CDCM Seed Projects

CDCM Seed Projects enable the Center to engage new faculty members and provide flexibility to incorporate emerging, potentially transformative research directions. Broad participation, including junior faculty members and small, interdisciplinary teams engaged in emerging areas of research, are emphasized. Open calls for seed project proposals will be issued annually. 

Strained soft materials to create asymmetry and emergent functionality
- Dr. Alexander Marras, Walker Department of Mechanical Engineering

This seed project aims to develop smart bioinspired materials by leveraging hierarchical design principles to achieve coordination of stochastic molecular components into asymmetric non-equilibrium architectures capable of autonomous lifelike emergent behavior. This approach is inspired  by cells and tissues, which exceed current engineered materials in capabilities, including adaptive structure, transport, self-healing, and efficient energy conversion, enabled by hierarchical materials that couple stochastic molecular processes with macroscale behaviors. For example, cell membranes are asymmetric at both molecular (lipid composition) and macroscopic levels, enabling compartment formation and directed motion, respectively. In tissue, asymmetry drives collective behavior of cells for transport, morphogenesis, and large-scale signaling. Dynamic biomimetic materials with asymmetric adaptable structures that respond to molecular signals could revolutionize fields including nano/microelectronics, soft robotics, smart textiles and coatings, and provide a foundation for future technologies in quantum materials. DNA nanotechnology, with its structural programmability and stimuli responsiveness, enables unique molecular-scale sensing, actuation, and signal processing. Prior work from our team members and others establishes dynamic DNA nanomaterials for molecular detection, probing molecular processes and reconfigurable assemblies. However, DNA materials alone cannot reach macroscales. Bridging this gap requires a team effort to address the key challenge of transducing dynamics asymmetrically across materials and scales. We propose a hybrid, bio-synthetic platform leveraging nanomechanical DNA structures triggered by DNA aptamers to transduce molecular events into local reconfiguration to orchestrate  collective dynamic behavior in lipid materials at meso- to macro-scales. Key questions include: (1) How  nanostructure and membrane properties affect coupling across length-scales; (2) How the distribution of  molecular assemblies affects collective function; and (3) How asymmetric organization enables coordination of stochastic nanoscale processes. Close integration of experiments and modeling will guide  design of hierarchical anisotropic materials to help fill this gap. Foundational efforts include high-order assembly of DNA aptamers, nanostructures, or nanoparticles, integration of nanostructures with polymers or in lipid membranes that include biomolecular  interactions but lack the structural organization required to direct large-scale processes. This seed project  will take a major step forward by integrating DNA aptamers to trigger dynamic DNA origami mechanisms embedded in lipid membranes (Figure 1). Dynamic behavior will be organized asymmetrically to translate molecular signals to large-scale anisotropic material property responses. This approach will enable new understanding of how stochastic molecular interactions can trigger emergent material properties, building 
towards an IRG on multiscale materials with lifelike behavior. 

High Entropy Ultrawide-Bandgap Nitrides: Polarization Physics in Complex Semiconductor Alloys
- Dr. Xiuling Li, Chandra Department of Electrical and Computer Engineering. 

Ultrawide-bandgap (UWBG) semiconductors are emerging as a foundational platform for next
generation electronics, photonics, and sensing technologies operating under extreme conditions
including high temperature, high voltage, and radiation environments. Materials such as AlN, GaN,
and related nitride alloys exhibit exceptionally large bandgaps, high breakdown electric fields, and
superior thermal stability. These properties enable devices with dramatically reduced Size, Weight,
Power, and Cost (SWaP-C) compared with conventional semiconductor technologies.
High-entropy materials have transformed alloy design in metals and oxides by enabling new phases and compositions inaccessible in conventional binary or ternary systems.1 However, this concept remains largely unexplored in ultrawide-bandgap semiconductors. Recently, a new class of materials, ferroelectric nitrides, has emerged within the III-nitride family. Alloying AlN with transition or rare-earth metals such as Sc, Y, and La introduces switchable polarization while preserving the wide bandgap and high Curie temperature characteristic of nitride semiconductors. These materials combine semiconductor functionality with ferroelectric order, creating
opportunities for polarization-driven electronics and new high-field transport phenomena. Furthermore, increasing compositional complexity in these alloys is predicted to modify the polarization energy landscape, reduce coercive fields, and stabilize structural phases that cannot be realized in conventional nitrides. These effects arise from the interplay of configurational entropy, strain accommodation, and defect energetics. Very recent DFT calculations3 (Fig. 1) shows that high configurational entropy can compensate positive formation enthalpy (Ehull), stabilizing multicomponent nitride alloys while simultaneously distorting the wurtzite lattice. These distortions modify the polarization energy landscape and may enable new polarization states inaccessible in conventional nitrides. However, the microscopic origins of polarization switching, defect formation, and structural stability in these materials remain poorly understood.
We propose to investigate a new materials platform based on multicomponent nitride alloys of the form: Al(XYZ)N where X, Y, Z = Sc, Y, La, B, Ga, or In. The problem we aim to experimentally address is - can configurational entropy create new polarization states in ultrawide-bandgap semiconductors? This problem requires an integrated approach combining advanced epitaxial synthesis, ultrafast Xray characterization, surface/interface science, and data-driven materials discovery. The proposed seed project establishes an interdisciplinary collaboration across electrical engineering, physics, and mechanical engineering to explore entropy-stabilized UWBG semiconductors and polarization driven phenomena in complex nitride alloys. Vision: If configurational entropy can stabilize new polarization states in ultrawide-bandgap semiconductors, it would establish a fundamentally new materials design strategy for semiconductor physics.

