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📝 Recent Platform Updates Release 2024.7.25 contains updates and UX improvements. We highlight (1) an example Jupyter notebook demonstrating the ability to create point defects in materials, including Interstitials, Vacancies, Substitutions, and Adatoms; (2) add interfacial energy calculation for pre-relaxed interfaces using Foundational models ALIGNN and M3gnet (3) initial support for QE workflows using spin-orbit coupling. Feature: - Point Defect Creation - Add Energy Delta calculation for relaxed interface - Initial support for Spin-orbit coupling Improvement: - Improve Entire collection search Bugfix: - Fix: import from materials project - Fix: workflow update action For Developers: - [Made] Add vacuum adjustment - [Made] Import 3rd party from one file - [Made] Cut section of material to adjust and place back - [Made] Add Basis and Lattice classes - [Made] Select atoms in a box functionality - [Made] Select atoms in a XY triangle projection - [Made] Adatom defect builder equidistant - [Made] Adatom defect builder crystal site More on the highlights in the next additional posts on this topic! 🔜 Share with us, how do you like these changes? 👇 #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

⚛️ Mat3rials 3xplorer. Gallium Nitride with Mg dopant (GaN: Mg), 3 by 3 by 3 supercell. Available online in our materials bank: https://lnkd.in/dp3Nsu8A 😉 Click here to follow our updates: Mat3ra.com #mat3rials3xplorer #materialsscience #mat3ra

💡 Industry News Etched.AI raises US$120m to bet on transformer-only ASIC. Etched.ai Inc. (Cupertino, Calif.), a 2022 startup, has raised US$120 million in Series A round of funding to develop a transformer-only ASIC called Sohu and take on Nvidia. The company claims that because Sohu is architected to run transformer models, which are at the heart of LLMs and such applications as ChatGPT, it is 20x faster than Nvidia N100s. The downside of that is that Sohu cannot execute many traditional AI models. Sohu can’t run CNNs, RNNs or long short-term memory (LSTM) models, deep learning recommendation models (DLRMs); protein-folding models, such as AlphaFold 2, or older image models such as Stable Diffusion 2, the company states. But Etched is fine with that because it reckons almost every state-of-the-art AI model these days is based on transformer software. These include ChatGPT, Sora, Google’s Gemini, Stable Diffusion 3, and many others. “If transformers are replaced by SSMs [State Space Models], RWKV [Receptance Weighted Key Value], or any new architecture, our chips will be useless,” the company admits on its website. More: https://lnkd.in/eHP4c7Q4 Samsung set to delay Texas fab, aim for 2nm in 2026. Samsung is taking steps to delay the beginning of production at its wafer fab in Taylor, Texas, from 2024 to 2026 and is now aiming to start with a 2nm manufacturing process, according to Korea’s ETnews. The paper reported that a decision on the switch to 2nm would be made in the 3Q24. Samsung announced a plan to spend US$17 billion to build its first Taylor fab – and second in Texas – in November 2021 although that budget is thought to have drifted up to about US$20 billion in the interim. That fab was expected to begin production on Samsung’s 4nm node by the end of 2024. However, ETnews reports that Samsung is delaying chipmaking equipment orders pending a decision on whether to shoot for starting at 2nm. One consideration could be the speed of market adoption of AI and the need for leading-edge chips. Leading edge devices are already being produced on 3nm by Samsung rival TSMC for market leader Nvidia. More: https://lnkd.in/d6WWTsdi 👉 Follow our newsletter for more industry news: https://lnkd.in/gNnf9cyx #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

