Additive manufacturing最新文献

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Enhancing classical Scheil–Gulliver model calculations by predicting generated phases and corresponding compositions through machine learning techniques 通过机器学习技术预测生成的相位和相应的成分,从而改进经典的 Scheil-Gulliver 模型计算
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-09-05 DOI: 10.1016/j.addma.2024.104516
Zhengdi Liu, Wenwen Sun
{"title":"Enhancing classical Scheil–Gulliver model calculations by predicting generated phases and corresponding compositions through machine learning techniques","authors":"Zhengdi Liu,&nbsp;Wenwen Sun","doi":"10.1016/j.addma.2024.104516","DOIUrl":"10.1016/j.addma.2024.104516","url":null,"abstract":"<div><div>The classical Scheil-Gulliver model is an important tool for simulating non-equilibrium solidification processes in materials science, especially for rapid cooling processes such as additive manufacturing. However, the high computational intensity of the Scheil-Gulliver calculations through the <strong>CAL</strong>culation of <strong>PHA</strong>se <strong>D</strong>iagrams (CALPHAD) method, especially for complex alloys, limits its application in high-throughput scenarios. This study introduces a novel machine learning (ML)-based approach to enhance the calculation of the Scheil-Gulliver model, facilitating efficient and large-scale simulations. We developed a suite of ML models to predict generated phases and their elemental composition in the Fe-Ni-Cr-Mn system. By integrating these models with a parallel calculation algorithm, the calculation process is completed in 52 minutes, while performing direct one-by-one calculations could take months. Our high-throughput calculations successfully processed 176,688 out of 176,851 compositions. Based on the calculated data, an algorithm was designed for linear gradient pathway planning. Thirty pathways from the BCC_B2 phase to the FCC_L12 phase were used for exemplification, with 28 pathways validated as feasible.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"95 ","pages":"Article 104516"},"PeriodicalIF":10.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Toward 3D printability prediction for thermoplastic polymer nanocomposites: Insights from extrusion printing of PLA-based systems 热塑性聚合物纳米复合材料的三维打印性能预测:聚乳酸基体系挤压打印的启示
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-09-05 DOI: 10.1016/j.addma.2024.104533
Burcu Ozdemir , Miguel Hernández-del-Valle , Maggie Gaunt , Christina Schenk , Lucía Echevarría-Pastrana , Juan P. Fernández-Blázquez , De-Yi Wang , Maciej Haranczyk
{"title":"Toward 3D printability prediction for thermoplastic polymer nanocomposites: Insights from extrusion printing of PLA-based systems","authors":"Burcu Ozdemir ,&nbsp;Miguel Hernández-del-Valle ,&nbsp;Maggie Gaunt ,&nbsp;Christina Schenk ,&nbsp;Lucía Echevarría-Pastrana ,&nbsp;Juan P. Fernández-Blázquez ,&nbsp;De-Yi Wang ,&nbsp;Maciej Haranczyk","doi":"10.1016/j.addma.2024.104533","DOIUrl":"10.1016/j.addma.2024.104533","url":null,"abstract":"&lt;div&gt;&lt;div&gt;The development of new thermoplastic-based nanocomposites for, as well as using, 3D printing requires extensive experimental testing. One typically goes through many failed, or otherwise sub-optimal, iterations before finding acceptable solutions (e.g. compositions, 3D printing parameters). It is desirable to reduce the number of such iterations as well as exclude failed experiments that often require laborious disassembly and cleaning of the 3D printer. This issue could be addressed if we were able to understand, and ultimately predict ahead of experiments if a given material can be 3D printed successfully. Herein, we report on our investigations into forecasting the printing and resultant properties of polymer nanocomposites while encompassing both material properties and printing parameters, enabling the model to generalize across various thermoplastics and additives. To do so, nanocomposites of two different commercially available bio-based PLAs with varying concentrations of nanoclay (NC) and graphene nanoplatelets (GNP) were prepared using a twin-screw extruder. The thermal and rheological properties of the nanocomposites were analyzed. These materials were printed at varying temperature and flow using a pellet printer. The quality of the printing was evaluated by measuring weight fluctuation, internal diameter of cylindrical specimen, and surface uniformity. The interactions between material properties and printing parameters are complex but captured effectively by a machine learning model, specifically we demonstrate such a predictive model to forecast printability and, printing quality utilizing a Random Forest algorithm. Printability was predicted by developing a classification model with constraints based on the weight fluctuation (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;) of the printed sample w.r.t. the optimal print; defining “not printable” for &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;mo&gt;&lt;&lt;/mo&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;8&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and “printable” for &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;mo&gt;.