition zones to clarify the competing effects of deposition height, thermal cycling, deposition sequence, and energy input.

    Deposition Height Prediction in Directed Energy Deposition · 2026 · DOI

  • Although such additions are known to promote grain refinement, their influence on alloy processability and on the L-PBF processing window remains insufficiently quantified.

    Process understanding and optimization of nano-TiC powder surface functionalization for improved L-PBF printability of AA2017 alloy · 2026 · DOI

  • While alloying elements such as Zn, Mg, Si, and Cu are common, Al-Sn alloys (typically used in plain bearing applications) remain under-investigated as L-PBF feedstock.

    Process parameter investigation and mechanical characterization of an Al-Sn-Cu-Ni alloy manufactured by laser powder bed fusion · 2026 · DOI

  • and https://doi.org/10.3390/met15020158 Lucia, O., Maussion, P., Dede, E. J., & Burdio, J. M. (2014). Induction heating technology and its applications: Past developments, current technology, and future challenges.

    Design and Simulation of an Ultrasonic–Induction Hybrid System for Aluminium Foil Fusion in Additive Manufacturing · 2026 · DOI

  • The conference contributions suggest that the next stage of development will depend on a closer link between simulation outputs and experimental feedback. Process maps, compensation strategies, and defect predictions are valuable only when calibrated against measured distortions, microstructures, porosity, and mechanical behaviour. For L-PBF parts, this means that future work should integrate powder characterisation, melt-pool stability, thermal history, phase evolution, and surface quality into a single workflow [12,13,27-31]. Such an approach can reduce the number of failed builds and also shorten the time required to transfer laboratory knowledge to industrial production. A similar tendency can be expected in joining and sheet processing. The results for Litecor and HX300LAD sheets show that joint quality depends on the interaction among material thickness, formability, coating, adhesive layer, and tool geometry [5,6]. Future research will therefore combine mechanical testing with metallographic inspection, numerical simulation and long-term evaluation of fatigue, corrosion and environmental stability. These requirements are especially relevant for transport applications, where lightweight structures must meet both safety and durability criteria while maintaining acceptable production costs. From a broader perspective, KSIT 2025 showed that the sustainable development of advanced manufacturing requires cooperation among universities, research clusters, and industrial partners. Metal AM may reduce material waste and enable topology-optimised parts, while hybrid joining and lightweight design can contribute to lower mass and improved functional integration [6,14,29]. However, these benefits are achieved only when the process is robust, reproducible, and supported by people who can communicate technical findings across disciplines. This is why the Fellexcel round table and the AI-supported communication contribution formed an important complement to the materialsoriented lectures [1,2,7].

    FellExcel: advanced technologies, additive manufacturing and simulation-driven innovation · 2026 · DOI

  • To evaluate and compare steel in terms of their supply chain resilience, a key performance indicator Resilience Factor has been introduced, which is based on the specific chemi- cal composition (CC) of a material. Taking a Germany-cen- tric perspective as an example, this contribution assumes the fact that certain elements, such as Co and W, are often mined in politically semi-stable regions and elements such as Ni will be in significantly higher demand in the future. On this basis, three materials with varying resilience fac- tors and hardness promises were selected, processed using PBF-LB/M, and mechanically characterized. The key find- ings are: ● Even though C is one of the most important alloying elements for the hardenability of steels, there is no con- tinuous trend between the C-content and the resulting hardness of components in the as-built condition across different materials. Furthermore, no significant change could be detected between hardness and increased C- content under otherwise identical CC conditions (1.7218 / 1.7225 / 1.7228), as is the case with other materials [53]. ● When comparing materials with similar CC (1.7218 / 1.7225 / 1.7228), it becomes apparent that an increased C-content leads to an improvement in performance in terms of strength values (UTS + 14% / + 20%) and im- pact toughness (+ 12%) ● The selection of materials shows that comparable or bet- ter mechanical properties can also be achieved in the as- built condition with the more resilient steel 1.7228 than with high-alloyed tool steels 1.4125 and 1.2709. This means that a material substitution in general is possible. ● Even materials that are considered difficult to weld can be processed using PBF-LB/M without the need for preheating. This generally results in the same or even higher performance values in terms of component load capacity. This may be due to reduced internal stresses resulting from the smaller size of the used machines and the lower energy input during melting (line energy 1.7225: 0.3 J/mm, 1.7228: 0.22 J/mm). However, this statement needs to be verified [54]. Further work is needed to establish this possibility of mate- rial substitution. This includes, among other things: ● Further investigations on cracking mechanisms for 1.4125 to prove that the found cracks are not a general problem. ● Review and comparison of the mechanical properties of 1.4125 and 1.7228 in the heat-treated state ● Evaluation of the resulting microstructure to provide ad- ditional insights and to verify the previous direct com- parison between 1.7225 and 1.7228 as well as the influ- ence of the C-content of the hardening mechanism. ● Evaluation of the residual stresses of 1.7228 in order to confirm the statement regarding the crack susceptibility. ● An AI-supported approach to expand the parameter win- dow for material 1.7228 and, if necessary, further in- crease the as-built mechanical properties. ● Creation of real-world applications for material substi- tution to test the performance of resilient materials in comparison to currently in use materials. Especially in light of the tendency of 1.4125 to work hardening and the resulting applications ● Extent the definition of the resilience factor to make it a fit also for non-steel materials or for applications where a minimum Cr-content for corrosion resistance is needed. The authors have no competing interests to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organi- zation or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article. Data sets generated during the current study are available from the corresponding author on reasonable request.

