npj Advanced Manufacturing最新文献

Laser sintering of electrohydrodynamic inkjet-printed silver in microgravity for in-space manufacturing of electronic devices. 微重力下激光烧结电流体喷墨印刷银在空间电子器件制造中的应用。

npj Advanced Manufacturing Pub Date : 2025-01-01 Epub Date: 2025-10-01 DOI: 10.1038/s44334-025-00054-9

Ellie Schlake, Sagar Kumar Verma, Liangkui Jiang, Pengyu Zhang, Hantang Qin, Nirmala Kandadai

{"title":"Laser sintering of electrohydrodynamic inkjet-printed silver in microgravity for in-space manufacturing of electronic devices.","authors":"Ellie Schlake, Sagar Kumar Verma, Liangkui Jiang, Pengyu Zhang, Hantang Qin, Nirmala Kandadai","doi":"10.1038/s44334-025-00054-9","DOIUrl":"10.1038/s44334-025-00054-9","url":null,"abstract":"The National Aeronautics and Space Administration (NASA) plans to deploy a fully functional 3D printer in low Earth orbit for in-space manufacturing (ISM) of semiconductor electronics. Earlier, our group demonstrated the successful application of high-resolution printing for semiconductor manufacturing using electrohydrodynamic printing. However, sintering of printed films is a significant challenge due to payload constraints. In this paper, we demonstrate laser sintering as a viable technology for ISM. The first experiments of successful demonstration of laser sintering of EHD printed silver on silicon in micro and lunar gravity are presented. The microstructures and conductivity of the samples are compared to those of the ground samples, and we observe that samples under microgravity exhibit increased heat transport compared to those under gravity. We hypothesize that the samples under microgravity experience lower convective heat transport, resulting in increased surface melting. A COMSOL heat transport model supports the laser sintering studies and hypotheses.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":"2 1","pages":"42"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12488487/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145234868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning image-based analysis for bead geometry prediction in fused granulate fabrication for large format additive manufacturing. 基于机器学习图像的大幅面增材制造熔融颗粒加工中磁珠几何形状预测分析。

npj Advanced Manufacturing Pub Date : 2025-01-01 Epub Date: 2025-03-18 DOI: 10.1038/s44334-025-00018-z

Daniele Vanerio, Mario Guagliano, Sara Bagherifard

{"title":"Machine learning image-based analysis for bead geometry prediction in fused granulate fabrication for large format additive manufacturing.","authors":"Daniele Vanerio, Mario Guagliano, Sara Bagherifard","doi":"10.1038/s44334-025-00018-z","DOIUrl":"10.1038/s44334-025-00018-z","url":null,"abstract":"This study investigates an artificial neural network (ANN) for predicting cross-sectional geometry in fused granulate fabrication (FGF), a key polymer-based technology in large-format additive manufacturing (LFAM). Critical process parameters-layer height, transverse speed, and screw speed-were systematically varied to study their effects on bead morphology. A full factorial design generated a robust training dataset, and cross-sectional images were processed for model training. The ANN architecture, featuring two hidden layers, was paired with image processing techniques to manage computational demands. Results showed strong agreement between predicted and experimental cross-sections, with a mean absolute error of 8.88%, highlighting the ANN's capability in capturing geometry. This approach advances prior LFAM studies by predicting full cross-sectional images rather than contour points, improving complex shape prediction. The findings demonstrate the ANN's effectiveness for FGF profiles and its potential to enhance geometric precision and generate complex shapes across LFAM technologies.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":"2 1","pages":"8"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the role of interface strategy in multi-scale hybrid additive manufacturing. 界面策略在多尺度混合增材制造中的作用研究。

npj Advanced Manufacturing Pub Date : 2025-01-01 Epub Date: 2025-08-29 DOI: 10.1038/s44334-025-00034-z

Alan Burl, Zaky Hussein, Venkata Surya Karthik Adapa, Melissa Foley, Nicole Van Handel, Matthew McCoy, Thomas Kurfess, Christopher Saldaña, Kyle Saleeby