Accelerated Discovery of Wadsley-Roth Phase Bimetallic Oxides for Fast Electrochemical Storage of Earth-Abundant Ions - Dr. Kent Zheng, McKetta Department of Chemical Engineering 

Currently, the most effective battery chemistries depend on Li-ion intercalation into host crystal structures, enabling reversible energy storage and release.1,2 Looking ahead, sustainable energy storage must address two key challenges: (1) diversifying beyond Li-ion chemistries, given Li’s scarcity in the Earth’s crust (abundance: 20 ppm) and geopolitical risks tied to Li- and Co-related minerals,3-5 and (2) enabling faster charging to broaden applications in electric vehicles and enhance grid storage efficiency.6,7 However, affordable Earth-abundant ionslike Na+ (23,600 ppm), Mg2+ (23,300 ppm), andAl3+ (82,300 ppm) present significant hurdles. Their larger size or higher charge density compared to Li+ disrupts host material lattices, slowing ion diffusion and reducing reversibility.8,9 The study of Li-ion storage materials has been ongoing for decades;1,10 we cannot afford to wait that long for post-Li-ion technologies key to carbon net zero by 2050.11 Discovering new materials that rapidly and reversibly store these ions requires holisticcodesign tailoring structures across multiple scales—from lattice (Å), to particle morphology (nm to µm), and electrode architecture (10 to 100 µm)—to render target ion storage behavior.12,13 Departing from conventional methods, we propose a synergistic data- and model-guided experimental approach to significantly accelerate the discovery of principles governing the electrochemical storage of Earth-abundant ions, focusing on structure-property relationships in materials with multiscale structural features optimized for such ions. While traditional experimental synthesis and measurement offer high accuracy, exhaustively studying ion storage behavior in a single material system can take years. Exploring the entire design space (i.e., chemical composition, stoichiometry, crystal structure, defect/doping, and particle morphology) using traditional trial-and-error approaches requires an impractically vast amount of time and research resources. To overcome this limitation, we will develop models using density functional theory (DFT) to generate a large volume of physics-based simulated data. This dataset will be used to train machine learning (ML) algorithms. The predictions made by ML will be assessed experimentally, forming an iterative feedback loop: Experiment-Model-Machine Learning-Experiment (EMME). We identify Wadsley-Roth (W-R) phase bimetallic oxide as a model material system to establish, refine, and validate the proposed EMME approach in our one-year seed project. The choice of W-R phase bimetallic oxides is driven by their unique, chemically tunable crystal structures (Fig. 1). 14 Specifically, W-R phases exhibit 1D open channels of unusually large size, formed by ReO3-like corner-sharing [MO6] octahedra. However, unlike a pure ReO3 structure, W-R phases also contain edge-sharing [MO6] octahedra within so-called “shear planes,” which provide structural stability during ion intercalation. Most importantly, these structural features—the size and arrangement of the 1D channels and the prevalence of shear planes—are highly tunable by adjusting the ratio between the two constituent transition metals.15 These features at small length scales give rise to unconventional ultrafast Li-ion transport behavior. For example, W-R phase Titanium Niobium Oxide (TNO) have demonstrated an exotic regime called “intercalation pseudo-capacitance” giving rise to unprecedented rate capability for Li-ion storage, making TNO an emerging commercial Li-ion anode Fig. 1: Crystal structure of W-RTiNb2O7. 2 Zheng,Kent-#7190 40 of 160 material.16,17 Unfortunately, such unconventional ion transport and storage behavior has yet to be realized for Earth-abundant ions, such as Na+; the charge-discharge is dominated by surface processes,18-20 rather than utilization of entire particles.

Designing 3D-Printable Materials that Mimic Soft Interfacial Gradients in Natural Systems (SIGNS) - Dr. Zachariah Page, McKetta Department of Chemical Engineering 

Materials with mechanical gradients between stiff and soft domains are ubiquitous in nature. From bird talons to turtle shells to muscle-bone junctions, these Soft Interfacial Gradients in Natural Systems (SIGNS) synergistically impart bulk strength and toughness, while enabling programmable movement.1–4 However, our ability to produce synthetic analogs of SIGNS with geometric precision is lacking.5–7 Emergent light-based 3D printing technologies offer a promising approach through its precise, rapid, and cost-effective fabrication of complex materials, but still falls short of the desired continuum of material properties.8–11 Achieving SIGNS requires new design principles linking structure, processing, and properties in 3D-printable materials. Success herein would be transformative for a myriad of technologies, including soft robotics, wearable electronics and personal protective equipment. This proposal integrates resin development, material modeling, and mechanical characterization to advance all-polymer 3D-printed composites (Fig. 1). We envision a direct route to enrich these efforts in a future IRG, extending beyond mechanical gradients to optical, thermal, and electrical properties, leveraging theory from atomistic to macro scales and accelerating progress via machine learning. The interdisciplinary nature of 3D printing fosters research and educational collaborations across UT Austin, with outreach through Texas InventionWorks aligning with MRSEC’s core mission.