These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
118 related articles for article (PubMed ID: 38139639)
21. Process Window for Highly Efficient Laser-Based Powder Bed Fusion of AlSi10Mg with Reduced Pore Formation. Leis A; Weber R; Graf T Materials (Basel); 2021 Sep; 14(18):. PubMed ID: 34576480 [TBL] [Abstract][Full Text] [Related]
22. Continuous Comprehensive Monitoring of Melt Pool Morphology Under Realistic Printing Scenarios with Laser Powder Bed Fusion. Vallabh CKP; Zhao X 3D Print Addit Manuf; 2023 Feb; 10(1):101-110. PubMed ID: 36998791 [TBL] [Abstract][Full Text] [Related]
23. In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks. Ye D; Hsi Fuh JY; Zhang Y; Hong GS; Zhu K ISA Trans; 2018 Oct; 81():96-104. PubMed ID: 30054038 [TBL] [Abstract][Full Text] [Related]
24. Keyhole Formation by Laser Drilling in Laser Powder Bed Fusion of Ti6Al4V Biomedical Alloy: Mesoscopic Computational Fluid Dynamics Simulation versus Mathematical Modelling Using Empirical Validation. Ur Rehman A; Mahmood MA; Pitir F; Salamci MU; Popescu AC; Mihailescu IN Nanomaterials (Basel); 2021 Dec; 11(12):. PubMed ID: 34947634 [TBL] [Abstract][Full Text] [Related]
25. Laser Powder Bed Fusion of Chromium Bronze Using Recycled Powder. Pelevin IA; Burmistrov MA; Ozherelkov DY; Shinkaryov AS; Chernyshikhin SV; Gromov AA; Nalivaiko AY Materials (Basel); 2021 Jun; 14(13):. PubMed ID: 34208840 [TBL] [Abstract][Full Text] [Related]
26. Deep Learning Applied to Defect Detection in Powder Spreading Process of Magnetic Material Additive Manufacturing. Chen HY; Lin CC; Horng MH; Chang LK; Hsu JH; Chang TW; Hung JC; Lee RM; Tsai MC Materials (Basel); 2022 Aug; 15(16):. PubMed ID: 36013797 [TBL] [Abstract][Full Text] [Related]
27. Reuse of Ti6Al4V Powder and Its Impact on Surface Tension, Melt Pool Behavior and Mechanical Properties of Additively Manufactured Components. Skalon M; Meier B; Leitner T; Arneitz S; Amancio-Filho ST; Sommitsch C Materials (Basel); 2021 Mar; 14(5):. PubMed ID: 33800747 [TBL] [Abstract][Full Text] [Related]
28. Mesoscopic Simulation of Core-Shell Composite Powder Materials by Selective Laser Melting. Bao T; Tan Y; Xu Y Materials (Basel); 2023 Nov; 16(21):. PubMed ID: 37959603 [TBL] [Abstract][Full Text] [Related]
29. Melt Pool Changes Characterization in Laser-Processed H11 Hot Work Tool Steel Using Point-by-Point Scanning Mode towards LPBF Process Optimization. Fryzowicz K; Bardo R; Dziurka R; Kawałko J; Cios G; Stwora A; Bała P Materials (Basel); 2024 Sep; 17(18):. PubMed ID: 39336372 [TBL] [Abstract][Full Text] [Related]
30. Evaluation of Inconel 718 Metallic Powder to Optimize the Reuse of Powder and to Improve the Performance and Sustainability of the Laser Powder Bed Fusion (LPBF) Process. Gruber K; Smolina I; Kasprowicz M; Kurzynowski T Materials (Basel); 2021 Mar; 14(6):. PubMed ID: 33801106 [TBL] [Abstract][Full Text] [Related]
31. Laser Powder Bed Fusion (LPBF) of In718 and the Impact of Pre-Heating at 500 and 1000 °C: Operando Study. Ur Rehman A; Pitir F; Salamci MU Materials (Basel); 2021 Nov; 14(21):. PubMed ID: 34772210 [TBL] [Abstract][Full Text] [Related]
32. In Situ Monitoring of Powder Bed Fusion Homogeneity in Electron Beam Melting. Grasso M Materials (Basel); 2021 Nov; 14(22):. PubMed ID: 34832415 [TBL] [Abstract][Full Text] [Related]
33. An Empirical Approach for the Development of Process Parameters for Laser Powder Bed Fusion. Pfaff A; Jäcklein M; Schlager M; Harwick W; Hoschke K; Balle F Materials (Basel); 2020 Nov; 13(23):. PubMed ID: 33261091 [TBL] [Abstract][Full Text] [Related]
34. On thermal properties of metallic powder in laser powder bed fusion additive manufacturing. Zhang S; Lane B; Whiting J; Chou K J Manuf Process; 2019; 47():. PubMed ID: 32855624 [TBL] [Abstract][Full Text] [Related]
35. Predictive modeling and optimization of multi-track processing for laser powder bed fusion of nickel alloy 625. Criales LE; Arısoy YM; Lane B; Moylan S; Donmez A; Özel T Addit Manuf; 2017 Jan; 13():. PubMed ID: 38487077 [TBL] [Abstract][Full Text] [Related]
36. Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion. Harbig J; Wenzler DL; Baehr S; Kick MK; Merschroth H; Wimmer A; Weigold M; Zaeh MF Materials (Basel); 2022 Feb; 15(3):. PubMed ID: 35161208 [TBL] [Abstract][Full Text] [Related]
38. Simultaneous Pore Detection and Morphological Features Extraction in Laser Powder Bed Fusion with Image Processing. Li J; Zhang X; Ma F; Wang S; Huang Y Materials (Basel); 2024 Mar; 17(6):. PubMed ID: 38541527 [TBL] [Abstract][Full Text] [Related]
39. Convolutional neural network analysis of recurrence plots for high resolution melting classification. Ozkok FO; Celik M Comput Methods Programs Biomed; 2021 Aug; 207():106139. PubMed ID: 34029831 [TBL] [Abstract][Full Text] [Related]
40. Roughness and Near-Surface Porosity of Unsupported Overhangs Produced by High-Speed Laser Powder Bed Fusion. Shange M; Yadroitsava I; du Plessis A; Yadroitsev I 3D Print Addit Manuf; 2022 Aug; 9(4):288-300. PubMed ID: 36660231 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]