    A novel approach to resilience in cold-work applications: experimental comparison of the as-built mechanical properties of high-alloy 1.2709, high-alloy 1.4125 and low-alloy 1.7228 produced using PFB-LB/M · 2026 · DOI

  • Conventional nominal stress, hot spot stress, and effective notch stress methods are evaluated for rough WAAM specimens, but their applicability is limited by the highly irregular and continuously varying surface geometry.

    Numeriek en experimenteel onderzoek naar het vermoeiingsgedrag van met wire arc additive manufacturing vervaardigde componenten · 2026

  • 1. Optimised welding parameters and ILT [9, 10, 12, 13, 18, 20, 21]. 2. Optimum cooling conditions to enhance α-y transformation for achieving a suitable phase balance [10, 18, 21,31-33, 36, 40]. 3. Alloy composition adjustment by suitable shielding gas combination, or special material or mechanism for enhanced mechanical and electrochemical properties [50, 52-54, 57]. 4. Post-process treatment [5, 38]. that Similarly, in the case of shielding gas combinations, literature shows these combinations could be instrumental for achieving desired characteristics in DSS structures deposited by the GMAW-AM process, as long as the combination employed complies with relevant standards [2]. Compared to other gases, N2 could be vital in promoting a suitable α-γ phase ratio, as it promotes austenisation of otherwise highly ferritic microstructure, especially in parts developed using a smaller number of layers [51, 53]. Special mechanism-assisted fabrication can be handy for overcoming an unbalanced phase ratio. Employment of secondary wire feed in addition to the primary filler wire favorably modified the overall alloy composition of DSS parts and their overall metallographic characteristics [57-59]. This method could alter the alloy improved Tehnički vjesnik 33, 3(2026), 1290-1299 1295 Uhamir PATRICK et al.: Review of Fabrication Methods Employed for 3D Printing DSS Parts using GMAW-AM Process: A Systematic Analysis composition to improve the overall or a particular mechanical property as dictated by the commercial requirements of fabricated parts. Besides the special mechanisms already employed and researched, future studies should explore additional mechanisms to assist the for example, deposition process, in-situ ultrasonic cold application, pressure vibration deformation, interpass rolling, etc., to achieve a tailored deposition geometry, grain growth, boundary formation, and α-γ distribution characteristics [63, 66]. assistance, The review analysis is summarised in the form of a suitable fabrication route for DSS parts by the GMAW-AM process, as both the cause and cure lie in the fabrication method employed, (Tab. 2).

