Faculty Name: Nicholas Rolston
Experimental
Research Area: Nanoscience and Materials Physics
Research Title: Inorganic Metal Halide Perovskites for Direct Alphavoltaic Converters
Research/Project Short Description: One of the key drawbacks of photovoltaic devices is the intermittency of power generation based on limited solar radiation. Radioactive sources that involve alpha particle emitting isotopes have continuous decay processes with long half-life can provide a source of extended and reliable power generation if coupled with long-lasting materials/devices for alphavoltaics. Metal halide perovskites (MHPs) are a rising star in the next generation of photovoltaic materials with lab-reported power conversion efficiencies rivaling that of incumbent silicon technology after just over ten years of research. Furthermore, MHPs hold the potential for making high-performance, low-cost devices through solution-processing of Earth-abundant materials in polycrystalline phases compatible with in-line methods such as roll-to-roll processing. The bandgap is highly tunable based on replacing constituents of the ABX3 lattice structure, most notably through replacing the X-site with Br (or Cl) in place of I to increase the band gap over a range of nearly 2 eV.
Although MHPs have been extensively studied in photovoltaic applications, they also have showed significant promise in radiation-based gamma detectors and space environments due to the inherent radiation hardness of the large atomic number constituents. MHPs have also been developed in fully inorganic phases using CsPbI3 and CsPbBr3 phases that exhibit superior thermal stability compared to the hybrid organic-inorganic counterparts. The Cs, Pb, and I/Br components are expected to be more stable under alpha (and other forms of) radiation compared to many of the alternative materials that have been used in direct alphavoltaic converters (DACs) to date.
This project will involve solution-based processing of inorganic metal halide perovskites and measurement of structural, ionic, and mechanical changes along with interactions of radiation and operational conditions with associated structural and mechanical robustness of charge transport layers/electrodes and interfaces for DAC applications.
Faculty Name: Siddharth Karkare
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Characterization of Novel Photoelectron Emitters in High Electric Fields
Research/Project Short Description: Brightness of electron beams generated from photoemitters limits the performance of most linear accelerator applications, ranging from small meter-scale electron microscopes to large km-long particle colliders and x-ray free electron lasers. In this project, you will work on a unique DC electron gun with a cryogenically cooled cathode to test the performance on novel, nanostructured photo emissive materials under extreme electric fields to generate record high brightness electron beams for various applications. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.
Faculty Name: Siddharth Karkare
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Characterization of Novel Photoelectron Emitters in High Electric Fields
Research/Project Short Description: Brightness of electron beams generated from photoemitters limits the performance of most linear accelerator applications, ranging from small meter-scale electron microscopes to large km-long particle colliders and x-ray free electron lasers. In this project, you will work on a unique DC electron gun with a cryogenically cooled cathode to test the performance on novel, nanostructured photo emissive materials under extreme electric fields to generate record high brightness electron beams for various applications. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.
Faculty Name: Siddharth Karkare
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Development of Ultrafast Electron Microscopy
Research/Project Short Description: In this project you will develop the ability to perform Ultrafast Electron Diffraction - a novel technique used to study femtosecond scale structural dynamics of atomic lattices and molecules - using the ASU DC cryogenic electron gun. You will also design and develop novel electron guns for advanced electron microscopes which will allow performing ultrafast electron microscopy with unprecedented spatial and energy resolution. The project involve working with and designing high-voltage-high-field electron guns and cryogenic cooling systems under ultra-high-vacuum conditions. Such guns are not only useful to generate electron beams for ultrafast science, but will also ower the next generation particle colliders and x-ray free electron lasers. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.
Faculty Name: Siddharth Karkare
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Development of Ultrafast Electron Microscopy
Research/Project Short Description: In this project you will develop the ability to perform Ultrafast Electron Diffraction - a novel technique used to study femtosecond scale structural dynamics of atomic lattices and molecules - using the ASU DC cryogenic electron gun. You will also design and develop novel electron guns for advanced electron microscopes which will allow performing ultrafast electron microscopy with unprecedented spatial and energy resolution. The project involve working with and designing high-voltage-high-field electron guns and cryogenic cooling systems under ultra-high-vacuum conditions. Such guns are not only useful to generate electron beams for ultrafast science, but will also ower the next generation particle colliders and x-ray free electron lasers. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.