&lt;/mo&gt;&lt;mn&gt;8&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. The classification model for predicting printability, performed well with an accuracy of 92.8% and identified flow index and complex viscosity, contributing 52% to the model’s importance. Another model to predict &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;mi&gt;W&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; of the only on successful prints also showed strong performance, emphasizing the importance of viscoelastic properties, thermal stability, and printing temperature. For diameter change (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;D&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;), the Random Forest model identified flow consistency index, complex viscosity, and thermal stability as influential parameters, with crystallization enthalpy gaining increased importance, reflecting its role in cryst","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"95 ","pages":"Article 104533"},"PeriodicalIF":10.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Volumetric 3D printing of ionic conductive elastomers for multifunctional flexible electronics 用于多功能柔性电子器件的离子导电弹性体体积三维打印技术
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-09-05 DOI: 10.1016/j.addma.2024.104536
Shuai Peng , Geming Chen , Xuan Luo , Xinghao Zhang , Dongya Li , Yibo Xu , Chonghao Sun , Erwei Shang , Xiaolong Wang , Yu Liu
{"title":"Volumetric 3D printing of ionic conductive elastomers for multifunctional flexible electronics","authors":"Shuai Peng ,&nbsp;Geming Chen ,&nbsp;Xuan Luo ,&nbsp;Xinghao Zhang ,&nbsp;Dongya Li ,&nbsp;Yibo Xu ,&nbsp;Chonghao Sun ,&nbsp;Erwei Shang ,&nbsp;Xiaolong Wang ,&nbsp;Yu Liu","doi":"10.1016/j.addma.2024.104536","DOIUrl":"10.1016/j.addma.2024.104536","url":null,"abstract":"<div><div>Flexible electronics based on ionic conductive elastomers (ICE) hold significant potential for applications in smart wearables, self-powered sensing, and human-computer interaction. However, current fabrication techniques constrain ICE-based ionic electronic components to simplified volumetric geometries, limiting their functionality. This work reports a volumetric 3D printing (V3DP) for fabricating flexible electronic components with excessive transparency, high conductivity, excellent thermal stability, and superior adhesion. By controlling the light dose, this printing technique enables precise modulation of the printed structures' mechanical properties. Furthermore, V3DP greatly improves the processing efficiency of high-viscosity ionic conductive liquids and makes it easier to prepare composite structures, combining different conductive mechanisms through unique overprinting. This study provides a promising strategy for preparing multifunctional, liquid-free, ionic flexible electronics, such as strain sensors and ionic-electronic triboelectric nanogenerators (iTENG).</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"95 ","pages":"Article 104536"},"PeriodicalIF":10.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Advancing laser powder bed fusion with non-spherical powder: Powder-process-structure-property relationships through experimental and analytical studies of fatigue performance 推进非球形粉末的激光粉末床融合:通过疲劳性能的实验和分析研究了解粉末-工艺-结构-性能之间的关系
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-09-05 DOI: 10.1016/j.addma.2024.104534
Mohammadreza Asherloo , Madhavan Sampath Ramadurai , Mike Heim , Dave Nelson , Muktesh Paliwal , Iman Ghamarian , Anthony D. Rollett , Amir Mostafaei
{"title":"Advancing laser powder bed fusion with non-spherical powder: Powder-process-structure-property relationships through experimental and analytical studies of fatigue performance","authors":"Mohammadreza Asherloo ,&nbsp;Madhavan Sampath Ramadurai ,&nbsp;Mike Heim ,&nbsp;Dave Nelson ,&nbsp;Muktesh Paliwal ,&nbsp;Iman Ghamarian ,&nbsp;Anthony D. Rollett ,&nbsp;Amir Mostafaei","doi":"10.1016/j.addma.2024.104534","DOIUrl":"10.1016/j.addma.2024.104534","url":null,"abstract":"<div><div>This study investigates the multifaceted interdependencies among powder characteristics (i.e., non-spherical morphology and particle size ranging 50–120 or 75–175 µm), laser powder bed fusion (L-PBF) process condition (i.e., contouring), post-process treatments (i.e., hot isostatic pressing (HIP) and mechanical grinding) on the pore, microstructure, surface finish, and fatigue behavior of additively manufactured Ti-6Al-4V samples. Microstructure analysis shows a phase transformation α′ → α+β microstructure after HIP treatment (at 899±14 °C for 2 h under the applied pressure of 1034±34 bar) of the as-built Ti-6Al-4V parts. The findings from pore analysis using micro-computed tomography (μ-CT) show an