<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Materials Design, Inc.]]></title><description><![CDATA[Materials Design, Inc. is the leading atomistic simulation software and services company for materials  science.]]></description><link>https://www.materialsdesign.com/news</link><generator>RSS for Node</generator><lastBuildDate>Wed, 07 Oct 2026 07:18:28 GMT</lastBuildDate><atom:link href="https://www.materialsdesign.com/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Materials Design Invited to Deliver Seminar at Nazarbayev University - Dr. Eyert will deliver a seminar entitled “Multiscale Modeling for Transition-Metal Oxides"]]></title><description><![CDATA[During his visit, scheduled for 2-6 October 2026, Dr. Eyert will deliver a seminar entitled “Multiscale Modelling for Transition-Metal Oxides" and engage in scientific discussions with faculty, researchers, and students from the School of Engineering, the Institute of New Materials and Energy Technologies, and the National Laboratory ]]></description><link>https://www.materialsdesign.com/post/materials-design-invited-to-deliver-seminar-at-nazarbayev-university</link><guid isPermaLink="false">6a92bf1a94a35c6c99d59673</guid><pubDate>Thu, 17 Sep 2026 13:36:01 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_ebb56555085541b480d2759a7aacc798~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Materials Design presents at SEMICONUZ 2026 Tashkent, Uzbekistan &#38; brings MedeA Training to Namangan State University]]></title><description><![CDATA[The conference focuses on bridging fundamental semiconductor physics, device engineering, system-level integration, and industrial applications, with particular emphasis on technologies enabling energy transition, digitalization, and advanced manufacturing. Special attention is given to development opportunities, infrastructure building, and international collaboration relevant to Uzbekistan and the broader Central Asian region. Dr Volker Eyert, Senior Scientist at Materials Design, will present]]></description><link>https://www.materialsdesign.com/post/materials-design-presents-at-semiconuz-2026-tashkent-uzbekistan-brings-medea-training-to-namangan</link><guid isPermaLink="false">6a92b0874f7694ed1ed9b6af</guid><pubDate>Mon, 07 Sep 2026 22:00:00 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_6554c45405c84f749255f34926e10a7d~mv2.png/v1/fit/w_1000,h_542,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Webinar: Modeling Defects in Solids with DFT, doped and ShakeNBreak]]></title><description><![CDATA[Learn how to model point defects in solids using Density Functional Theory (DFT). This webinar covers modern defect modelling workflows, ShakeNBreak for identifying ground-state defect structures, the doped Python package for reproducible charged-defect calculations, non-radiative charge capture in semiconductors, and the role of machine learning in accelerating materials discovery.]]></description><link>https://www.materialsdesign.com/post/webinar-modeling-defects-in-solids-with-dft-doped-and-shakenbreak</link><guid isPermaLink="false">6a8bc8494e12adafbf7e68aa</guid><pubDate>Mon, 24 Aug 2026 04:49:33 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_433a582e4a2d4d1c8bb9357b046a04ca~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[MedeA 3.13: Free 6-Month OVITO Pro Trial + Direct Export]]></title><description><![CDATA[A Complimentary Six-Month OVITO Pro Trial for MedeA Users - Starting with MedeA 3.13, users can export structures, structure lists, and trajectories directly to OVITO Pro and receive a complimentary six-month OVITO Pro trial license to jumpstart their analysis.]]></description><link>https://www.materialsdesign.com/post/medea-3-13-free-6-month-ovito-pro-trial-direct-export</link><guid isPermaLink="false">6a7215d82df0f1eeb2f3506e</guid><pubDate>Tue, 04 Aug 2026 17:27:36 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_031e1b87ffeb44a283b2efca05547d75~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[What's New in MedeA 3.13 - Atomic Insights at Scale]]></title><description><![CDATA[Materials Design announces MedeA® 3.13, the latest release of its comprehensive materials simulation environment, delivering significant advances across model building, simulation, and analysis. This release brings atomic insights at scale — empowering researchers to tackle larger, more complex systems with greater speed and confidence...The highly anticipated update to VASP 6.6.0 offers a new and very accurate NMR chemical shift computation for solids within the so-called ZORA approximation.
