Ran Zhang
Postdoctoral Researcher
Max Planck Institute of Microstructure Physics
Exploring the frontiers of spintronics and probabilistic computing
About
Ph.D. in Physics with a strong background in spintronics and nanoscale device research, specializing in magnetic tunnel junctions, skyrmion-based systems, and spin-orbit torque phenomena. Extensive hands-on experience in device fabrication, electrical characterization, and automated test system development. Proven track record in investigating fundamental spintronic mechanisms and translating them into concepts for novel memory and computing devices.
Education
Ph.D. in Condensed Matter Physics
University of Chinese Academy of Sciences & Fraunhofer-Gesellschaft
Thesis: Magnetic Tunnel Junctions and Their Applications in Probabilistic Computing
B.Sc. in Physics
Shandong University
Experience
Postdoctoral Researcher
Max Planck Institute of Microstructure Physics, Halle
Visiting Scholar
Technische Universität Braunschweig
Visiting PhD Researcher
Fraunhofer IPMS-CNT, Dresden
Research Assistant
Institute of Physics, Chinese Academy of Sciences
Skills
Programming
Web Development
Hardware & Test Engineering
Lab Techniques
Simulation & CAD
Awards
- 2023 Graduation with Distinction — Northern Arizona University
- 2023 IOP Director's Scholarship Award — CAS
- 2022 IOP Director's Scholarship Award — CAS
- 2018 National Endeavor Scholarship — Shandong University
- 2017 Physics Talent Scholarship — Shandong University
Research
Spintronic Devices and Architectures for Emerging Computational Paradigms
My research sits at the intersection of condensed matter physics and applied computing, exploring how nanoscale spintronic phenomena can be engineered into practical hardware for probabilistic reasoning, reconfigurable logic, and brain-inspired architectures.
Skyrmion-Based Unconventional Logic
Skyrmions offer rich dynamics, non-trivial topology, and stability at nanoscale dimensions. I investigate how controlled nucleation, motion, and annihilation of skyrmions can be harnessed for reconfigurable logic elements and energy-efficient information processing.
- Topological spin textures
- Reconfigurable logic
- Energy-efficient computing
MTJ-Based Probabilistic Computing
Magnetic tunnel junctions with tunable switching probabilities provide a natural hardware platform for probabilistic algorithms, neural sampling, and Bayesian inference. I design and test novel MTJ circuits capable of generating configurable probability distributions for machine learning and optimization tasks.
- True random number generation
- Bayesian inference hardware
- Combinatorial optimization
Hybrid Spintronic Architectures
By combining MTJs, skyrmion tracks, and other emergent quantum materials, I propose and evaluate architectures for beyond-von Neumann computing, including probabilistic neural networks and spintronic accelerators for data-intensive tasks.
- Beyond von Neumann computing
- Neuromorphic systems
- Hardware-software co-design
Publications
17 publications including 5 first-author papers in Nature Communications, Physical Review Applied, and Advanced Science
Showing 17 of 17 publications
Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions
Li, X., Xu, Y., Wan, C., Zhang, R., Hindenberg, M., Hoffmann, R., Liu, S., Zhang, T., Xiong, S., Kong, D., Xia, J., Gao, F., Nie, Z., Kämpfe, T., Yu, G., Han, X.
Advanced Intelligent Systems, e202500961 (2026)
Probabilistic greedy algorithm solver using magnetic tunneling junctions for traveling salesman problem
Zhang, R., Li, X., Wan, C., Hoffmann, R., Hindenberg, M., Xu, Y., Liu, S., Kong, D., Xiong, S., He, S., Vardar, A., Dai, Q., Gong, J., Sun, Y., Zheng, Z., Kämpfe, T., Yu, G., Han, X.
Nature Communications (2025)
Reconfigurable Boolean logic gates with a single spin-orbit-torque magnetic tunnel junction
Zhang, R., Wan, C., Zhao, M., Li, X., Xu, Y., Liu, S., Kong, D., Xiong, S., Yu, G., Han, X.
Physical Review Applied 24(3), 034079 (2025)
Drift-resilient magnetic-tunnel-junction random-number generator via hybrid control strategies
Zhang, R., Wan, C., Xu, Y., Li, X., Hoffmann, R., Hindenberg, M., Liu, S., Kong, D., Xiong, S., He, S., Vardar, A., Dai, Q., Gong, J., Sun, Y., Zheng, Z., Kämpfe, T., Yu, G., Han, X.
Physical Review Applied 23(5), 054073 (2025)
The analysis of spin current source in current-induced switching of the magnetization in T-type magnetic structures
Liu, S., Wan, C., Xia, J., Zhang, R., Li, J., Li, X., Gao, F., Xu, Y., Davydenko, A. V., Stebliy, M. E., Ognev, A. V., Samardak, A. S., Yu, G., Han, X.
