About

Ian McCue is an Assistant Professor of Materials Science and Engineering at Northwestern University, holding the Morris E. Fine Junior Professorship in Materials and Manufacturing. He earned his Ph.D. in Materials Science and Engineering from Johns Hopkins University, where he also completed his B.S. in the same field. His research focuses on solving the problem of scalable processing for advanced, nanostructured materials by emphasizing advanced manufacturing and self-organization phenomena. His work aims to push the boundaries of microstructural control during fabrication to create new materials that are stronger, tougher, more thermally stable, and capable of self-repair. His research is divided into key areas including developing new manufacturing processes for nanocomposites for structural applications, studying the mechanical behavior of nanostructured materials, and advancing the fundamental understanding of the relationship between material architecture, diffusion pathways, external fields, and phase transformations.

Research topics

• Computer Science
• Mechanical engineering
• Engineering
• Computer Security
• Artificial Intelligence
• Aerospace engineering
• Aeronautics
• Composite material
• Control engineering
• Materials science
• Condensed matter physics
• Bioinformatics
• Architectural engineering
• Physics
• Mathematics
• Systems engineering
• Nanotechnology
• Biology
• Structural engineering

Selected publications

• Reaction kinetics and phase evolution of nanoporous TaC from metallic precursors

  Acta Materialia · 2026-02-02

  articleSenior authorCorresponding
  PublisherDOI

• Tobaco: topology optimization via band-limited coordinate networks for compositionally graded alloys

  Structural and Multidisciplinary Optimization · 2026-03-17

  articleOpen access

  Abstract Compositionally graded alloys (CGAs) offer unprecedented design flexibility by enabling spatial variations in composition; tailoring material properties to local loading conditions. This flexibility leads to components that are stronger, lighter, and more cost-effective than traditional monolithic counterparts. The fabrication of CGAs have become increasingly feasible owing to recent advancements in additive manufacturing (AM), particularly in multi-material printing and improved precision in material deposition. However, AM of CGAs requires imposition of manufacturing constraints; in particular limits on the maximum spatial gradation of composition. This paper introduces a topology optimization (TO) based framework for designing optimized CGA components with controlled compositional gradation. In particular, we represent the constrained composition distribution using a band-limited coordinate neural network. By regulating the network’s bandwidth, we ensure implicit compliance with gradation limits, eliminating the need for explicit constraints. The proposed approach also benefits from the inherent advantages of TO using coordinate networks, including mesh independence, high-resolution design extraction, and end-to-end differentiability. The effectiveness of our framework is demonstrated through various elastic and thermo-elastic TO examples.

  PublisherOA PDFDOI

• In-Situ Material Characterization of Steel Through High-Speed Imaging During Orthogonal Cutting

  ˜The œminerals, metals & materials series · 2026-01-01

  book-chapterSenior author
  PublisherDOI

• HT-DABI: High-Throughput Extraction of Creep and Static Material Properties of Metallic Alloys via Dimple Array Bulging

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• Correction: Materials laboratories of the future for alloys, amorphous, and composite materials

  MRS Bulletin · 2025-02-28

  articleOpen access
  PublisherOA PDFDOI

• The Morphological and Compositional Stability of Nanoporous UHTCs During Fabrication from Metallic Precursors

  ˜The œminerals, metals & materials series · 2025-01-01

  book-chapterSenior authorCorresponding
  PublisherDOI

• Percolation diagrams derived from first-principles investigation of chemical short-range order in binary alloys

  Scripta Materialia · 2025-12-17

  preprintOpen accessSenior author

  Recent developments in the percolation theory of passivation have shown that chemical short-range order (SRO) affects the aqueous passivation behavior of alloys. However, there has been no systematic exploration to quantify these SRO effects on percolation in practical alloys and the related passivation behavior. In this study, we quantify the effects of SRO on percolation in a binary size-mismatched Cu-Rh alloy and study the related passivation behavior. We develop a mixed-space cluster expansion model trained on the mixing energy calculated using density functional theory. We use the cluster expansion model to sample the configuration space via variance-constrained semi-grand canonical Monte Carlo simulations and develop SRO diagrams over a range of compositions and temperatures. Building on this with the percolation crossover model, specifically the variation of percolation threshold with SRO in the FCC lattice, we construct the first nearest-neighbor chemical percolation diagram. These diagrams can inform the design of the next generation of corrosion-resistant metallic alloys.

