Featured Technologies - Engineering/Physical Sciences


Below are some recent technologies developed in Physical Sciences and Engineering. 

Professor Qibing Pei demonstrates his innovation: A Reversible Bioadhesive (UCLA Case No. 2021-139)

Professor Qibing Pei demonstrates his innovation: A Reversible Bioadhesive (UCLA Case No. 2021-139)

UCLA researchers in the Department of Materials Science and Engineering have developed a reusable bioadhesive that can provide strong adhesion to skin and living tissue when heated to body temperature and easily detached without damage at room temperature. For more information please visit: https://ucla.technologypublisher.com/technology/43869

Pipeline System Integrity Management - Professor Mosleh; UCLA Case No. 2022-279

UCLA Researchers led by Professor Mosleh have developed an advanced and user-friendly software to address the safety challenges presenting in the pipeline industries. It is a comprehensive assessing tool with a system-level prognosis and health monitoring (PHM) capabilities for PSIM, and it serves as a “one-stop-shop” for the pipeline operators to inspect and analyze the health state of the pipelines and have optimized mitigation suggestions accordingly. Compared to the traditional pipeline integrity management solution, this innovation considers dynamic and time-dependent mitigation actions to the pipeline operators. The information of optimized sensor placement and updated inspection/maintenance schedule is passed back to the predicting model as the field data to constantly optimize the mitigation plans to avoid or reduce the likelihood of pipeline failure at a lower cost. Due to its ease of integration with different types of pipeline systems and versatility of proposed data analytics techniques, this PSIM solution as a whole can be easily adapted with other types of pipeline systems that are used for large-scale infrastructure. Additional information can be found here: http://ucla.technologypublisher.com/technology/48512.  

Deep Learning Super-Resolution Magnetic Resonance Imaging via Slice-Profile-Transformation Based Downsampling

Dr. Kyung Sung and his team have developed a novel slice-profile transformation super-resolution (SPTSR) framework with deep generative learning for through-plane super-resolution (SR) of multi-slice 2D MRI imaging. After training their framework with 3,453 clinical subjects, they validated the framework in 392 patients and had two genitourinary radiologists qualitatively evaluate images taken with the framework in 50 patients. They found that this approach overcomes some of the current limitations of conventional approaches and reduces the need for acquiring additional orthogonal imaging planes. This method helps address the physical discrepancies between slice-encoding and frequency/phase-encoding in 2D MRI. Their novel approach is applicable across various disease contexts and results in higher accuracy imaging and reduced MRI acquisition time, making it a valuable tool in clinical settings to increase patient care and reduce the time burden on clinicians. Additional information can be found here: http://ucla.technologypublisher.com/technology/48773

Professor Aydogan discusses Mobile Diagnostic Innovations

Professor Aydogan Discusses Pictor Labs

2022-250: DeepAdjoint: Photonic Structure Design Tool

DeepAdjoint Photonic Structures

Professor Raman and his research team have invented an interactive materials design tool called DeepAdjoint that helps non-experts expedite the design of photonic structures, or electromagnetic components in general. This platform optimizes across materials and geometries simultaneously and supports various classes of NNs such as generative adversarial networks (GANs), variational autoencoders (VAEs), and multilayer perceptrons (MLPs). It seamlessly streamlines advanced ML techniques with improved optimization methods to realize an automated electromagnetic metamaterials design process. An engineer with limited domain knowledge or experience can specify an arbitrary optical design target, and then achieve a photonic structure with the desired optical properties all within a single user-friendly application interface. Additionally, this design tool is generalizable and paves the way towards the systematic unification of ML and optimization algorithms for materials inverse design.


ForceSight: Non-Contact Force Sensing

ForceSight is a non-contact force sensing approach using laser speckle imaging.

2021-359 Seeing Through Random Diffusers Without a Computer

2021-359 Seeing Through Random Diffusers Without a Computer

UCLA researchers led by Professor Aydogan Ozcan have developed an all optics-based system that can perform image reconstruction at the speed of light for images distorted by light scattering and diffusion. By working purely with optics this approach works at the speed of light and does not require digital communication or power. This all-optical approach is an improvement which is orders of magnitude faster than digital approaches and adaptive optics. For additional information about this technology, please visit: http://ucla.technologypublisher.com/technology/47434

Personalized Control of Hemodynamics

Personalized Control of Hemodynamics in High-Risk Surgery Patients by Jinyoung Brian Jeong BS, Michael Zargari BS, Daniel Garcia MD PhD, Chih Ming Ho PhD, Jure Marijic MD, Jaques Neelankavil MD, Maxime Cannesson MD PhD, Soban Umar MD PhD Department of Mechanical & Aerospace Engineering Department of Anesthesiology and Perioperational Medicine UCLA

Fully Integrated Stretchable Sensor Array for Wearable Sign Language Translation to Voice by Jun Chen, Assistant Professor of Bioengineering, UCLA

Lamprey Lock: Secure High Flow Catheter Connector 

A secure high-flow catheter connector Lucas R. Cusumano, MD MPH: Resident Physician, Interventional Radiology Justin P. McWilliams, MD FSIR: Associate Professor, Inteventional Radiology UCLA

Multi-Rotors Copter 

Modular Platforms with Multi-Rotor Copters Mounted on Hinges of Gimbals for Form Mechanically Constrained Flight Formations Tsu-Chin Tsao, Professor of Mechanical & Aerospace Engineering. UCLA

UV Reflective Paints For Cooling

UCLA researchers in the Department of Materials Science & Engineering have developed coatings with exceptional solar-ultraviolet (UV) reflectance for efficient passive daytime radiative cooling of buildings. The coating can be applied by a painting, dip-coating or other simple techniques. Upon drying, the coating, in sufficient thicknesses, can achieve solar reflectance from 0.94-0.98