MIPAR’s Spotlight democratizes cutting-edge vision intelligence, automating even the most challenging microscopy applications. By combining zero-shot detection with custom-trained models and conventional processing, MIPAR’s platform accelerates materials research, reduces human bias, and extracts previously hidden insights from micrographs—making AI image analysis accessible to all researchers and industry professionals.

An overview of a few non-traditional methods for technical ceramics and other hard & brittle materials. A brief description along with benefits and limitations of ultrasonic machining, high precision grinding and laser micromachining

Zircar Zirconia, Inc. explores the critical design challenges in developing rapid cycle high-temperature furnace modules, essential for advanced manufacturing and thermal processing. The need for materials that withstand corrosive environments, thermal stress resulting from rapid heating and cooling rates, and precise temperature control are some of the determining factors built into the design. The key obstacles include thermal fatigue, energy efficiency, and compatibility with the items being heat treated.

High-performance rare earth magnets have emerged as critical materials for electric vehicles, green energy, and robotics technologies, but intensifying material supply risks are driving a transformation in magnet design and production. Grain boundary engineering and novel jet milling technologies are emerging to improve magnet performance while reducing heavy rare earth content. At the same time, existing manufacturing technologies are increasingly being repurposed for the recycling of rare earth magnets. With large public investment flowing into domestic rare earth magnet supply chains, IDTechEx evaluates the impact of design innovations in the context of emerging magnet production, providing an outlook for the industry over the next decade.

Developments in particle accelerators have greatly benefited from the fundamental understanding of the Nb₃Sn superconductors for advanced high-field magnets and particle accelerators. Here, I will present the exciting ongoing research on Nb₃Sn at the FAMU- FSU, College of Engineering, and the Applied Superconductivity Center (NHMFL) in Tallahassee, FL. The focus will be on the present state of the art and the future technologies that high-current-carrying Nb₃Sn superconducting cables and coatings will enable.

Pandat software has evolved through three generations. The first generation laid the foundation by focusing on thermodynamic and phase diagram calculations rooted in the CALPHAD methodology. The second generation of Pandat, coupling CALPHAD with kinetic simulations, enables predictions of microstructure evolution during processes such as precipitation, diffusion, and solidification. The third-generation Pandat advances its capability by directly coupling with phase-field modeling for simulating three-dimensional microstructure evolution, and with FEM software packages for applications during manufacturing processes. This presentation will focus on the third-generation Pandat software. Examples of integrating with Moose, Ansys and Abaqus will be presented

Dragonfly 3D World offers a versatile platform for volumetric data inspection, segmentation, and analysis. With integrated deep learning tools such as U-Net 3D, image segmentation can be automated to deliver superior performance, including the ability to distinguish pores from fractures. The platform’s intuitive design makes advanced neural network–based workflows accessible to a broad user base. In addition, Dragonfly provides comprehensive quantitative analysis and numerical modeling capabilities, enabling researchers to extract meaningful insights from complex porous structures.

High-entropy materials, complex solids stabilized by configurational disorder, are unlocking new frontiers in energy technology with promising applications spanning clean hydrogen production, waste-heat conversion, energy storage, and nuclear waste immobilization. The Entropy for Energy (S4E) laboratory integrates high-throughput first-principles computation, machine learning, and data-driven design to explore and optimize high-entropy oxides, halides, and alloys. This talk will highlight how harnessing chemical complexity, guided by advanced computational and AI tools within the Materials Genome Initiative framework, accelerates the discovery and development of next-generation energy materials. Join us to learn how these synergistic approaches are streamlining innovation cycles and expanding the landscape of materials for a sustainable energy future.