Faculty Name: Robert Nemanich
Experimental
Research Area: Nanoscience and Materials Physics
Research Title: Interfaces of Semiconducting Diamond and Dielectric Layers for High Power Transistors
Research/Project Short Description: Diamond semiconducting devices are now projected to be crucial for the future electricity grid, which will accommodate new power sources to support the growth of AI cloud services. High voltage electronics based on diamond, are expected to be central to achieving this goal. This research rotation project will employ photoemission spectroscopy to measure interface properties of oxide layers deposited on doped diamond. The interface will be optimized to support a highly conducting channel that originates from the interface bonding structure. The results will be important for design and fabrication of a new generation of power transistors.
Faculty Name: Rizal Hariadi
Experimental
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Molecular tweezers for multi-axial force control at the single molecule level
Research/Project Short Description: Multi-axial force application at the single-molecule level has remained technically challenging, as current force spectroscopy techniques cannot replicate the complex multi-directional tension environments that integrins experience in complex cells. This project addresses these limitations through the design and fabrication of Multi-Axial Entropic Spring Tweezers along Rigid Origami (MAESTRO) devices, which are programmable DNA origami-based molecular tools capable of applying controlled piconewton-scale forces to individual integrin molecules in multiple directions simultaneously. The research will test the hypothesis that multi-axial tensions critically regulate integrin structure, conformation, and dynamics Students will engage in hands-on research that connects fundamental physics concepts including entropic elasticity and force-extension behavior of DNA polymers to cutting-edge biophysical applications, gaining experience with single-molecule techniques such as fluorescence resonance energy transfer (FRET), fluorescence correlation spectroscopy (FCS), and cryo-electron microscopy (cryo-EM), alongside DNA nanotechnology and quantitative data analysis methodologies. Research activities will include calibrating DNA hairpin force sensors on origami platforms, preparing samples for fluorescence experiments, and analyzing force-dependent conformational changes in integrin activation states to test the hypothesis that tensions critically regulate integrin-ligand binding kinetics and catch-bond behavior, providing students with a strong foundation in single-molecule biophysics, cryo-electron microscopy, and coarse-grained modeling within a well-equipped and collaborative laboratory environment. This project is supported by a $1.1M NSF CAREER award.
Faculty Name: Rizal Hariadi
Experimental
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Molecular tweezers for multi-axial force control at the single molecule level
Research/Project Short Description: Multi-axial force application at the single-molecule level has remained technically challenging, as current force spectroscopy techniques cannot replicate the complex multi-directional tension environments that integrins experience in complex cells. This project addresses these limitations through the design and fabrication of Multi-Axial Entropic Spring Tweezers along Rigid Origami (MAESTRO) devices, which are programmable DNA origami-based molecular tools capable of applying controlled piconewton-scale forces to individual integrin molecules in multiple directions simultaneously. The research will test the hypothesis that multi-axial tensions critically regulate integrin structure, conformation, and dynamics Students will engage in hands-on research that connects fundamental physics concepts including entropic elasticity and force-extension behavior of DNA polymers to cutting-edge biophysical applications, gaining experience with single-molecule techniques such as fluorescence resonance energy transfer (FRET), fluorescence correlation spectroscopy (FCS), and cryo-electron microscopy (cryo-EM), alongside DNA nanotechnology and quantitative data analysis methodologies. Research activities will include calibrating DNA hairpin force sensors on origami platforms, preparing samples for fluorescence experiments, and analyzing force-dependent conformational changes in integrin activation states to test the hypothesis that tensions critically regulate integrin-ligand binding kinetics and catch-bond behavior, providing students with a strong foundation in single-molecule biophysics, cryo-electron microscopy, and coarse-grained modeling within a well-equipped and collaborative laboratory environment. This project is supported by a $1.1M NSF CAREER award.