Applied Physics Letters 127(6), 062405 (2025)
Integrating P-Bits in MTJs: A Bridge to Efficient Stochastic Computing
Laleni, N., Ranjbar, S., Zhang, R., Tsiougkos, A., Yadav, N., Pavlidis, V., Kämpfe, T.
2025 14th International Conference on Modern Circuits and Systems Technologies (MOCAST), 1--4 (2025)
Bayesian Reasoning Enabled by Spin-Orbit Torque Magnetic Tunnel Junctions
Xu, Y., Li, X., Wan, C., Zhang, R., He, B., Liu, S., Xia, J., Kong, D., Xiong, S., Yu, G., Han, X.
arXiv (2025)
Restricted Boltzmann Machines Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions
Li, X., Wan, C., Zhang, R., Zhao, M., Xiong, S., Kong, D., Luo, X., He, B., Liu, S., Xia, J., Yu, G., Han, X.
Nano Letters 24(18), 5420--5428 (2024)
Probability‐Distribution‐Configurable True Random Number Generators Based on Spin‐Orbit Torque Magnetic Tunnel Junctions
Zhang, R., Li, X., Zhao, M., Wan, C., Luo, X., Liu, S., Zhang, Y., Wang, Y., Yu, G., Han, X.
Advanced Science 11(23), 2402182 (2024)
Electrical switching of the perpendicular Néel order in a collinear antiferromagnet
He, W., Zhang, T., Zhou, Y., Wan, C., Wu, H., Cui, B., Xia, J., Zhang, R., Guo, T., Chen, P., Zhao, M., Jiang, L., Grutter, A., Balakrishnan, P. P., Caruana, A. J., Kinane, C. J., Langridge, S., Yu, G., Song, C., Han, X.
Nature Electronics 7(11), 975--983 (2024)
Self-stabilized true random number generator based on spin–orbit torque magnetic tunnel junctions without calibration
Xu, Y. Q., Li, X. H., Zhang, R., Wan, C. H., Wang, Y. Z., Liu, S. Q., Luo, X. M., Lan, G. B., Xia, J. H., Yu, G. Q., Han, X. F.
Applied Physics Letters 125(13), 132403 (2024)
Magnetization switching driven by spin current in a T-type ferromagnetic trilayer
Liu, S., Wan, C., Feng, J., Luo, X., Zhang, R., Namsaraev, Z. Z., Li, X., Gao, F., Stebliy, M. E., Ognev, A. V., Yu, G., Samardak, A. S., Han, X.
Applied Physics Letters 124(19), 192403 (2024)
Experimental evidence of the oscillation behavior of the interlayer DMI effect
Gao, F. S., Liu, S. Q., Zhang, R., Xia, J. H., He, W. Q., Li, X. H., Luo, X. M., Wan, C. H., Yu, G. Q., Su, G., Han, X. F.
Applied Physics Letters 123(19), 192401 (2023)
All-Electrical 9-Bit Skyrmion-Based Racetrack Memory Designed with Laser Irradiation
He, B., Tomasello, R., Luo, X., Zhang, R., Nie, Z., Carpentieri, M., Han, X., Finocchio, G., Yu, G.
Nano Letters 23(20), 9482--9490 (2023)
True random number generator based on spin–orbit torque magnetic tunnel junctions
Li, X. H., Zhao, M. K., Zhang, R., Wan, C. H., Wang, Y. Z., Luo, X. M., Liu, S. Q., Xia, J. H., Yu, G. Q., Han, X. F.
Applied Physics Letters 123(14), 142403 (2023)
Stochastic p-Bits Based on Spin-Orbit Torque Magnetic Tunnel Junctions
Li, X. H., Zhao, M. K., Zhang, R., Wan, C. H., Wang, Y. Z., Luo, X. M., Liu, S. Q., Xia, J. H., Yu, G. Q., Han, X. F.
arXiv (2023)
Type-Y magnetic tunnel junctions with CoFeB doped tungsten as spin current source
Zhao, M. K., Zhang, R., Wan, C. H., Luo, X. M., Zhang, Y., He, W. Q., Wang, Y. Z., Yang, W. L., Yu, G. Q., Han, X. F.
Applied Physics Letters 120(18), 182405 (2022)
Projects
Academic tools and web applications I'm building
Random Number Testing Suite
A web-based tool for statistical testing and validation of random number generators, implementing NIST SP800-22 test suite directly in the browser.
In-Browser Micromagnetics Simulator
Interactive micromagnetic simulation running entirely in the browser, enabling visualization of magnetic domain structures, skyrmion dynamics, and spin-orbit torque switching.
MTJ Device Characterization Dashboard
Automated data analysis and visualization platform for magnetic tunnel junction electrical characterization, supporting parametric sweeps and statistical analysis.
Get in Touch
Feel free to reach out for collaborations, discussions, or questions about my research.
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