{"title":"On the role of interface strategy in multi-scale hybrid additive manufacturing.","authors":"Alan Burl, Zaky Hussein, Venkata Surya Karthik Adapa, Melissa Foley, Nicole Van Handel, Matthew McCoy, Thomas Kurfess, Christopher Saldaña, Kyle Saleeby","doi":"10.1038/s44334-025-00034-z","DOIUrl":"10.1038/s44334-025-00034-z","url":null,"abstract":"As multiple macro scale directed energy deposition (DED) processes begin to be industrially adopted for large scale component manufacture, it is imperative that interface strategies between the processes are fully understood. The present work investigates the asynchronous deposition of a wire component (DED-arc), followed by a powder-based deposition (DED-LP) with varying surface treatments which were evaluated for flatness, porosity, hardness, and Charpy impact energy. The self-regulation effect of DED-LP was fully realized with up to 55% reduction in surface variation relative to the DED-arc surface. Contrarily, as surface contaminants were not removed between each process, the resultant DED-LP porosity was significantly reduced from 99.5% to 92.4%. Albeit the reduction in density did not negatively impact the impact toughness as evidenced by a low correlation coefficient of -0.46. As such, the overall manufacturing costs and application space must be considered for selection of the different interface strategies presented in the current work.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":"2 1","pages":"38"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396965/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144985199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transfer learning assessment of small datasets relating manufacturing parameters with electrochemical energy cell component properties. 与电化学能量电池组件特性相关的制造参数小数据集的迁移学习评估。

npj Advanced Manufacturing Pub Date : 2025-01-01 Epub Date: 2025-04-18 DOI: 10.1038/s44334-025-00024-1

Francisco Fernandez, Soorya Saravanan, Rashen Lou Omongos, Javier F Troncoso, Diego E Galvez-Aranda, Alejandro A Franco

{"title":"Transfer learning assessment of small datasets relating manufacturing parameters with electrochemical energy cell component properties.","authors":"Francisco Fernandez, Soorya Saravanan, Rashen Lou Omongos, Javier F Troncoso, Diego E Galvez-Aranda, Alejandro A Franco","doi":"10.1038/s44334-025-00024-1","DOIUrl":"https://doi.org/10.1038/s44334-025-00024-1","url":null,"abstract":"The performance of electrochemical cells for energy storage and conversion can be improved by optimizing their manufacturing processes. This can be time-consuming and costly with the traditional trial-and-error approaches. Machine Learning (ML) models can help to overcome these obstacles. In academic research laboratories, manufacturing dataset sizes can be small, while ML models typically require large amounts of data. In this work, we propose a simple but still novel application of a Transfer Learning (TL) approach to address these manufacturing problems with a small amount of data. We have tested this approach with pre-existing experimental and stochastically generated datasets. These datasets consisted of component properties (e.g., electrode density) related to different manufacturing parameters (e.g., solid content, comma gap, coating speed). We have demonstrated the robustness of our TL approach for manufacturing problems by achieving excellent prediction performance for electrodes in lithium-ion batteries and gas diffusion layers in fuel cells.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":"2 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12008025/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144001658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating residual stress in additively manufactured nitinol shape memory alloy. 增材制造镍钛诺形状记忆合金的残余应力评价。

npj Advanced Manufacturing Pub Date : 2025-01-01 Epub Date: 2025-04-30 DOI: 10.1038/s44334-025-00027-y

Sampreet Rangaswamy, Josiah Cherian Chekotu, Thomas Gillick, Cian Hughes, Jayne Nicholl, David Easton, Caner Şimşir, Dermot Brabazon