]]></description><link>https://www.materialsdesign.com/post/what-s-new-in-medea-3-13-atomic-insights-at-scale</link><guid isPermaLink="false">6a446876f5f40624272b5e2b</guid><pubDate>Thu, 02 Jul 2026 05:21:01 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_72da9f619de447d0a9051e17a72fc9cf~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Webinar: Predictive Multiscale Simulation for Advanced Materials: From Machine-Learned Atomistics to Microstructure Evolution]]></title><description><![CDATA[This webinar presents a single, parameter-free simulation workflow that runs from density functional theory to machine-learned interatomic potentials to continuum phase-field modeling, drawing all parameters from atomistic calculations rather than empirical fits. Through case studies in zirconium cladding corrosion, hydride formation and fracture, tritium trapping in oxidized tungsten, and radiation damage, Kyle will show how one atomistics-to-continuum pipeline built on MedeA moves materials...]]></description><link>https://www.materialsdesign.com/post/webinar-predictive-multiscale-simulation-for-advanced-materials-from-machine-learned-atomistics-to</link><guid isPermaLink="false">6a413b3469b2dfbbf12608ff</guid><pubDate>Wed, 24 Jun 2026 06:16:57 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_355d7b1ea61d4bcf8f180a278011d937~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Exploring Machine-Learned Potentials for Transition-Metal Oxides at FM&#38;NT 2026 in Riga]]></title><description><![CDATA[Dr. Eyert will deliver a talk titled "Machine-Learned Potentials for Transition-Metal Oxides." Transition-metal oxides are a class of materials with diverse and valuable properties, including magnetism, superconductivity, and catalytic activity. Understanding and predicting their behavior is crucial for developing new technologies in energy, electronics, and photonics.]]></description><link>https://www.materialsdesign.com/post/exploring-machine-learned-potentials-for-transition-metal-oxides-at-fm-nt-2026-in-riga</link><guid isPermaLink="false">6a39a5ccbde01eb602749fae</guid><pubDate>Mon, 01 Jun 2026 13:00:38 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_576407b2f6ea4e838b17348891f22a13~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Materials Design to Present Predictive Multiscale Nuclear Materials Research at GE Vernova Materials Frontiers Symposium]]></title><description><![CDATA[Kyle Starkey will present new research demonstrating a predictive multiscale modeling framework for zirconium corrosion in nuclear reactor environments. The work integrates first-principles calculations, machine-learned interatomic potentials, molecular dynamics, and continuum phase-field modeling to better understand the degradation mechanisms affecting zirconium alloy cladding in light water reactors.]]></description><link>https://www.materialsdesign.com/post/materials-design-to-present-predictive-multiscale-nuclear-materials-research-at-ge-vernova-materials</link><guid isPermaLink="false">6a39a5ccbde01eb602749f60</guid><pubDate>Wed, 27 May 2026 13:54:45 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_a9bba2267ded4b1db36263d8b140f36c~mv2.png/v1/fit/w_1000,h_774,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Multiscale Phase Field Modeling: Extending Classical FEA for Microstructure and Damage Driven Problems]]></title><description><![CDATA[Dr. Alexander Mavromaras will be presenting: “Multiscale Phase Field Modeling: Extending Classical FEA for Microstructure and Damage Driven Problems.”
This presentation explores how phase field modeling can extend traditional finite element analysis (FEA) workflows by enabling the simulation of evolving microstructures, moving interfaces, oxidation, crack formation, and coupled degradation processes that are difficult to capture with classical continuum approaches alone.]]></description><link>https://www.materialsdesign.com/post/multiscale-phase-field-modeling-extending-classical-fea-for-microstructure-and-damage-driven-proble</link><guid isPermaLink="false">6a39a5cbbde01eb602749f10</guid><pubDate>Fri, 15 May 2026 19:59:05 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_0f4ba8aa78564a9ca3b66de9180eb736~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Webinar: Machine-Learned Potentials: DFT-Level Accuracy for Real-World R&#38;D]]></title><description><![CDATA[This webinar will share several case studies showcasing how the integrated machine-learning workflow in MedeA 3.12 can accelerate your research, streamline the adoption of MLPs, and move beyond the limitations of standard first-principles methods.]]