Faculty Name: Steve Pressé
Experimental
Research Area: Biological and Soft Matter Physics
Research Title: From bacterial hydrodynamics to bacterial predator-prey dynamics
Research/Project Short Description: We have previously shown that the bacterial predator, Bdellovibrio bacteriovorus, hunt their prey, E. coli, by leveraging passive hydrodynamic forces rather than actively seeking out their prey through, say, chemical signaling. In particular, hydrodynamic forces can become manifest when predators move near surfaces forcing them to co-localize with prey. Here we propose to take this idea a step further and investigate the predator's hunting efficiency when it is part of a population of predator and prey within the microbiome of a living organism (in this case, the worm c. elegans). In living organisms, questions as to how predators hunt abound. For example we hope to address these questions: 1) how do we go about quantifying the kinetics of predation when predation occurs within the gut of an organism?; 2) how does the effect of physical confinement within the gut of c. elegans impact the predator's predation efficiency?; 3) what kind of (non-equilibrium statistical mechanical) theories are required in order to describe predation dynamics from individual gut colonization events, to saturation involving tens of thousands of bacteria, while describing fluctuations in levels of predator and prey within a living organism's gut?; 4) can we ever use this knowledge to engineer the predator as a living antibiotic?
Faculty Name: Steve Pressé
Theoretical
Research Area: Biological and Soft Matter Physics, Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Statistical mechanics meets AI/ML
Research/Project Short Description: We live in an age where data abound from biological physics to astronomy and there is an explosion of new tools (AI/ML) inspiring us to think quantitatively about these data. Yet these tools, often inspired by developments in Mathematics and CS, can be black boxes and not suitable for applications within the Natural Sciences. Our goal is to advance computational tool, appropriate for the Natural Sciences, critical in gathering insights on life's processes observed through advanced microscopy techniques or astronomical events observed using modern telescopes. In particular, we leverage tools from AI and machine learning, many grounded in computational statistics, to glean insights about our physical universe otherwise unavailable using traditional analysis techniques. For example, of particular interest, is resolving with higher resolution objects further away from our planet from very limited photon budgets or unraveling the collective dynamics of molecular machines (i.e., transcription factors) operating cohesively at gene loci to read DNA's instructions. Unraveling these dynamics is especially complex as most events of interest occur on length scales far smaller than the light we use to observe them. Thus from a smattering of photons of wavelength hundreds of times larger than the objects we care to characterize in biological systems, must be derived insight on life's fundamental processes. Students working on this project will quickly become experts in state-of-the-art tools of AI, simulation-based inference, Bayesian inference, and machine learning more broadly.
Faculty Name: Steve Pressé
Theoretical
Research Area: Biological and Soft Matter Physics, Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Statistical mechanics meets AI/ML
Research/Project Short Description: We live in an age where data abound from biological physics to astronomy and there is an explosion of new tools (AI/ML) inspiring us to think quantitatively about these data. Yet these tools, often inspired by developments in Mathematics and CS, can be black boxes and not suitable for applications within the Natural Sciences. Our goal is to advance computational tool, appropriate for the Natural Sciences, critical in gathering insights on life's processes observed through advanced microscopy techniques or astronomical events observed using modern telescopes. In particular, we leverage tools from AI and machine learning, many grounded in computational statistics, to glean insights about our physical universe otherwise unavailable using traditional analysis techniques. For example, of particular interest, is resolving with higher resolution objects further away from our planet from very limited photon budgets or unraveling the collective dynamics of molecular machines (i.e., transcription factors) operating cohesively at gene loci to read DNA's instructions. Unraveling these dynamics is especially complex as most events of interest occur on length scales far smaller than the light we use to observe them. Thus from a smattering of photons of wavelength hundreds of times larger than the objects we care to characterize in biological systems, must be derived insight on life's fundamental processes. Students working on this project will quickly become experts in state-of-the-art tools of AI, simulation-based inference, Bayesian inference, and machine learning more broadly.