    Review of Fabrication Methods Employed for 3D Printing DSS Parts using GMAW-AM Process: A Systematic Analysis · 2026 · DOI

  • Looking ahead, the convergence of several parallel technical developments is likely to reshape the landscape of ML-driven quality assurance for metal AM in ways that go well beyond incremental improvement on existing https://doi.org/10.53941/jmem.2026.100022 20 of 27 Ekengwu et al. J. Mech. Eng. Manuf. 2026 approaches. The following trends represent, in the authors’ assessment, the most consequential directions that the field will need to navigate over the coming five to ten years. Foundation models and transfer at scale. The emergence of large pre-trained foundation models in computer vision and multimodal learning opens a genuinely new possibility for AM defect detection: a single, massively pre-trained model that can be fine-tuned to a specific AM process, material, and sensor configuration with a fraction of the labelled data that current approaches require. Models in the GPT and CLIP lineage have already demonstrated remarkable cross-domain generalisation in natural image tasks; their adaptation to the structured, physics-governed imagery of AM monitoring is a near-term prospect rather than a distant aspiration. The critical research question is not whether such adaptation is possible but how much domain-specific data is needed to achieve industrially reliable performance, and whether the internal representations these models develop are physically meaningful or statistically coincidental—a distinction with profound implications for regulatory acceptance. Physics-ML co-design as a standard rather than a speciality. Physics-informed neural networks and hybrid data-physics models are currently treated as a specialised subfield pursued by groups with both ML and computational materials expertise. Over the coming decade, the expectation is that physical constraint integration will become a standard design requirement rather than an optional enhancement—driven by regulatory pressure, by the interpretability demands of certification bodies, and by the demonstrated performance advantages of models that cannot make physically impossible predictions. This shift will require changes in how AM-ML researchers are trained: the next generation of practitioners will need fluency in both machine learning methodology and the thermomechanical physics of rapid solidification, a combination that current educational programmes rarely provide. Closed-loop autonomous manufacturing systems. The trajectory of reinforcement learning and closed-loop adaptive control points toward AM machines that do not merely detect and report defects but actively prevent them—machines that learn from every build, accumulate process knowledge across materials and geometries, and autonomously optimise their own parameters within defined safety envelopes.

    Machine Learning for Process Optimization and Defect Detection in Metal Additive Manufacturing: A Critical Review of Algorithms, In-Situ Monitoring Strategies, and Quality Assurance Frameworks · 2026 · DOI

  • 7 Model limitations The present study employs a multiphysics CFD–DEM framework to investigate melt pool dynamics and powder bed stability in LPBF; however, several modeling assump- tions should be considered when interpreting the results.

    Multiphysics modeling of melt pool dynamics and powder bed stability in LPBF of inconel 718 for a circular cavity · 2026 · DOI

  • While the roughening strategy was validated on ASTM A36-SS316L bimetallic system, the optimal roughness range of 91.57 μm may not be universally applicable across other material combinations. The study lacks investigation into how material-specific properties (melting point, thermal conductivity, microstructural response) influence the optimal interfacial roughness for different dissimilar metal systems.

    Metal repair using hybrid additive manufacturing process: A comparative study of interfacial surface roughness for improved mechanical strength · 2026 · DOI

  • The study identified that beam reflection caused insufficient energy delivery at smooth interfaces (8.76 μm roughness), leading to defects such as partially melted powder and lack of fusion, but did not quantify the relationship between surface roughness and beam energy absorption or reflection coefficient in the hybrid additive manufacturing process.

    Metal repair using hybrid additive manufacturing process: A comparative study of interfacial surface roughness for improved mechanical strength · 2026 · DOI

  • The FE model was only applied to flat interfaces in bimetallic specimens under tensile loading. The authors explicitly identify the need to extend the model to non-flat interfaces with increased contact area and alternative repair geometries, which remain untested and would improve practical applicability to complex component repair scenarios.

    Metal repair using hybrid additive manufacturing process: A comparative study of interfacial surface roughness for improved mechanical strength · 2026 · DOI

  • The study observed that interface roughening improved yield strength by 36.36% and UTS by 64.23% in one metal system, but reduced ductility in the dissimilar metal system (ASTM A36-SS316L) with only 25.06% elongation versus 41.16% in substrate. The trade-off mechanism between strength and ductility across different metal pairs requires investigation with additional dissimilar metal combinations beyond the two tested systems.

    Metal repair using hybrid additive manufacturing process: A comparative study of interfacial surface roughness for improved mechanical strength · 2026 · DOI

  • The FE model is limited to interpreting mechanical responses of repaired components and cannot identify optimal surface roughness values for hybrid additive manufacturing repair. Future work must develop physics-based microstructural models that incorporate interfacial roughness parameters to determine the specific roughness range (between the tested 8.76 μm and 91.57 μm) that maximizes bonding strength.

