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Highlights

Interpretable ML for Crystal Energy Landscapes Using Kolmogorov-Arnold Networks
Interpretable ML for Crystal Energy Landscapes Using Kolmogorov-Arnold Networks
Apr 10, 2026
The University of Tennessee - Knoxville

Interpretable ML for Crystal Energy Landscapes Using Kolmogorov-Arnold Networks

The University of Tennessee, Knoxville's Center for Advanced Materials and Manufacturing has introduced the Element-Weighted Kolmogorov–Arnold Network, a novel interpretable ML architecture that predicts crystal energy landscape properties — formation energy, band gap, and work function — directly from chemical composition. EWKAN achieves state-of-the-art accuracy across large-scale databases, matching or exceeding GNN-based models that require full 3D atomic structure inputs, while using orders of magnitude fewer parameters.
AI Enabled Quantum Chemical Accuracy for Helium-Benzene Interactions
AI Enabled Quantum Chemical Accuracy for Helium-Benzene Interactions
Apr 2, 2026
The University of Tennessee - Knoxville

AI Enabled Quantum Chemical Accuracy for Helium-Benzene Interactions

An interdisciplinary team of CAMM IRG1 researchers developed a quantitatively reliable helium-benzene potential energy surface with quantum chemical accuracy by combining CCSD(T)/CBS electronic-structure and a multifidelity Gaussian process model that merges sparse high-accuracy data with dense lower-cost DFT data. This is an important result for a weakly bound quantum system in which small errors in the interaction potential lead to materially different many-body predictions.
Machine Learning for Materials Discovery: Hackathon
Machine Learning for Materials Discovery: Hackathon
Mar 5, 2026

Machine Learning for Materials Discovery: Hackathon

The Center for Advanced Materials & Manufacturing (CAMM) launched a biweekly “Machine Learning for Materials Discovery” Hackathon, bringing together students and researchers from materials science, physics, and data science to explore how AI can accelerate materials design. Over 5 intensive sessions since October 2025, participants worked through hands-on problems that linked real experimental data to modern machine learning workflows.
Microscopic Fingerprint of Chiral Superconductivity
Microscopic Fingerprint of Chiral Superconductivity
Mar 2, 2026

Microscopic Fingerprint of Chiral Superconductivity

Chiral superconductivity — a long-sought quantum phase with potential applications in quantum technologies — has eluded definitive microscopic confirmation for decades. While several candidate materials exhibit signatures of time-reversal symmetry breaking, such evidence alone does not prove chiral Cooper pairing.
Persistence of Small Polarons in Doped Bismuthate Superconductors
Persistence of Small Polarons in Doped Bismuthate Superconductors
Oct 22, 2025
Big Idea: Harnessing the Data Revolution

Persistence of Small Polarons in Doped Bismuthate Superconductors

University of Tennessee, Knoxville (UTK) Center for Advanced Materials and Manufacturing (CAMM)

In a paper titled Persistence of Small Polarons in Doped Bismuthate Superconductors, researchers study Ba1−xKxBiO3, which becomes a high-Tc superconductor when doped into a charge-density-wave insulator. They show that short-range lattice distortions and strong electron-phonon coupling persist into the metallic phase. Using resonant inelastic x-ray and neutron scattering plus modeling, the team suggests BKBO’s metallic state is an unusual bipolaronic liquid with persistent polarons.
Expanding CAMM’s Impact: REU Summer Outreach with Knoxville Youth
Expanding CAMM’s Impact: REU Summer Outreach with Knoxville Youth
Aug 28, 2025
The University of Tennessee - Knoxville

Expanding CAMM’s Impact: REU Summer Outreach with Knoxville Youth

University of Tennessee, Knoxville (UTK) Center for Advanced Materials and Manufacturing (CAMM)

The Center for Advanced Materials and Manufacturing (CAMM) engaged hundreds of high school students through lab tours and discussions during the 2024-2025 school year. Over the summer, CAMM expanded its outreach to younger students in Knoxville, working with local community centers to host hands-on STEM workshops. Activities included tensile testing, materials games, and demonstrations with ferrofluids and shape memory alloys. This initiative not only educated local youth but also enhanced awareness of CAMM’s programs while providing valuable experience for student participants.
Trajectories among Experimenta con PREM students and comparable cohort of UPRH students. A) Fields of study identified in ECP application, college admission, and bachelor’s degree graduation for ECP students who graduated or have been enrolled in a bachelor’s program (N = 232) for 6 years or more. b) Same data from (a), organized by specific fields of study. c) Fields of admission and graduation for UPRH students from freshman classes 2011–2017, enrolled in STEM or Health programs at some point during their studies (N = 2258)
Trajectories among Experimenta con PREM students and comparable cohort of UPRH students. A) Fields of study identified in ECP application, college admission, and bachelor’s degree graduation for ECP students who graduated or have been enrolled in a bachelor’s program (N = 232) for 6 years or more. b) Same data from (a), organized by specific fields of study. c) Fields of admission and graduation for UPRH students from freshman classes 2011–2017, enrolled in STEM or Health programs at some point during their studies (N = 2258)
May 22, 2025
University of Pennsylvania

Experimenta Con PREM: Documenting Two Decades of Impact

Idalia Ramos, U. Puerto Rico, Humacao and Eric Stach, U. Pennsylvania
An article in the journal MRS Advances documented the outcomes of a summer research program for high school students based at the University of Puerto Rico, in partnership with the Penn MRSEC. Over the past two decades this program has engaged nearly 400 students in hands-on materials science research since 2005, with 84% pursuing STEM undergraduate studies.
Images: REU students presenting their research to a high school audience and to fellow program participants and other research groups.
Images: REU students presenting their research to a high school audience and to fellow program participants and other research groups.
May 22, 2025
University of Pennsylvania

REU: New Emphasis on Science Communication

Mark Licurse & Ashley Wallace, University of Pennsylvania
This University of Pennsylvania program immerses students in hands-on materials research while incorporating a recently piloted initiative: training participants to become effective science communicators. While students spend 10 weeks conducting advanced research projects, they simultaneously develop crucial skills in translating complex scientific concepts for broader audiences, particularly younger students.
Under the right conditions, liquid crystals form astonishing structures reminiscent of biological systems, shown here in actual (left) and false color (right), with the filaments in light blue and the flattened discs in yellow. (Credit: Christopher Browne)
Under the right conditions, liquid crystals form astonishing structures reminiscent of biological systems, shown here in actual (left) and false color (right), with the filaments in light blue and the flattened discs in yellow. (Credit: Christopher Browne)
May 22, 2025
University of Pennsylvania

Self-Assembling Networks: A New Structured Fluid Architecture Through Phase Separation

Chinedum Osuji, University of Pennsylvania
Scientists at the University of Pennsylvania discovered a unique self-assembling network structure that forms when certain liquid crystal materials separate. These networks spontaneously create intricate patterns of filaments and disc-shaped structures through a series of physical transformations driven by competing forces.
Building Rigid Networks with Prestress and Selective Pruning
Building Rigid Networks with Prestress and Selective Pruning
May 22, 2025
Big Idea: Machine Learning / Artificial Intelligence

Building Rigid Networks with Prestress and Selective Pruning

John Crocker and Andrea Liu, University of Pennsylvania
Researchers John Crocker and Andrew Liu at the University of Pennsylvania have discovered that biopolymer networks pruned by tension-inhibited methods remain rigid at much lower coordinations than those pruned randomly. This finding helps explain the evolutionary advantage of tension-inhibited filament-severing proteins in biological systems.

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