GE Aerospace, Evendale, OH, announced a $225 million investment to modernize the GE Aerospace Research Center in Niskayuna, NY, advancing the site’s legacy as the innovation engine behind breakthroughs in aviation advancements.
Continue readingHow twisting two-dimensional materials led to a new field of research
Researchers from Rutgers University, MIT, and UT Austin, supported by the U.S. Department of Energy, have been awarded the Kavli Prize in Nanoscience for pioneering ‘twistronics’, discovering that twisting two-dimensional materials like graphene unlocks novel quantum behaviors like superconductivity.
Continue readingAI helps microscopes find the most informative nanoscale features
Researchers at the Department of Energy’s Oak Ridge National Laboratory have developed SimuScan, an artificial intelligence framework that uses realistic synthetic data to train AI to identify nanoscale features and autonomously target the most informative regions of a sample.
Continue readingMIT researchers use AI to uncover atomic defects in materials
Researchers at the Massachusetts Institute of Technology built an AI model trained on 2,000 different semiconductor materials using data from a noninvasive neutron-scattering technique that can detect and classify up to six kinds of point defects in a material simultaneously, something that would be impossible using conventional techniques alone.
Continue readingKeysight addresses cross-domain physics issues that leave electronic designs vulnerable to late-stage failure
Keysight Technologies, Santa Rosa, Calif., announced Keysight Multiphysics, a design and verification solution that addresses the physics interactions driving failure in modern electronic designs, featuring a structural analysis application covering drop, shock, and vibration that enables engineering teams to identify and fix problems earlier, before a prototype is built.
Continue readingMegalibraries could reshape AI-driven materials discovery faster than self-driving labs
Researchers at Northwestern University, Evanston, Illinois, have developed a megalibrary platform that enables the rapid, intentional engineering of new materials with specific properties, such as piezoelectricity, by using high-throughput screening and AI-ready datasets to accelerate discovery from years to hours.
Continue readingMicrostructure on demand for additive manufacturing
Fraunhofer ICON Project “UltraGRAIN” demonstrates local microstructure control in metallic components during laser-based directed energy deposition, using pulsed-laser-induced melt pool excitation with potential for tailored products.
Continue readingSynopsys and AMD honored by World Economic Forum for generative and agentic AI vision, leadership, and impact
Synopsys, in collaboration with AMD, has been selected for the World Economic Forum’s MINDS (Meaningful, Intelligent, Novel, Deployable Solutions) AI program for their joint work in transforming chip design through AI-powered workflows.
Continue readingCornell researchers reveal how small optical computers could get
By studying the theoretical limits of how light can be used to perform computation, Cornell researchers have uncovered new insights and strategies for designing energy-efficient optical computing systems.
Continue readingMachine learning automates material analysis and design using X-ray spectroscopy data
A research team from Tokyo University of Science, Japan, has developed an automated artificial intelligence-based approach for analyzing X-ray absorption spectroscopy data to establish a clear and objective link between a material’s spectral data and its underlying material properties.
Continue readingNew computational model by Northeastern scientists revolutionizing alloy design
Scientists at Northeastern University, Boston, Mass., introduce a new cost- and energy-efficient computational model for designing alloys that factors in material defects.
Continue readingHarnessing ancient materials and AI for sustainable architecture
In the adrenaline-fueled rush of a set-up for their studio review, a team of students pursuing a Master of Science in Design with a concentration in Robotics and Autonomous Systems (MSD-RAS) assemble layer upon layer of ceramic bricks, securing them in place with a satisfying “clink.” And as the model got taller, the stakes got higher. The breakability of ceramic was not far from anybody’s mind.
Clay is one of the world’s oldest building materials: From adobe bricks to terracotta tiles, clay has been used to construct buildings for millennia. Now, advances in computational design and robotic technology have revolutionized the way these bricks are made, and what forms they can take. Made by extruding layers of clay in carefully defined toolpaths, the students 3D printed their designs using six-axis industrial robots, more easily found in a car manufacturing plant than a design school.
These fully-integrated and automated robots are housed just a floor below the Plaza Gallery in Meyerson Hall, in the Stuart Weitzman School of Design’s Robotics Lab, which opened in 2019 as part of the Department of Architecture’s Advanced Research and Innovation Lab. They position the School at the forefront of architectural design research that leverages and develops approaches to robotic fabrication. The two-semester MSD-RAS program combines an education in robotics with the tools of artificial intelligence and automated systems, which hold the promise of thoroughly adaptive, sustainable, and intelligent approaches to manufacturing and design.
Robert Stuart-Smith, the program’s director and an assistant professor of architecture, sees the MSD-RAS program in relation to the Fourth Industrial Revolution, a historic shift in manufacturing that began in the last decade or so with the development of technology like artificial intelligence. One simple example of a semi-autonomous robot application, is a sanding robot, which adjusts its position in response to sensor-feedback to maintain a constant amount of pressure that it applies to the part it is finishing.
“Most architecture is still built by Second Industrial Revolution technologies of mass production,” says Stuart-Smith, “where things are only economical if we make them all the same, and produce these same parts at high volumes of production. But with the Fourth Industrial Revolution, we have the capabilities of bespoke production at a scale or volume similar to mass production.” The goal, he says, is to put artisanship back into manufacturing, in a way that’s less expensive and more accessible than ever before, and less wasteful.
For more information: University of Pennslyvania
Image: Offering a robust suite of milling, additive manufacturing, sheet-metal bending, and hot-wire cutting tools, the Robotics Lab in Meyerson Hall brings together faculty and students across the Department of Architecture for studio-based work and funded research.
Predicting grain growth for better materials
New research is helping scientists better understand how microstructures change, or undergo grain growth, at high temperatures, thus determining properties such as hardness. A team of materials scientists and applied mathematicians developed a mathematical model that more accurately describes such microstructures by integrating data that can be identified from highly magnified images taken during experiments.
Continue readingScientists use computational modeling to design “ultrastable” materials
These highly stable metal-organic frameworks could be useful for applications such as capturing greenhouse gases.
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