  PublisherDOI

• On-the-fly path planning for the design of compositional gradients in high dimensions

  Materials & Design · 2025-04-25 · 1 citations

  articleOpen accessSenior author

  • Surrogate models scale poorly when designing functional gradients in many element systems. • On-the-fly sampling can reduce the number of CALPHAD queries by orders of magnitude. • A relaxed constraint RRT with a bad phase purge operation further enhances efficiency. Functional gradients have recently experienced a surge in research activity due to advances in manufacturing, where compositions can now be spatially varied on-the-fly during fabrication. In addition, modern computational thermodynamics has reached sufficient maturity – with respect to property databases and the availability of commercial software – that gradients can be designed with specific sets of properties. Despite these successes, there are practical limitations on the calculation speeds of these thermodynamic tools that make it intractable to model every element in an alloy. As a result, most path planning is carried out via surrogate models on simplified systems (e.g., approximating Inconel 718 as Ni 59 Cr 23 Fe 18 instead of Ni 53 Cr 23 Fe 18 Nb 3 Mo 2 Ti 1 ). In this work, it is demonstrated that this limitation can be overcome using a combination of on-the-fly sampling and a conjectured corollary of the lever rule for transformations of isothermal paths in arbitrary compositional dimensions. The effectiveness of this new method is quantitatively benchmarked, and it is found that it can be as much as 10 6 times more efficient than surrogate modeling.

  PublisherDOI

• Materials laboratories of the future for alloys, amorphous, and composite materials

  MRS Bulletin · 2025-01-29 · 4 citations

  articleOpen access

  Abstract In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a roadmap for realizing this vision; identify technical bottlenecks and barriers to access; and propose pathways to equitable and democratic access to integrated toolsets in a manner that addresses urgent societal needs, accelerates technological innovation, and enhances manufacturing competitiveness. Spanning three important materials classes, this article summarizes the areas of alignment and unifying themes, distinctive needs of different materials research communities, key science drivers that cannot be accomplished within the capabilities of current materials laboratories, and open questions that need further community input. Here, we provide a broader context for the workshop, synopsize the salient findings, outline a shared vision for democratizing access and accelerating materials discovery, highlight some case studies across the three different materials classes, and identify significant issues that need further discussion. Graphical abstract

  PublisherOA PDFDOI

• Unveiling the Origin of Morphological Instability in Topologically Complex Electrocatalytic Nanostructures

  Journal of the American Chemical Society · 2025-09-06 · 4 citations

  articleOpen accessCorresponding

  Coarsening and degradation phenomena in metals have largely focused on thermally driven processes, such as bulk and surface diffusion. However, dramatic coarsening has been reported in high-surface-area, nanometer-sized Pt-based catalysts during potential cycling in an electrolyte at room temperature─a temperature too low for the process to be explained purely by surface mobility values measured in both vacuum and electrolytes (∼10–22 and ∼10–18 cm2/s, respectively). This morphological evolution must be due to a different mechanism for mass transport that is sensitive to electrochemical conditions (e.g., electrolyte composition, potential limits, and scan rate). However, there have been no notable studies of electrochemically induced coarsening in nanometer-sized electrocatalysts. Here, we unveil the origins of coarsening in an electrolyte through coupled in situ experiments and atomistic kinetic Monte Carlo (kMC) simulations. Our work demonstrates electrochemical coarsening is driven by two concurrent mechanisms that can be explained at the atomistic level: (i) dissolution/redeposition during the reduction of an oxidized species and (ii) rapid surface diffusion of undercoordinated atoms.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Compositional and Atomic-Scale Ordering Effects on Aqueous Passivation of Binary BCC and FCC Alloys

  NSF · $466k · 2022–2026

Frequent coauthors

• Jonah Erlebacher

  61 shared

• K. Sieradzki

  Arizona State University

  41 shared

• Alain Karma

  39 shared

• Mingwei Chen

  Johns Hopkins University

  38 shared

• J. Eckert

  Austrian Academy of Sciences

  36 shared

• Qing Chen

  Peking University Shenzhen Hospital

  36 shared

• Jörg Weißmüller

  Universität Hamburg

  36 shared

• Sean Hearne

  36 shared

Awards & honors

• Invited Speaker, Gordon Research Conference – Physical Metal…
• Materials Research Society Graduate Student Award, Silver (2…