increase in sub-surface pores when relatively smaller powders are L-PBF processed including contouring. Surface optical profilometry reveals a decrease in surface roughness when fine powder is L-PBF including contouring. Pore analysis conducted through μ-CT reveals that the presence of lack-of-fusion pores within the L-PBF processed coarse powder is more pronounced when compared to the fine powder. Furthermore, HIP treatment does not eliminate these pores. The fracture failure in as-printed parts occurs at the surface, while the combination of HIP and mechanical grinding alters crack initiation to subsurface pore defects. Fractography reveals that HIP and as-built samples followed the facet formation and pseudo-brittle fracture mechanisms, respectively. Fatigue life assessments, supported by statistical analysis, indicate that mechanical grinding and HIP significantly enhanced fatigue resistance, approaching the benchmarks set by wrought Ti-6Al-4V alloy. A fatigue prediction model which considers the surface roughness as a micro-notch has been used.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"95 ","pages":"Article 104534"},"PeriodicalIF":10.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Local porosity prediction in metal powder bed fusion using in-situ thermography: A comparative study of machine learning techniques 利用原位热成像技术预测金属粉末床熔融过程中的局部孔隙率:机器学习技术比较研究
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-09-05 DOI: 10.1016/j.addma.2024.104502
Simon Oster, Nils Scheuschner, Keerthana Chand, Simon J. Altenburg
{"title":"Local porosity prediction in metal powder bed fusion using in-situ thermography: A comparative study of machine learning techniques","authors":"Simon Oster,&nbsp;Nils Scheuschner,&nbsp;Keerthana Chand,&nbsp;Simon J. Altenburg","doi":"10.1016/j.addma.2024.104502","DOIUrl":"10.1016/j.addma.2024.104502","url":null,"abstract":"<div><div>The formation of flaws such as internal porosity in parts produced by Metal-based Powder Bed Fusion with Laser Beam (PBF-LB/M) significantly hinders its broader industrial application, as porosity can potentially lead to part failure. Addressing this issue, this study explores the efficacy of in-situ thermography, particularly short-wave infrared thermography, for detecting and predicting porosity during manufacturing. This technique is capable of monitoring the part’s thermal history which is closely connected to the flaw formation process. Recent advancements in Machine Learning (ML) have been increasingly leveraged for porosity prediction in PBF-LB/M. However, previous research primarily focused on global rather than localized porosity prediction which simplified the complex prediction task. Thereby, the opportunity to correlate the predicted flaw position with expected part strain to judge the severity of the flaw for part performance is neglected. This study aims to bridge this gap by studying the potential of SWIR thermography for predicting local porosity levels using regression models. The models are trained on data from two identical HAYNES®282® specimens. We compare the effectiveness of feature-based and raw data-based models in predicting different porosity types and examine the importance of input data in porosity prediction. We show that models trained on SWIR thermogram data can identify systematic trends in local flaw formation. This is demonstrated for forced flaw formation using process parameter shifts and, moreover, for randomly formed flaws in the specimen bulk. Furthermore, we identify features of high importance for the prediction of lack-of-fusion and keyhole porosity from SWIR monitoring data.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"95 ","pages":"Article 104502"},"PeriodicalIF":10.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using virtual reality to orient parts for additive manufacturing and its effects on manufacturability and experiential outcomes 使用虚拟现实技术为增材制造部件定向及其对可制造性和体验成果的影响
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-08-25 DOI: 10.1016/j.addma.2024.104421
Jayant Mathur , Scarlett R. Miller , Timothy W. Simpson , Nicholas A. Meisel
{"title":"Using virtual reality to orient parts for additive manufacturing and its effects on manufacturability and experiential outcomes","authors":"Jayant Mathur ,&nbsp;Scarlett R. Miller ,&nbsp;Timothy W. Simpson ,&nbsp;Nicholas A. Meisel","doi":"10.1016/j.addma.2024.104421","DOIUrl":"10.1016/j.addma.2024.104421","url":null,"abstract":"<div><div>Additive manufacturing (AM) enables the fabrication of geometrically complex designs through layer-by-layer joining of material along single or multiple directions. To determine favorable design and manufacturing solutions, designers must navigate this 3D spatial complexity while ensuring the functionality and manufacturability of their designs. Evaluating the manufacturability of their solutions necessitates modalities that help naturally visualize AM processes and the designs enabled by