></description><link>https://www.materialsdesign.com/post/webinar-machine-learned-potentials-dft-level-accuracy-for-real-world-r-d</link><guid isPermaLink="false">6a39a5ccbde01eb60274a098</guid><pubDate>Fri, 15 May 2026 11:25:50 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_7ea87e0ccca44eaca601e1c5dd3c065d~mv2.jpg/v1/fit/w_1000,h_911,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Intellegens and Materials Design, Inc. Collaborate to Accelerate Materials Research]]></title><description><![CDATA[Cambridge, UK and San Diego, CA – 12 May, 2026 Intellegens and Materials Design, Inc., today announced a collaboration enabling materials research organizations to combine advanced machine learning and the full range of materials simulation methods, delivering insights that speed up development of new and improved materials and processes. Alchemite™ machine learning from Intellegens extracts valuable information from research data, identifying key relationships that drive material properties...]]></description><link>https://www.materialsdesign.com/post/intellegens-and-materials-design-inc-collaborate-to-accelerate-materials-research</link><guid isPermaLink="false">6a39a5ccbde01eb60274a097</guid><pubDate>Tue, 12 May 2026 19:02:53 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_2fd1564b7c9b480e98d30297fed5c077~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Webinar: High-Throughput Molecular Simulations for Gas Sorption in Polymers: Automated Workflows for Industrial Materials Design ]]></title><description><![CDATA[Discover how automated high-throughput Molecular Dynamics (MD) and Monte Carlo (MC) workflows enable accurate prediction of gas sorption, isotherms, and polymer swelling in industrial polymer systems. This webinar demonstrates how molecular simulations accelerate material selection, membrane and packaging design, and process optimization while reducing experimental screening effort and time-to-results.]]></description><link>https://www.materialsdesign.com/post/webinar-high-throughput-molecular-simulations-for-gas-sorption-in-polymers-automated-workflows-for</link><guid isPermaLink="false">6a39a5ccbde01eb60274a020</guid><pubDate>Wed, 18 Feb 2026 23:59:09 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_02e0a27cc1ff4967b3ab27aba6b027b8~mv2.png/v1/fit/w_1000,h_770,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Technical Workshop: Modeling Insights: From Femto to Micro, Bridging Length and Time Scales with MedeA]]></title><description><![CDATA[Recent advances in computational materials science are increasingly driven by multiscale modeling, machine learning, and major improvements in theoretical frameworks and computational performance. Artificial intelligence plays an ever more central role in materials discovery and optimization by enabling systematic screening, accelerated exploration of configurational space, and quantitative property prediction. However, machine learning approaches rely on high‑quality, materials‑specific data...]]></description><link>https://www.materialsdesign.com/post/technical-workshop-modeling-insights-from-femto-to-microbridging-length-and-time-scales-with-medea</link><guid isPermaLink="false">6a39a5ccbde01eb602749f5f</guid><pubDate>Fri, 13 Feb 2026 17:08:14 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_216f6990fb254420ad866a47e20ea4e9~mv2.png/v1/fit/w_910,h_478,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[ACEworks and Materials Design to continue their successful collaboration in the field of Machine-Learned Potentials]]></title><description><![CDATA[ACEworks  and Materials Design are rolling forward their successful collaboration with the full integration of the GRACEmaker code of ACEworks in the MedeA  computational environment. The GRACEmaker code is based on the Graph Atomic Cluster Expansion (GRACE), one of the most advanced methods for the generation of Machine-Learned Potentials (MLPs). MedeA  3.12  provides comprehensive support of the leading GRACE 1L and 2L potentials in MedeA  LAMMPS . This includes access to the most recent...]]></description><link>https://www.materialsdesign.com/post/aceworks-and-materials-design-to-continue-their-successful-collaboration-in-the-field-of-machine-lea</link><guid isPermaLink="false">6a39a5cbbde01eb602749f38</guid><pubDate>Mon, 09 Feb 2026 17:25:32 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_a8f9e0798a3d4495a707a1dfbb1aa0f2~mv2.png/v1/fit/w_1000,h_872,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[VASP and Supercomputers – a Marriage made in Heaven]]></title><description><![CDATA[The shift from physical laboratories to in-silico research has transformed materials science, with the Vienna Ab initio Simulation Package (VASP) at its core. As the world’s most widely used density functional theory (DFT) code, VASP drives digital twins, machine learning, and GPU-accelerated simulations on leading supercomputers. MedeA uniquely integrates VASP with workflow automation, job management, and analysis, enabling productive, reproducible, and scalable materials discovery.]]