Faculty Name: Steve Pressé
Theoretical
Research Area: Biological and Soft Matter Physics, Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Statistical mechanics meets AI/ML
Research/Project Short Description: We live in an age where data abound from biological physics to astronomy and there is an explosion of new tools (AI/ML) inspiring us to think quantitatively about these data. Yet these tools, often inspired by developments in Mathematics and CS, can be black boxes and not suitable for applications within the Natural Sciences. Our goal is to advance computational tool, appropriate for the Natural Sciences, critical in gathering insights on life's processes observed through advanced microscopy techniques or astronomical events observed using modern telescopes. In particular, we leverage tools from AI and machine learning, many grounded in computational statistics, to glean insights about our physical universe otherwise unavailable using traditional analysis techniques. For example, of particular interest, is resolving with higher resolution objects further away from our planet from very limited photon budgets or unraveling the collective dynamics of molecular machines (i.e., transcription factors) operating cohesively at gene loci to read DNA's instructions. Unraveling these dynamics is especially complex as most events of interest occur on length scales far smaller than the light we use to observe them. Thus from a smattering of photons of wavelength hundreds of times larger than the objects we care to characterize in biological systems, must be derived insight on life's fundamental processes. Students working on this project will quickly become experts in state-of-the-art tools of AI, simulation-based inference, Bayesian inference, and machine learning more broadly.
Faculty Name: Alexander van Engelen
Theoretical
Research Area: Cosmology, Particle, and Astrophysics
Research Title: New Directions with the Cosmic Microwave Background
Research/Project Short Description: This project will involve research into extracting maximal information from surveys of the mm-wave sky, focussed on the cosmic microwave background and the information it holds on the evolution of cosmic structures. One direction could be to extract CMB gravitational lensing information on small scales. Another would be to investigate the imprint that ionized gas has on the distribution of the CMB. Projects could be purely theoretical in nature, or could involve a data analysis component.
Faculty Name: Rizal Hariadi
Experimental
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Catalytronix: Electromagnetic control of molecular dynamics
Research/Project Short Description: Our lab is seeking a student to contribute to a DARPA project that uses physical forces and programmable nanostructures that apply electromagnetic and thermodynamic principles to control chemical reactions. Research activities begin with learning to design and characterize DNA nanostructures using techniques such as atomic force microscopy and fluorescence imaging, providing hands-on experience that directly applies fundamental physics principles. Daily research activities include designing molecular systems computationally, preparing samples in laboratory settings, conducting measurements with sophisticated instrumentation, and analyzing data to understand how electromagnetic fields control molecular behavior. Students will build upon coursework in electromagnetism and thermodynamics to investigate how chemical reactions can be manipulated using the same physics principles that govern electronic circuits and thermodynamic systems. Beginning researchers receive close mentorship from Dr. Hariadi, who brings extensive experience in DNA nanotechnology, along with guidance from graduate students who provide training in laboratory safety protocols through advanced measurement techniques. Students will develop highly valued skills, including DNA origami placement, nanoscale measurement techniques, quantitative data analysis, scientific programming, and understanding of physics at the molecular level, preparing them for careers in academic research and industries.
Faculty Name: Rizal Hariadi
Experimental
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Catalytronix: Electromagnetic control of molecular dynamics
Research/Project Short Description: Our lab is seeking a student to contribute to a DARPA project that uses physical forces and programmable nanostructures that apply electromagnetic and thermodynamic principles to control chemical reactions. Research activities begin with learning to design and characterize DNA nanostructures using techniques such as atomic force microscopy and fluorescence imaging, providing hands-on experience that directly applies fundamental physics principles. Daily research activities include designing molecular systems computationally, preparing samples in laboratory settings, conducting measurements with sophisticated instrumentation, and analyzing data to understand how electromagnetic fields control molecular behavior. Students will build upon coursework in electromagnetism and thermodynamics to investigate how chemical reactions can be manipulated using the same physics principles that govern electronic circuits and thermodynamic systems. Beginning researchers receive close mentorship from Dr. Hariadi, who brings extensive experience in DNA nanotechnology, along with guidance from graduate students who provide training in laboratory safety protocols through advanced measurement techniques. Students will develop highly valued skills, including DNA origami placement, nanoscale measurement techniques, quantitative data analysis, scientific programming, and understanding of physics at the molecular level, preparing them for careers in academic research and industries.
