Conference Logo ProgramMaster Logo
Conference Tools for 2027 TMS Annual Meeting & Exhibition
Login
Register as a New User
Help
Submit An Abstract
Propose A Symposium
Presenter/Author Tools
Organizer/Editor Tools

About this Abstract
Meeting 2027 TMS Annual Meeting & Exhibition
Symposium Hume-Rothery Symposium: Data-Driven Materials Discovery and Phase Stability
Presentation Title How Computational Modeling Shapes Materials at Apple
Author(s) William Art Counts
On-Site Speaker (Planned) William Art Counts
Abstract Scope Apple products are celebrated for their iconic industrial design, care for the environment, and breakthrough performance, and for the extraordinary manufacturing scale that brings them to customers around the world. Materials design and innovation, powered by computational modeling, is central to that achievement. These models allow Apple engineers to take an integrated computational materials engineering (ICME) approach spanning multiple length scales, virtually designing material solutions that meet the demanding requirements of every Apple product. This talk explores how computational materials science tools and approaches shape materials design in industry.
Proceedings Inclusion? Planned:

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Computational Thermodynamics Framework with Intrinsic Chemical Short-Range Order
Accelerating Oxygen Ion Conductor Discovery Through First-Principles Design and Autonomous Materials Optimization
AI in the Wild: Autonomous laboratories for materials synthesis
Alloy theory applied to the anodes of all-solid-state batteries
Alloying effects on deformation modes in wrought magnesium: An integrated computational and experimental investigation
Atomic-Scale Simulations of Metal/Molten-Salt Interfaces by Machine-Learning Interatomic Potentials
Beyond Order: A Disorder-Aware Workflow toward OQMD 2.0
Beyond Randomness: Designing Short-Range Order for Materials Performance
Bonding-Driven Discovery and Design of Thermoelectric Materials
Calibrated Machine-Learning Uncertainty for Data-Driven Alloy Design
Chemical Intuition as a Guide to Data-Driven Materials Discovery
Computational Design of Battery Guided by Degradation Mechanism
Computational discovery of materials for energy storage
Data- and Simulation-Driven Design of Structural and Functional Materials: Successes and Challenges
Data-Driven Discovery of Novel High-Performance Photovoltaics in an Experimentally Known Family of Quaternary Chalcogenides
Data-driven Prediction of Solid-State Synthesis
Elemental Features for Data-Driven Materials Properties Prediction
Elucidating the role of solute-solute interactions on diffusion in Ni-based substitutional solid solutions
Exploring the electronic structure of all known inorganics - from transport to superconductivity to topology.
First-principles modeling of disorder in cathodes and beyond
From Computational Design to Accelerated Discovery of High-Entropy Alloys
Functional Synthesizability: Tuning the Extreme-Properties of High-Entropy Ceramics
High-Throughput Anharmonic Phonons for Data-Driven Materials Discovery, Phase Stability, and Thermal Transport
How Computational Modeling Shapes Materials at Apple
Hume-Rothery Strikes Again: Intrinsic Correlations Permit Tailored Materials With Exceptional Properties
Integrating Automated Computation with Experiment for Accelerated Materials Discovery
Irreversible Thermodynamic Basis for the Phase-field Method of Ordered Stoichiometric Compounds
Lithium Extraction with Ion Exchange at Lilac Solutions
Mapping Lithium-Ion Transport in Sulfide Argyrodites: From Defect Chemistry to Composite Interfaces
Phase Diagrams On-Demand
Relationship Between Configurational and Vibrational Entropies of Mixing and Their Effects on Phase Diagrams
Standing on Chris's Shoulders: From High-Throughput DFT to AI for Materials Discovery
Symmetry Broken DFT Corrects the Stability and Mott Band Gap Errors Without Adding Strong Correlations
The Generalized Aliasing Decomposition, A New Paradigm for Modeling
The Possibility of New Complex Magnet Material
The Spatial Arrangement of Nanoparticles on Substrates and the Role of Phase Transformations
Theoretical Insights Into Hydrogenation and Proton Transport in ABO3 Perovskite
Thermodynamic and Kinetic Stability of M–N–C Active Sites for O₂ Reduction
Towards Ai-enabled High Throughput Characterization and Materials Discovery
Zentropy: A Thermodynamic Framework Bridging Phase Stability, Data-Driven Modeling, and Artificial Intelligence
Questions about ProgramMaster? Contact programming@programmaster.org | TMS Privacy Policy | Accessibility Statement