></description><link>https://www.materialsdesign.com/post/vasp-and-supercomputers-a-marriage-made-in-heaven</link><guid isPermaLink="false">6a39a5cebde01eb60274a123</guid><pubDate>Fri, 30 Jan 2026 16:37:06 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_f7f1de9d6ff84c0c98cf0c5803be22ce~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Gerhard Engel</dc:creator></item><item><title><![CDATA[Webinar: Problem Solving in the Golden Age of Computational Materials Science ]]></title><description><![CDATA[Join this webinar to see how highly efficient software such as VASP, unprecedented compute power, and intuitive multiscale modeling have made computational materials science central to R&#38;D. Learn how these tools can optimize electronic devices, engineer organic–inorganic interfaces, unravel reaction mechanisms, study hydrogen diffusion, tailor polymer properties, and predict stress in PVD-grown thin films.]]></description><link>https://www.materialsdesign.com/post/webinar-problem-solving-in-the-golden-age-of-computational-materials-science</link><guid isPermaLink="false">6a39a5ccbde01eb602749f5e</guid><pubDate>Tue, 20 Jan 2026 17:48:08 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_bae74bc0238e41e19d25c95fff09813c~mv2.png/v1/fit/w_721,h_510,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Join Us at the MCC-VASP Workshop 2026 at LSBU Hub London for Insights and Networking]]></title><description><![CDATA[We are excited to announce our participation and support for the  MC C-VASP Workshop 2026,  taking place  January 19–21, 2026  at the  LSBU Hub, London South Bank University . This workshop is designed for both  new and experienced users of VASP  on  ARCHER2 HPC  and other UK high-performance computing platforms. It will bring together  VASP users, developers, and HPC experts  to share best practices, troubleshoot challenges, and explore recent VASP features and their implementation on...]]></description><link>https://www.materialsdesign.com/post/join-us-at-the-mcc-vasp-workshop-2026-at-lsbu-hub-london-for-insights-and-networking</link><guid isPermaLink="false">6a39a5ccbde01eb602749f88</guid><pubDate>Thu, 08 Jan 2026 18:57:33 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_79da70d2754040faab82d5e8a68cbd08~mv2.webp/v1/fit/w_800,h_400,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Materials Design Releases MedeA 3.12 —Train.Deploy.Discover]]></title><description><![CDATA[Materials Design announces MedeA 3.12, materials simulation environment, delivering a revolutionary integration of machine learning capabilities that transform materials modeling workflows. The MedeA 3.12 release establishes a comprehensive machine-learned potential ecosystem spanning training, refinement, deployment, and analysis, while introducing powerful new builders for complex microstructures and enhanced tools for materials discovery.]]></description><link>https://www.materialsdesign.com/post/materials-design-releases-medea-3-12-train-deploy-discover</link><guid isPermaLink="false">6a39a5cbbde01eb602749f37</guid><pubDate>Tue, 23 Dec 2025 00:14:01 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_63d583c199f146db8df9862e1705fb15~mv2.png/v1/fit/w_1000,h_983,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Happy Holidays from Materials Design]]></title><description><![CDATA[The dendritic growth of the snowflakes was simulated using Materials Design’s phase field technology.]]></description><link>https://www.materialsdesign.com/post/happy-holidays-phasefield</link><guid isPermaLink="false">6a39a5cbbde01eb602749f36</guid><pubDate>Mon, 22 Dec 2025 15:12:41 GMT</pubDate><enclosure url="http://video.wixstatic.com/video/541861_f6a75a0d0f1e40c7a4c5713831bf9048/1080p/mp4/file.mp4" length="0" type="video"/><dc:creator>khollingsworth9</dc:creator></item><item><title><![CDATA[Webinar: Precision at Scale with Machine-Learned Potentials ]]></title><description><![CDATA[Join this webinar and explore how MLPs extend DFT accuracy to large, complex systems and long time scales. Learn how MedeA’s MLP Generator streamlines training, enables advanced materials-property predictions, and supports real-world research in corrosion, phase stability, defects, and catalysis. Ideal for scientists and engineers in multiscale modeling.]]></description><link>https://www.materialsdesign.com/post/webinar-precision-at-scale-with-machine-learned-potentials</link><guid isPermaLink="false">6a39a5ccbde01eb60274a0e6</guid><pubDate>Sat, 06 Dec 2025 04:19:36 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/541861_779f72663356409b8aa8152ffce984a8~mv2.png/v1/fit/w_1000,h_872,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>khollingsworth9</dc:creator></item></channel></rss>