Faculty Name: Nicholas Matlis
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Lasers, electrons and X-rays at CXFEL
Research/Project Short Description: ASU hosts a ground-breaking project to build a Compact X-ray Free Electron Laser (CXFEL) whose objective is to make very short, extremely bright pulses of X-rays that allow us to peer inside matter (be it nature’s molecules or materials enabling the next generation of technology) and see its structure and dynamics at work. Two complementary machines are being built. The first is already producing first X-rays and the second is under construction. Join the team and be part of history. Projects range from developing new accelerator technologies to inventing novel ultrafast diagnostics to running experiments with lasers, electrons and X-rays. We are always looking for good people. Come by and see what fits you.
Faculty Name: Nicholas Matlis
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Lasers, electrons and X-rays at CXFEL
Research/Project Short Description: ASU hosts a ground-breaking project to build a Compact X-ray Free Electron Laser (CXFEL) whose objective is to make very short, extremely bright pulses of X-rays that allow us to peer inside matter (be it nature’s molecules or materials enabling the next generation of technology) and see its structure and dynamics at work. Two complementary machines are being built. The first is already producing first X-rays and the second is under construction. Join the team and be part of history. Projects range from developing new accelerator technologies to inventing novel ultrafast diagnostics to running experiments with lasers, electrons and X-rays. We are always looking for good people. Come by and see what fits you.
Faculty Name: Nicholas Matlis
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Extreme Beams for Future Technologies
Research/Project Short Description: High energy, high average-power laser systems are a versatile tool for generating exotic beams of photons and particles for exploring quantum dynamics in matter, from molecules important for life to novel materials enabling the next breakthrough in computing technologies. This research encompasses a combination of projects spanning laser development; creation of novel high-energy, highly tunable sources of terahertz-frequency electromagnetic pulses (THz pulses) using nonlinear optics; development of novel, THz-based electron acceleration and manipulation technologies, and studying the responses of matter driven into extreme regimes previously inaccessible without these specialized tools. You will get hands-on experience using and tuning laser systems, building data acquisition and control systems, transforming intense light into various other types of beams and designing and running experiments exploiting the matching of THz photon energies with key excitations in quantum materials, including spin, orbital, and lattice degrees of freedom to control material properties. Both theory and experimental projects are available.
Faculty Name: Nicholas Matlis
Experimental
Research Area: Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics
Research Title: Extreme Beams for Future Technologies
Research/Project Short Description: High energy, high average-power laser systems are a versatile tool for generating exotic beams of photons and particles for exploring quantum dynamics in matter, from molecules important for life to novel materials enabling the next breakthrough in computing technologies. This research encompasses a combination of projects spanning laser development; creation of novel high-energy, highly tunable sources of terahertz-frequency electromagnetic pulses (THz pulses) using nonlinear optics; development of novel, THz-based electron acceleration and manipulation technologies, and studying the responses of matter driven into extreme regimes previously inaccessible without these specialized tools. You will get hands-on experience using and tuning laser systems, building data acquisition and control systems, transforming intense light into various other types of beams and designing and running experiments exploiting the matching of THz photon energies with key excitations in quantum materials, including spin, orbital, and lattice degrees of freedom to control material properties. Both theory and experimental projects are available.
