3D printing crystallographic data for post-printing construction
نویسندگان
چکیده
منابع مشابه
Autocomplete Textures for 3D Printing
Texture is an essential property of physical objects that affects aesthetics, usability, and functionality. However, designing and applying textures to 3D objects with existing tools remains difficult and time-consuming; it requires proficient 3D modeling skills. To address this, we investigated an auto-completion approach for efficient texture creation that automates the tedious, repetitive pr...
متن کامل3D-Printing for Analytical Ultracentrifugation
Analytical ultracentrifugation (AUC) is a classical technique of physical biochemistry providing information on size, shape, and interactions of macromolecules from the analysis of their migration in centrifugal fields while free in solution. A key mechanical element in AUC is the centerpiece, a component of the sample cell assembly that is mounted between the optical windows to allow imaging a...
متن کاملi3DP, a robust 3D printing approach enabling genetic post-printing surface modification.
Initiator integrated 3D printing, namely i3DP, was developed by incorporating a vinyl-terminated initiator into UV curable resin to make functional structural materials that enable genetic post-printing surface-initiated modification. Taking advantage of 3D printing and surface-initiated ATRP, the feasible i3DP makes 3D printed complex architectures possible for nearly any desired surface modif...
متن کاملPath optimizing for 3D printing
In the 3D printing process, the 3D CAD model is built in CAD system and sliced into a series of 2D slices. The 2D cross section data contains a lot of unnecessary idle running. If transform the original data into processing path code directly, the processing efficiency will be significantly reduced. A path optimization algorithm is developed in this paper. The minimum spanning tree strategy is ...
متن کاملTion in 3d Printing
The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits. In order to enhance the security level of the 3D printing process, the present research aims to detect and recognize illegal components using deep learning. In this work, we collected a dataset of 61,340 2D images (28×28 for each ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Crystallographica Section A Foundations and Advances
سال: 2019
ISSN: 2053-2733
DOI: 10.1107/s0108767319099768