    Metal repair using hybrid additive manufacturing process: A comparative study of interfacial surface roughness for improved mechanical strength · 2026 · DOI

  • The methodology for predictive assessment of mechanical properties using pole density distribution is validated only against literature data for similar materials, not against independent experimental datasets from WAAM Inconel 718 specimens with varied processing histories or post-processing treatments (heat treatment, machining allowance).

    Elastic Property Anisotropy in Inconel 718 Alloy Specimens Fabricated by Wire Arc Additive Manufacturing · 2026 · DOI

  • The elastic property anisotropy measurements (Young's modulus, shear modulus, Poisson's ratio) are reported for three orthogonal directions (X, Y, Z), but the paper lacks investigation of elastic properties at intermediate angles or analysis of the complete 6×6 elastic stiffness matrix to fully characterize anisotropic behavior in WAAM specimens.

    Elastic Property Anisotropy in Inconel 718 Alloy Specimens Fabricated by Wire Arc Additive Manufacturing · 2026 · DOI

  • The paper proposes using quantitative texture analysis to predict mechanical behavior under various loading schemes but provides no validation data for multiaxial loading conditions, cyclic loading, or in-service stress states relevant to the mentioned critical applications in military equipment repair.

    Elastic Property Anisotropy in Inconel 718 Alloy Specimens Fabricated by Wire Arc Additive Manufacturing · 2026 · DOI

  • While the paper demonstrates that Young's modulus reduction in the Z direction (perpendicular to deposition plane) reaches 10-11% in WAAM Inconel 718 and notes similar patterns in SLS-fabricated specimens, it does not systematically compare quantitative texture characteristics and mechanical property predictions between these two additive manufacturing technologies to establish technology-specific texture-property relationships.

    Elastic Property Anisotropy in Inconel 718 Alloy Specimens Fabricated by Wire Arc Additive Manufacturing · 2026 · DOI

  • The study establishes a correlation between pole density distribution (along [001]–[111] crystallographic diagonal) and elastic anisotropy in WAAM-fabricated Inconel 718, but does not experimentally validate this predictive methodology across different deposition parameters, layer heights, or wire feed rates that could alter crystallographic texture development.

    Elastic Property Anisotropy in Inconel 718 Alloy Specimens Fabricated by Wire Arc Additive Manufacturing · 2026 · DOI

  • Class 1, corresponding to medium energy density, exhibited the lowest F1 score and confidence level in prediction among the three classes due to morphological overlap with adjacent energy density classes and blurred class boundaries.

    Process-structure linkage for laser powder bed fusion using simulated microstructure images and deep learning · 2026 · DOI

  • This study aimed to provide basic understanding about the differences between the wear measurement methods on AM parts and serve further studies on measuring, predicting and preventing wear with more technological methods.

    Measurement of wear on additive manufactured surfaces via precision metrology and image processing techniques · 2024 · DOI

  • In addition, the challenges of PBF-produced parts are hot issues among stakeholders because parts are still insufficient to meet the strict requirements of high-tech industries.

    Current Status and Challenges of Powder Bed Fusion-Based Metal Additive Manufacturing: Literature Review · 2023 · DOI

  • Arc-driven powder bed fusion represents a low-cost alternative to beam-based powder bed systems, yet the morphological stability regimes governing single-track formation and the relative influence of process parameters on regime transitions have not been systematically characterised.

    Interpretable Machine Learning for Process Parameter Analysis in Arc-Driven Powder Bed Fusion of 316L Stainless Steel · 2026 · DOI

  • The use of existing repair methods, which are based on welding or surfacing using argon arc welding, for example for blades, is limited by the high susceptibility of heat-resistant nickel alloys (ЖС3ДК, ВЖЛ12) to the formation of heat-fatigue cracks due to the high content of γ´ phase.

    MICROPLASMA POWDER CLADDING FOR THE REPAIR OF TURBINE MONOWHEELS MADE OF NICKEL-BASED HEAT-RESISTANT ALLOYS · 2026 · DOI

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39 open questions have been extracted from the limitations and future-work passages of 387 Additive Manufacturing Materials and Processes papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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