Kiran Mak

All Publications

• Three-dimensional nanophotonics with spatially modulated optical properties. Light, science & applications Salamin, Y., Yang, G., Mills, B., Grossi Fonseca, A., Roques-Carmes, C., Yang, Q., Beroz, J., Kooi, S. E., de Miguel Comella, M., Mak, K., Vaidya, S., Oran, D., Swain, C., Sun, Y., Maayani, S., Sloan, J., Amin Elfadil Elawad, A., Lopez, J. J., Boyden, E. S., Soljačić, M. 2026; 15 (1)

  Abstract

  Nanophotonics has revolutionized the control of light-matter interactions in various fields of fundamental science and technology. In this work, we propose Implosion Fabrication (ImpFab) as a versatile nanophotonics fabrication platform providing the highest spatial resolution, material versatility, and full volumetric control. ImpFab uniquely combines top-down lithography with bottom-up nanoparticle assembly within a hydrogel scaffold, enabling precise control over optical material properties, such as refractive index, by adjusting printing parameters. We showcase the potential of ImpFab by fabricating three-dimensional photonic crystals and quasicrystals, as well as demonstrating optical structures with spatially modulated unit cell material properties. Our results highlight the potential of ImpFab in producing nanostructures with tailored optical functionalities, which are crucial for applications in sensing, imaging, and information processing, and opening new avenues in developing non-Hermitian photonic systems with spatially controlled gain and loss.

  View details for DOI 10.1038/s41377-025-02166-5

  View details for PubMedID 41775693

  View details for PubMedCentralID PMC12957445

• Structural constraint integration in a generative model for the discovery of quantum materials. Nature materials Okabe, R., Cheng, M., Chotrattanapituk, A., Mandal, M., Mak, K., Córdova Carrizales, D., Hung, N. T., Fu, X., Han, B., Wang, Y., Xie, W., Cava, R. J., Jaakkola, T. S., Cheng, Y., Li, M. 2026; 25 (2): 223-230

  Abstract

  Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd0.22Bi0.88 and Ti0.5Pd1.5Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

  View details for DOI 10.1038/s41563-025-02355-y

  View details for PubMedID 40983616

  View details for PubMedCentralID 7417556