Material of the Month. Phosphorene is a two-dimensional material consisting of phosphorus. It consists of a single layer of black phosphorus, the most stable allotrope of phosphorus. Phosphorene is analogous to graphene. Among two-dimensional materials, phosphorene is a competitor to graphene because it has a nonzero fundamental band gap that can be modulated by strain and the number of layers in a stack. Phosphorene was first isolated in 2014 by mechanical exfoliation. Liquid exfoliation is a promising method for scalable phosphorene production. Researchers have fabricated transistors of phosphorene to examine its performance in actual devices. A phosphorene-based transistor consists of a channel of 1.0 μm and uses a few-layered phosphorene with a thickness varying from 2.1 to over 20 nm. Reduction of the total resistance with decreasing gate voltage is observed, indicating the p-type characteristic of phosphorene. The linear I-V relationship of the transistor at low drain bias suggests good contact properties at the phosphorene/metal interface. Good current saturation at high drain bias values was observed. However, it was seen that the mobility is reduced in few-layer phosphorene when compared to bulk black phosphorus. The field-effect mobility of phosphorene-based transistors shows a strong thickness dependence, peaking at around 5 nm and decreasing steadily with a further increase of crystal thickness. Atomic layer deposition (ALD) dielectric layer and/or hydrophobic polymer is used as encapsulation layers in order to prevent device degradation and failure. Phosphorene devices are reported to maintain their function for weeks with an encapsulation layer, whereas experience device failure within a week when exposed to ambient condition. Available in the Mat3ra platform in: https://lnkd.in/dYmFg6Qt #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

⚛️ Mat3rials 3xplorer. Interface between Gallium Arsenide and Silicon, GaAs(111)/Si(111), strain-matched supercell. Available online in our materials bank: https://lnkd.in/dp3Nsu8A #mat3rials3xplorer #materialsscience #mat3ra

Materials Meme of the week! 🔬 Every Neutron's Dream 🥹 👇 Share with us your favorite science jokes. #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

Job Postings! 🧑🤝🧑 Community Evangelist - https://lnkd.in/gkWRWCGk We look for outgoing people with strong technical backgrounds (Scientists/Engineers) seeking to diversify their skills to help us develop a vibrant global community around the software platform for designing and discovering new advanced materials and chemicals. Work will focus on (1) identifying strategic pathways for community growth, (2) preparing the relevant content, including case studies and technical presentations, (3) delivering content and measuring KPI. ☀️ Computational Materials Scientist - https://lnkd.in/gsM6qr6a We look for computational materials scientists excited about bridging the gap between materials/chemistry, data science, and computer science to help us develop a software framework for designing and discovering new advanced materials and chemicals. Work will focus on (1) the application of nanoscale modeling to large sets of materials, surfaces, and reaction pathways with minimal human input, (2) organizing the data produced by the models and experimental validation, (3) establishing artificial intelligence approaches using the data. All open positions are at https://lnkd.in/gnyVwKsZ Let’s make Iron Man’s Digital Materials R&D experience a reality together! Could this be useful to someone you know? If yes, make a repost! 🤝 #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

⚛️ Mat3rials 3xplorer. Interface between Phosphorene and Gold (P/Au(111)), 2x1x1 matching superlattice. Available online in our materials bank: https://lnkd.in/dp3Nsu8A #mat3rials3xplorer #materialsscience #mat3ra

Research papers we love 🔬 📄 An autonomous laboratory for the accelerated synthesis of novel materials. 👥 Nathan J. Szymanski, Bernardus Rendy, Yuxing Fei, Rishi E. Kumar, Tanjin He, David Milsted, Matthew J. McDermott, Max Gallant, Ekin Dogus Cubuk, Amil Merchant, Haegyeom Kim, Anubhav Jain, Christopher J. Bartel, Kristin Persson, Yan Zeng & Gerbrand Ceder. To close the gap between the rates of computational screening and experimental realization of novel materials we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics. Read more: https://lnkd.in/dgXmW7kM 🤔 What do you think about it? Share with us in the comments 👇 #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology

⚡️ Release 2024.6.20 highlights - The ability to visualize ferromagnetic structures. We highlight the ability to visualize atomic labels as different colors in the materials designer interface to highlight magnetic (anti-ferromagnetic) structures. 👉 Try it for free at https://lnkd.in/gNnf9cyx #materials #RnD #mat3ra #exabyteio #materialsscience #materialsdesign #materialsmodeling #science #technology