Free-form optimization of nanophotonic devices: from classical methods to deep learning

Nanophotonic devices have enabled microscopic control of light with an unprecedented spatial resolution by employing subwavelength optical elements that can strongly interact with incident waves. However, to date, most nanophotonic devices have been designed based on fixed-shape optical elements, and a large portion of their design potential has remained unexplored. It is only recently that free-form design schemes have been spotlighted in nanophotonics, offering routes to make a break from conventional design constraints and utilize the full design potential. In this review, we systematically overview the nascent yet rapidly growing field of free-form nanophotonic device design. We attempt to define the term “free-form” in the context of photonic device design, and survey different strategies for free-form optimization of nanophotonic devices spanning from classical methods, adjoint-based methods, to contemporary machine-learning-based approaches.

Experimental device design justification for radiation resistance tests of single-mode optical fibers and FBG-based sensors at the IVG.1M reactor

One of the most important stages in the development of an experimental device is to carry out a series of computational studies to substantiate the compliance of device design with the objectives of the experiment, such as the choice of test modes and the study of standard and hypothetical emergency modes of its operation. Result of these studies is the neutron-physical, thermal, strength and hydrodynamic characteristics of the structural elements of the device and working bodies. During this work, a series of neutron calculations was conducted using the MCNP6 code and thermal-physical calculations using the ANSYS software package of two configurations of the experimental device. A feature of the calculated studies is the presence of specific requirements for the thermal state of the experimental device sleeve. Namely, ensuring a predetermined temperature gradient between its ribs, which should not exceed 4°K during the reactor tests.

The Role of Soft Robotic Micromachines in the Future of Medical Devices and Personalized Medicine

Developments in medical device design result in advances in wearable technologies, minimally invasive surgical techniques, and patient-specific approaches to medicine. In this review, we analyze the trajectory of biomedical and engineering approaches to soft robotics for healthcare applications. We review current literature across spatial scales and biocompatibility, focusing on engineering done at the biotic-abiotic interface. From traditional techniques for robot design to advances in tunable material chemistry, we look broadly at the field for opportunities to advance healthcare solutions in the future. We present an extracellular matrix-based robotic actuator and propose how biomaterials and proteins may influence the future of medical device design.

The egg steamer paradox

Why do we need to pour less water in an egg steamer to prepare more eggs to the same degree of ‘doneness’? We discuss the physical processes at work in the electric egg steamer and resolve this seeming paradox. We demonstrate that the main heat transfer mechanism from steam to egg is due to latent heat through condensation. This not only explains the paradox, but also allows us to estimate the amount of water reduction. Comparing the preparation time to the one for traditional boiling, we estimate the eggshell temperature during steaming. We also describe the device design and provide further theoretical estimates and experimental kitchen measurement data for this appealing kitchen experiment that can be easily accomplished at home.