A5066557377- Additive Manufacturing and 3D Printing Technologies
- Electrophoretic Deposition in Materials Science
- Additive Manufacturing Materials and Processes
- Industrial Vision Systems and Defect Detection
- Electrostatics and Colloid Interactions
- Quantum Dots Synthesis And Properties
- Iron oxide chemistry and applications
- Microfluidic and Bio-sensing Technologies
- Welding Techniques and Residual Stresses
- Microfluidic and Capillary Electrophoresis Applications
- Acoustic Wave Phenomena Research
- Electrowetting and Microfluidic Technologies
- TiO2 Photocatalysis and Solar Cells
- Manufacturing Process and Optimization
- Advanced Memory and Neural Computing
- Industrial Engineering and Technologies
- Electrochemical Analysis and Applications
- Image Processing and 3D Reconstruction
- Electrohydrodynamics and Fluid Dynamics
- Image Processing Techniques and Applications
- Advanced X-ray and CT Imaging
- Spectroscopy and Quantum Chemical Studies
- Research Data Management Practices
- Modular Robots and Swarm Intelligence
- Innovative Microfluidic and Catalytic Techniques Innovation
Lawrence Livermore National Laboratory
2015-2025
Berkeley College
2019
University of California, Berkeley
2019
Lawrence Livermore National Security
2019
University of California, Santa Barbara
2013-2015
Abstract A two‐step machine learning approach to monitoring laser powder bed fusion (LPBF) additive manufacturing is demonstrated that enables on‐the‐fly assessments of track welds. First, in situ video melt pool data acquired during LPBF labeled according the (1) average and (2) standard deviation individual width also (3) whether or not continuous, measured postbuild through an ex height map analysis algorithm. This procedure generates three ground truth datasets for supervised learning....
Laser Powder Bed Fusion (LPBF) is the predominant metal additive manufacturing technique that benefits from a significant body of academic study and industrial investment given its ability to create complex geometry parts. Despite LPBF's widespread use, there still exists need for process monitoring ensure reliable part production reduce post-build quality assessments. Towards this end, we develop evaluate machine learning-based predictive models using height map-derived metrics single...
Abstract Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice with tailored or optimal mechanical properties remains a significant challenge. With each added variable, the space quickly becomes intractable. To address this challenge, research efforts have sought combine computational approaches machine learning (ML)-based reduce cost process and accelerate design. While these made substantial progress, challenges in (1)...
We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations binary electrolytes comprised equisized ions in an implicit solvent. The Bikerman LDA, which considers to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on Carnahan–Starling (CS) hard-sphere equation state capture simulated values ideal and excess chemical potential profiles extremely well, as well relationship surface...
This paper describes the hardware and software ecosystem encompassing brain-inspired TrueNorth processor - a 70mW reconfigurable silicon chip with 1 million neurons, 256 synapses, 4096 parallel distributed neural cores. For systems, we present scale-out system loosely coupling 16 single-chip boards scale-up tightly integrating chips in 4 × configuration by exploiting TrueNorth's native tiling. software, an end-to-end consisting of simulator, programming language, integrated environment,...
Selective Laser Melting (SLM) is a metal additive manufacturing technique. The lack of SLM process repeatability barrier for industrial progression. product quality hard to control, even when using fixed system settings. Thus could benefit from monitoring that provides assessments in real-time. Since there no publicly available dataset, we ran experiments collect over one thousand videos, measured the physical output via height map images, and applied proposed image processing algorithm them...
We automated a traditionally labor-intensive, yet widely-used capsule production system.
The interaction between a Au particle and defective TiO 2 surface was simulated over 6000 unique conditions, the relative importance of parameters determined by logistic regression.
Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These in turn, determine functional quality of printed parts. Hence, to ensure repeatable reliable part it is necessary monitor control characteristics. Existing approaches for in-situ monitoring behavior DoD-LMJ rely on high-speed imaging sensors. The resulting high volume images acquired computationally...
