Obvious Ventures’ Post

Professor John W. Cahn, initially drawn to #materials_science for its lack of mathematics, ultimately became a pioneer in mathematical modeling and #simulation. His groundbreaking contributions in computational materials science, particularly in phase field modeling, revolutionized the field. This underscores the importance of adaptability and leveraging emerging technologies. Particularly, in the rapidly evolving #battery industry, companies must similarly harness tools like digital twins, AI-driven simulations, and machine learning to stay ahead. Embracing these innovations enables firms to optimize thermal management, predict performance, and achieve sustainable, competitive solutions in this dynamic landscape. P.S. The image shows a temperature profile of a battery module, and credit belongs to Ansys #Battery_simulation #ECM #equivalent_circuit_model #Battery_thermal_management #lfp #solid_state_battery #battery_ai #battery_informatic

🔬 Moving Beyond Serendipity in Science with Simulations Can multiscale simulations and machine learning end trial and error, ushering in a data-driven science era? Serendipity, like Fleming's penicillin discovery, has long driven breakthroughs in science, such as X-rays, chemotherapy, and graphene. Traditionally, science relied on trial and error — constant, meticulous, repetitive experiments informing the next round of research. Technology like computational simulations and machine learning is revolutionizing research, making traditional methods obsolete. Read more in our blog: https://lnkd.in/geRHuhVj ▶️ If you want to know how Quantistry can help you upgrade your R&D get in touch: https://lnkd.in/gE8uy8rA #simulation #chemistry #research #machinelearning #materials #science

Thank you for sharing this excellent post on the transformative power of simulations in chemistry, Quantistry team! The strides being made in computational chemistry are indeed impressive and critical for advancing our field. Having been deeply involved in similar research, I can attest to the immense potential of these tools. During my projects at CMMR Lab at Michigan Technological University, I utilized reactive molecular simulations to simulate curing (crosslinking) reactions in high-performance polymers and predict thermo-mechanical properties as a function of processing parameters. This approach not only enhanced our understanding of the evolution of material properties with curing but also paved the way for multiscale process modeling using ICME (Integrated Computational Materials Engineering). One of the highlights of my recent work was winning the AIAA ICME prize 2022, where we leveraged advanced simulation techniques to optimize the design of composite Y-joint used in Aurora Flight Science's D8 aircraft. Seeing the capabilities of these simulations in action reaffirms my belief in their importance for future discoveries and innovations. It's inspiring to see the progress and dedication of the Quantistry team. #Simulation #Chemistry #Research #Innovation #ComputationalChemistry #MolecularSimulation #reactivity #polymers

New device precisely controls photon emission for more efficient portable screens

This week, the ATA Engineering team is attending the 2024 The Minerals, Metals & Materials Society (TMS) Specialty Congress in Cleveland. The TMS Specialty Congress will host three co-located events: the 2nd World Congress of Artificial Intelligence in Materials and Manufacturing, the Symposium on Digital and Robotic Forming 2024, and Accelerating Discovery for Mechanical Behavior of Materials 2024. Attending TMS and engaging with fellow industry experts in materials science are crucial as ATA continues to pursue research and innovation efforts in this field. To showcase a topic of ATA's Independent Research and Development (IRAD) work in materials science, ATA Engineer Liam Mackin will present the following paper tomorrow at TMS: ◼ Tuesday, June 18, at 11 a.m. local time “Thermodynamically Consistent Neural Networks for Modeling of Inelastic Material Responses” ATA Authors: Liam Mackin, David Najera, Rohan Patel, Bradley Davidson, and Paul Christodoulou If you are at TMS this week, be sure to attend this presentation and connect with our team! Participating in the TMS Specialty Congress 2024 is essential for accessing cutting-edge knowledge and networking opportunities in materials science, with focused sessions on artificial intelligence (AI), robotics, and machine learning, alongside multidisciplinary collaboration and comprehensive programming. Learn more at https://lnkd.in/gBKJNcvQ #MaterialsScience #ArtificialIntelligence #MachineLearning #AI

🚀 Just Released: Explore the Latest Findings from #CES! Section Category: Engineering Science 📄 Title: Insights into the Pore Structure Effect on the Mass Transfer of Fuel Cell Catalyst Layer via Combining Machine Learning and Multiphysics Simulation Authors: Laiming Luo, Xinrui Liu, Jujia Zhang, Jian Yao, Baohua Liu, Jin Zhang, Haining  Wang, Shanfu Lu, Yan Xiang 🔗 Read the full article now: https://lnkd.in/dbK8CpFk #HTPEMFC #Catalystlayerreconstruction #Structurepropertyrelationship #Threephasemasstransfer #Machinelearning #Multiphysicssimulation

On April 8, the third edition of our lecture series Materialize the future takes off 🚀 This year, we have again an incredible line-up of speakers (even more impressive than previous years), with online speakers from as far as Chicago (Prof. dr. Sara Kadkhodaei) giving us insights into the use of AI in materials design from the computational perspective. As robots and computers can not be kept out of the lab Prof. dr. Helge S. Stein will show us how High-Throughput automation and distributed research can help us efficiently design new materials. Further, we will learn how a gemstone like diamond can be at the heart of future quantum technologies (Prof. dr. Petr Siyuchev), how hydrogels can play a role in medicine (Prof. dr. Matthew Baker) and how plastic waste can be a useful source material (Prof. dr. Louis Pitet). Participation is free but registration is mandatory via https://lnkd.in/eeJUCxPD #materiomics #physics #chemistry #modeling #AI #ML #Robotics #uhasselt #futureproof imo-imomec UHasselt

The KIST(Korea Institute of Science and Technology) and Korea University have launched a groundbreaking Smart Lab platform powered by AI and robotics! Dr. Sang Soo Han and Dr. Donghun Kim from KIST’s Computational Science Research Center, along with Professor Kwan-Young Lee from the Department of Chemical Engineering and Biotechnology at Korea University, have pioneered the Smart Lab platform. Here are some of the key highlights ⬇️    📈 Boosts material development efficiency by 500 times.    🤖 Ensures consistent, high-quality research without human intervention.    💡 Automates synthesis and measurement of nanomaterials with AI-driven precision.    🔍 Employs Bayesian optimisation and early stopping technology for rapid discovery.    🛡️ Enhances lab safety with DenseSSD AI vision technology. Read more... 🔗https://lnkd.in/e5S_ZkiT #LabHorizons #KIST #smartlabs #labtechnology #innovation #laboratory #koreauniversity #research #science #computationalscience

“High-performance computing and artificial intelligence are now allowing scientists to rapidly use the elements in the periodic table like a painter might use a palette of colors, mixing them and arriving at new configurations.” Material modeling for specific purpose, welcome to the singularity.

Bionic Technology: bionics, science of constructing artificial systems that have some of the characteristics of living systems. Bionics is not a specialized science but an interscience discipline; it may be compared with cybernetics. Bionics and cybernetics have been called the two sides of the same coin. The science of bionics uses knowledge about how biological systems work to help solve engineering problems. The material Velcro, for example, was inspired by the way burrs behave when they stick to your clothes, and some computer chips are now wired in ways that imitate the "wiring" of the brain and nervous system. #snsinstitutions #snsdesignthinkers #designthinking