{"title":"Evaluating residual stress in additively manufactured nitinol shape memory alloy.","authors":"Sampreet Rangaswamy, Josiah Cherian Chekotu, Thomas Gillick, Cian Hughes, Jayne Nicholl, David Easton, Caner Şimşir, Dermot Brabazon","doi":"10.1038/s44334-025-00027-y","DOIUrl":"https://doi.org/10.1038/s44334-025-00027-y","url":null,"abstract":"This study provides a comprehensive analysis of residual stress characteristics in nitinol parts fabricated via laser powder bed fusion (PBF-LB). Unlike previous works that primarily focus on qualitative assessments or single-measurement techniques, this research employs a multi-modal experimental approach, Electronic Speckle Pattern Interferometry-Hole Drilling (ESPI-HD) and X-ray Diffraction (XRD), to achieve a more precise and spatially resolved evaluation of residual stress distribution. Furthermore, the study establishes a direct correlation between residual stress evolution and in situ pyrometric melt pool temperature data, an aspect that has not been extensively explored in prior investigations. A key novel finding is the non-monotonic relationship between volumetric energy density (VED) and residual stress. In this work, laser power was kept constant, and VED was varied by adjusting scanning speed and hatch spacing. The results show that the average residual stress initially increases with decreasing scan speed and hatch spacing, plateaus at a critical threshold, and subsequently decreases. However, residual stress was also found to vary in the build direction, indicating the complex stress distributions and accommodation mechanisms within the material. Additionally, an inverse relationship was recorded between the thermal gradient and VED which challenges conventional assumptions about their relationship. These insights offer a new perspective on optimizing PBF-LB process parameters for enhanced structural performance and long-term reliability of additively manufactured nitinol.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":"2 1","pages":"16"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12043501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144049475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian stability and force modeling for uncertain machining processes 不确定加工过程的贝叶斯稳定性和力建模

npj Advanced Manufacturing Pub Date : 2024-12-18 DOI: 10.1038/s44334-024-00011-y

Aaron Cornelius, Jaydeep Karandikar, Tony Schmitz

引用次数: 0

Energy-efficient and quality-focused control of conveyor belt dryers in petrochemical production 石化生产中传送带干燥机的节能与质量控制

npj Advanced Manufacturing Pub Date : 2024-12-04 DOI: 10.1038/s44334-024-00010-z

Muhammad Waseem, Kshitij Bhatta, Chen Li, Nabeel Haider, Qing Chang

{"title":"Energy-efficient and quality-focused control of conveyor belt dryers in petrochemical production","authors":"Muhammad Waseem, Kshitij Bhatta, Chen Li, Nabeel Haider, Qing Chang","doi":"10.1038/s44334-024-00010-z","DOIUrl":"10.1038/s44334-024-00010-z","url":null,"abstract":"The petrochemical industry’s dryers, which operate at high temperatures, consume substantial energy and require precise temperature control to maintain product quality. To address these challenges, conveyor belt dryers are used for continuous drying, but optimizing their operation is complex. Traditional control methods often rely on operator experience or fixed settings, which may not be optimal. This paper introduces a novel approach using a Graph Neural Network and Multiagent Deep Deterministic Policy Gradient algorithm. This method models dryers’ components—chambers, fans, and belts—as cooperating agents, optimizing temperature, fan speed, and belt speed based on quality predictions. The algorithm, trained with industrial data, improves decision-making by integrating quality predictions into its reward function. Extensive experiments show a 5% improvement in product quality and a 3% reduction in energy consumption per time step, translating to significant energy savings. This approach enhances both efficiency and product quality control in conveyor belt dryers.","PeriodicalId":501702,"journal":{"name":"npj Advanced Manufacturing","volume":" ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44334-024-00010-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards next-gen smart manufacturing systems: the explainability revolution 迈向下一代智能制造系统：可解释性革命

npj Advanced Manufacturing Pub Date : 2024-11-06 DOI: 10.1038/s44334-024-00006-9

Puthanveettil Madathil Abhilash, Xichun Luo, Qi Liu, Rajeshkumar Madarkar, Charles Walker

引用次数: 0

Multi-material vat photopolymerization 3D printing: a review of mechanisms and applications 多材料大桶光聚合三维打印：机制与应用综述

npj Advanced Manufacturing Pub Date : 2024-11-06 DOI: 10.1038/s44334-024-00005-w

Saroj Subedi, Siying Liu, Wenbo Wang, S. M. Abu Naser Shovon, Xiangfan Chen, Henry Oliver T. Ware

引用次数: 0

Polybutadiene structural effects on dynamic wetting 聚丁二烯结构对动态润湿的影响

npj Advanced Manufacturing Pub Date : 2024-10-11 DOI: 10.1038/s44334-024-00007-8

Sahson D. Raissi, Marc A. Magaña, Alexander Contreras, Shiqi Wei, Blair Brettmann, Joseph Kalman

引用次数: 0