Faculty Name: Chao Wang
Theoretical
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Nanoscale physical analysis and modeling of gold nanoparticle distribution towards ultrasensitive protein detection
Research/Project Short Description: Precise detection of low-abundance proteins is crucial to early detection of a wide range of infectious and chronic diseases. Currently, this is only possible through most advanced, yet expensive and complex instrument, which are not available in resource-limited settings. To date, rapid, sensitive, and cost-effective detection on a point-of-care platform remains elusive. In this project, we aim to establish a gold nanoparticle (AuNP)-supported, rapid electronic detection (NasRED) platform with digital readout to achieve sub-femtomolar sensitivity and high specificity. Here, surface-functionalized AuNPs act as multivalent detectors to recognize target proteins (e.g. antigens, antibodies and toxins), subsequently forming aggregates precipitated in a microcentrifuge tube and producing a solution color change. Uniquely, NasRED introduces active fluidic forces through engineered centrifugation and vortex agitation, effectively promoting low-concentration protein detection and accelerating signal transduction and readout within 15 to 30 minutes. In this project, the students will work with Ph.D. students in my lab and establish physical models and simulations (for example in COMSOL or other software) to understand the complex fluidic physics/mechanics of the AuNP sedimentation and resuspension process. These studies will play an important role in future biosensor system engineering for point-of-care diagnostics of broad diseases.
Faculty Name: Chao Wang
Theoretical
Research Area: Biological and Soft Matter Physics, Nanoscience and Materials Physics
Research Title: Nanoscale physical analysis and modeling of gold nanoparticle distribution towards ultrasensitive protein detection
Research/Project Short Description: Precise detection of low-abundance proteins is crucial to early detection of a wide range of infectious and chronic diseases. Currently, this is only possible through most advanced, yet expensive and complex instrument, which are not available in resource-limited settings. To date, rapid, sensitive, and cost-effective detection on a point-of-care platform remains elusive. In this project, we aim to establish a gold nanoparticle (AuNP)-supported, rapid electronic detection (NasRED) platform with digital readout to achieve sub-femtomolar sensitivity and high specificity. Here, surface-functionalized AuNPs act as multivalent detectors to recognize target proteins (e.g. antigens, antibodies and toxins), subsequently forming aggregates precipitated in a microcentrifuge tube and producing a solution color change. Uniquely, NasRED introduces active fluidic forces through engineered centrifugation and vortex agitation, effectively promoting low-concentration protein detection and accelerating signal transduction and readout within 15 to 30 minutes. In this project, the students will work with Ph.D. students in my lab and establish physical models and simulations (for example in COMSOL or other software) to understand the complex fluidic physics/mechanics of the AuNP sedimentation and resuspension process. These studies will play an important role in future biosensor system engineering for point-of-care diagnostics of broad diseases.
Faculty Name: Banu Ozkan
Theoretical
Research Area: Biological and Soft Matter Physics
Research Title: Building Physics-Integrated AI models to enhance learning in case of limited data
Research/Project Short Description: Proteins are the molecular workhorses of life, carrying out structural, catalytic, signaling, and regulatory roles across all living systems. Their universality and tunable properties make them powerful tools in medicine, biotechnology, and synthetic biology. However, our knowledge of protein function remains remarkably incomplete—current annotations cover only 1–10% of the known protein universe, with less than 1% of those functions experimentally verified. Most predictions rely on sequence or structural homology, yet many proteins share functional similarities without detectable sequence or structural resemblance.
An emerging paradigm emphasizes protein dynamics—the patterns of motion within their conformational landscape—as a universal determinant of function. Protein motions are shaped by evolutionary pressures and correlate strongly with functional outcomes, capturing both intrinsic properties and environmental context. Recent work has introduced the concept of “MD fingerprints”: dynamic signatures derived from molecular dynamics simulations that encode how proteins explore their energy landscape. These signatures offer the potential to generalize function predictions across unrelated sequences, overcoming the limitations of purely sequence- or structure-based approaches.
The major challenge lies in computational cost. All-atom molecular dynamics (MD) simulations are too expensive to apply to millions of proteins, with full coverage requiring thousands of GPU-years. Coarse-grained molecular dynamics (CG-MD) simulations offer a practical alternative, capturing essential motions at much lower computational expense. Combining these efficient sampling methods with advanced machine learning architectures such as graph neural networks (GNNs) provides an opportunity to learn dynamic–function relationships at scale.
A proof-of-concept pipeline for integrating CG-MD dynamics with GNN-based function prediction, laying the groundwork for scalable annotation of uncharacterized proteins.