them. Digitally non-immersive visualization can reduce this expense, but digital immersion has the potential to further improve the experience before building. This research investigates how differences in immersion between computer-aided (CAx) and virtual reality (VR) environments affect a designer’s approach to solving a build-with-AM (BAM) problem and its outcomes. First, it studies how immersion affects determining favorable build orientations when considering the additive manufacturability outcomes of designs of varying complexity. Second, it studies how immersion affects the participants’ experiential outcomes, including evaluation time, attempts made, and cognitive load when solving the BAM problem. Analysis reveals that as design complexity increases, visualizing and manufacturing designs in VR improves additive manufacturability outcomes by reducing build time and support material usage compared to CAx, reducing manufacturing costs by up to 4.61 % ($32) per part. Using immersive VR also helps designers determine favorable build orientations faster with fewer attempts and without increasing the cognitive load experienced. These findings present important implications for the role of immersive experiences in preparing designers to quickly produce lower-cost and sustainable manufacturing solutions with AM.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"94 ","pages":"Article 104421"},"PeriodicalIF":10.3,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation 通过数字图像相关性测量大幅面印刷聚合物复合结构的热机械响应
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-08-25 DOI: 10.1016/j.addma.2024.104479
Tyler M. Corum , Johnna C. O’Connell , James C. Brackett , Ahmed Arabi Hassen , Chad E. Duty
{"title":"Measuring thermomechanical response of large-format printed polymer composite structures via digital image correlation","authors":"Tyler M. Corum ,&nbsp;Johnna C. O’Connell ,&nbsp;James C. Brackett ,&nbsp;Ahmed Arabi Hassen ,&nbsp;Chad E. Duty","doi":"10.1016/j.addma.2024.104479","DOIUrl":"10.1016/j.addma.2024.104479","url":null,"abstract":"<div><div>Large-format additive manufacturing (LFAM) is a branch of additive manufacturing (AM) research with the ability to create large structures typically measuring several meters in scale. LFAM is advantageous for tooling applications, not only because it offers the ability to create complex geometries not easily made using subtractive manufacturing processes, but the cost savings of pelletized feedstock used by these systems result in larger parts printed at faster speeds than traditional AM systems. Fiber reinforced polymer (FRP) is a commonly used feedstock material in LFAM structures because it reduces the distortion experienced during printing. However, FRP introduces highly anisotropic thermomechanical properties and contributes to a nonhomogeneous microstructure that can result in critical distortion of dimensions during tooling. Measuring the global thermomechanical response of LFAM structures requires a more representative method that accounts for not only anisotropic properties but also the nonhomogeneous nature of the final part. This is where traditional techniques to measure thermomechanical response, such as thermomechanical analysis (TMA), fall short as they assume homogeneity. This study evaluated the coefficient of thermal expansion (CTE) of LFAM structures as measured by TMA as compared to a novel digital image correlation oven (DIC Oven) system. The LFAM structures were made from 20 % by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS). TMA measurements showed significant variations in CTE across a single LFAM bead, confirming the need for a global technique that captures overall thermomechanical response. The CTE values measured using the DIC Oven compared well to average TMA values obtained from localized measurements across the sample. The DIC Oven was also used to quantify the effects of different layer orientations on thermomechanical properties, which cannot be easily captured using TMA. A predictive model was also developed by using localized TMA values across an LFAM bead to predict the overall thermomechanical response of an LFAM structure.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"94 ","pages":"Article 104479"},"PeriodicalIF":10.3,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
4D Printed shape memory polymers in focused ultrasound fields 聚焦超声场中的 4D 印刷形状记忆聚合物
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-08-25 DOI: 10.1016/j.addma.2024.104465
Hrishikesh Kulkarni , Jiaxin Xi , Ahmed Sallam , Phoenix Lee , David Safranski , Reza Mirzaeifar , Shima Shahab