Abstract Opportunities to improve thermal management in electronic devices are currently hindered by processing constraints that limit conductivity polymer‐matrix composites. Active patterning of filler particles is a promising route while retaining processability improving particle contact density and directing heat along optimized pathways. This study employs acoustic align compact into stripes during stereolithographic 3D printing. approach produces polymer‐based composite materials with...
Additive manufacturing (AM) techniques have been used to enhance the design and fabrication of complex components for various applications in medical, aerospace, energy, consumer products industries. A defining feature many AM parts is internal geometry enabled by printing process. However, inspecting these structures requires volumetric imaging, i.e., X-ray CT, leading well-known challenge visualizing 3D geometries using 2D desktop interfaces. Furthermore, existing tools are limited...
Abstract Ontologies have gained popularity in the scientific community as a way to standardize terminologies organizations’ data. Although certain cohorts created frameworks with rules and guidelines on creating ontologies, there exist significant variations how Materials Science ontologies are currently developed. We seek provide guidance form of unified automated framework for developing interoperable modular Data that simplifies ontology terms matching by establishing semantic bridge up...
We present and evaluate a semiempirical particle-based model of electrophoretic deposition using extensive mesoscale simulations. analyze particle configurations in order to observe how colloids accumulate at the electrode arrange into deposits. In agreement with existing continuum models, thickness deposit increases linearly time during deposition. Resulting colloidal deposits exhibit transition between highly ordered bulk disordered regions that can give rise an appreciable density...
Platinum electrodes are critical components in many biomedical devices, an important example being implantable neural stimulation or recording electrodes. However, upon implantation, scar tissue forms around the electrode surface, causing unwanted deterioration of electrical contact. We demonstrate that sub-monolayer coatings platinum nanoparticles (PtNPs) applied to 3D by electrophoretic deposition (EPD) can enhance electrode's active surface area and significantly lower its impedance. In...
Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous sets that are impractical manual assessment characterization. In this work, an automated pipeline is developed enables feature extraction from high-speed camera video multi-modal analysis. The framework removes the need through utilization of deep learning techniques training models in a weakly supervised...
We conduct numerical simulations of acoustic focusing in dense suspensions to map the design space acoustically patterned materials and understand relationships between input parameters, structural features, functional properties. develop closed-form expressions for forces on particles, enabling rapid simulation thousands find excellent agreement with experimentally focused patterns over a range conditions. geometrical microstructural features particle their dependence processing parameters....
We develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. parameterize the only measurable quantities from broad set colloidal suspensions with properties that span experimentally relevant regime. With sufficient sampling, simulated diffusivities electrophoretic velocities match predictions ubiquitous Stokes-Einstein Henry equations, respectively. This agreement holds for non-polar aqueous solvents or ionic liquid under wide range...
Electrophoretic deposition (EPD) of platinum nanoparticles (PtNPs) on platinum–iridium (Pt–Ir) neural electrode surfaces is a promising strategy to tune the impedance electrodes implanted for deep brain stimulation in various neurological disorders such as advanced Parkinson's disease and dystonia. However, previous results are contradicting reduction was observed flat samples while three-dimensional (3D) structures, an increase observed. Hence, defined correlations between coating...
We derive a self-similarity criterion that must hold if planar electric double layer (EDL) can be captured by local-density approximation (LDA), without specifying any specific LDA. Our procedure generates similarity coordinate from EDL profiles (measured or computed), and all LDA for given electrolyte collapse onto master curve when plotted against this coordinate. Noncollapsing imply the inability of theory to capture EDLs in electrolyte. demonstrate our approach with molecular...
Electrophoretic deposition is an industrially proven technique to create materials from colloidal suspensions using electric field, including functionally graded materials. While typically the composition of suspension held constant during deposition, leading deposits uniform or distinct layers, several researchers have reported forming via electrophoretic by changing deposition. This article explores in a flow cell that allows arbitrary gradients deposited material be formed actively mixing...
Structured light metrology provides a precise and efficient digital reconstruction of real-world objects through projected patterns camera system. However, conducting measurements these systems often requires time-intensive manual setting input measurement parameters that may not be generalizable across wide range objects. Automating the steps involved in optimizing can significantly improve quality measured data. This work presents twin to automate refine based on ray-tracing simulations...