{"title":"4D Printed shape memory polymers in focused ultrasound fields","authors":"Hrishikesh Kulkarni ,&nbsp;Jiaxin Xi ,&nbsp;Ahmed Sallam ,&nbsp;Phoenix Lee ,&nbsp;David Safranski ,&nbsp;Reza Mirzaeifar ,&nbsp;Shima Shahab","doi":"10.1016/j.addma.2024.104465","DOIUrl":"10.1016/j.addma.2024.104465","url":null,"abstract":"<div><div>4D Printing is a new area of additive manufacturing that extends the possibilities of 3D printing by including the dimension of time. This cutting-edge technique entails creating elaborate structures out of intelligent materials, specifically shape memory polymers (SMPs), which may dynamically change shape or functionality in response to external inputs. The purpose of this study is to conduct a rigorous spatiotemporal characterization into the potential of focused ultrasound (FUS) in actuating 4D-printed SMPs as well as to evaluate the impacts of different printing parameters on shape recovery. Experiments demonstrate that FUS is a unique and non-invasive method that can cause localized heating, activate several intermediate shapes, and accomplish full shape recovery in SMPs. Moreover, by optimizing sample size, ultrasound frequency, exposure time, intensity, and the location of ultrasound focusing, FUS possesses an enhanced capacity for temporal and spatial control of shape recovery. We determine the effects of various 3D printing parameters, including printing temperature, printing speed, infill density, and infill structures, on the thermo-mechanical shape recovery properties of a thermoplastic polyurethane. Shape recovery ratios ranged from 50% to 80% across different printing parameters. The study demonstrated that increasing acoustic field intensity can maximize shape recovery to over 95%, although this may cause to material degradation depending on sample thickness. The findings also revealed that these printing parameters significantly influence storage modulus, loss modulus, and glass transition temperature, highlighting their impact on thermo-mechanical properties. Furthermore, this study uses acoustical principles and thermo-mechanical experimental data to show a systematic relationship between additive manufacturing settings and SMP viscoelastic deformation properties. Lastly, a dynamic transition of a 4D-printed functional gripper-like structure, exhibiting both opening and closing motions upon exposure to FUS irradiation, was demonstrated using the optimized parameters. This research paves the way for FUS to accurately spatiotemporal and localized actuation of SMPs, particularly in medical applications.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"94 ","pages":"Article 104465"},"PeriodicalIF":10.3,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A heterogeneous pore design algorithm for material extrusion additive manufacturing 用于材料挤压增材制造的异质孔隙设计算法
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-08-25 DOI: 10.1016/j.addma.2024.104449
Huawei Qu , Kaizheng Liu , Juan Liu , Chongjian Gao , Changshun Ruan
{"title":"A heterogeneous pore design algorithm for material extrusion additive manufacturing","authors":"Huawei Qu ,&nbsp;Kaizheng Liu ,&nbsp;Juan Liu ,&nbsp;Chongjian Gao ,&nbsp;Changshun Ruan","doi":"10.1016/j.addma.2024.104449","DOIUrl":"10.1016/j.addma.2024.104449","url":null,"abstract":"<div><div>Material extrusion additive manufacturing offers great potential for customizing matters with complex external contours, and filament diameter-adjustable 3D (FDA-3D) printing strategy provides fresh impetus to create heterogeneous porous structures inside these complex matters. However, the absence of supporting algorithms to implement FDA-3D printing severely hinders its widespread use. In this paper, we develop a heterogeneous pore design (HPD) algorithm aimed at advancing the development of FDA-3D printing for producing heterogeneous porous matters. The HPD algorithm consists of three sub-algorithms: model design, collapse compensation, and fabrication file (G-codes) generation. As proofs of concept, we utilize this algorithm to 3D print radial gradient and letter-embedded gradient materials following specific steps: (1) designing the heterogeneous porous models with collapse compensation in Grasshopper® and displaying them in Rhinocores®; (2) customizing and writing the corresponding G-codes files by following the material extrusion 3D printer's control rules; (3) upgrading a commercial extrusion printer to FDA-3D print the design models via the customized G-codes. Micro-computed tomography-based 3D reconstruction and quantified pore size maps for the fabricated objects demonstrate the high capability of this HPD algorithm. Overall, the HPD algorithm holds the potential to revolutionize material extrusion 3D printers cost-effectively, creating new possibilities for material extrusion of heterogeneous materials.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"94 ","pages":"Article 104449"},"PeriodicalIF":10.3,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-fidelity surrogate with heterogeneous input spaces for modeling melt pools in laser-directed energy deposition 采用异质输入空间的多保真度替代物,为激光引导能量沉积过程中的熔池建模
IF 10.3 1区 工程技术
Additive manufacturing Pub Date : 2024-08-25 DOI: 10.1016/j.addma.2024.104440
Nandana Menon, Amrita Basak
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