Tie Jun Cui

Bio: Tie Jun Cui is an academic researcher from Southeast University. The author has contributed to research in topics: Metamaterial & Surface plasmon polariton. The author has an hindex of 93, co-authored 922 publications receiving 33515 citations. Previous affiliations of Tie Jun Cui include University of Illinois at Urbana–Champaign & Tianjin University.

Coding metamaterials, digital metamaterials and programmable metamaterials

Abstract: Smart materials offering great freedom in manipulating electromagnetic radiation have been developed. This exciting new concept was realized by Tie Jun Cui and co-workers at the Southeast University, China, who developed digital metamaterials consisting of two kinds of unit cells whose different phase responses allow them to act as ‘0’ and ‘1’ bits. These cells can be judiciously arranged in sequences to enable controlled manipulation of electromagnetic waves. This is one-bit coding; higher-bit coding is possible by employing more kinds of unit cells. The researchers developed a metamaterial cell whose binary response can be controlled by a biased diode. By using a field-programmable gate array, they demonstrated that this digital metamaterial can be programmed. Such metamaterials are attractive for controlling radiation beams in antennas and for realizing other ‘smart’ metamaterials.

Coding Metamaterials, Digital Metamaterials and Programming Metamaterials

Abstract: As artificial structures, metamaterials are usually described by macroscopic effective medium parameters, which are named as "analog metamaterials". Here, we propose "digital metamaterials" in two steps. Firstly, we present "coding metamaterials" that are composed of only two kinds of unit cells with 0 and {\pi} phase responses, which we name as "0" and "1" elements. By coding "0" and "1" elements with controlled sequences (i.e., 1-bit coding), we can manipulate electromagnetic (EM) waves and realize different functionalities. The concept of coding metamaterial can be extended from 1-bit coding to 2-bit or more. In 2-bit coding, four kinds of unit cells with phase responses 0, {\pi}/2, {\pi}, and 3{\pi}/2 are required to mimic "00", "01", "10" and "11" elements, which have larger freedom to control EM waves. Secondly, we propose a unique metamaterial particle which has either "0" or "1" response controlled by a biased diode. Based on the particle, we present "digital metamaterials" with unit cells having either "0" or "1" state. Using the field-programmable gate array, we realize to control the digital metamaterial digitally. By programming different coding sequences, a single digital metamaterial has distinct abilities in manipulating EM waves, realizing the "programming metamaterials". The above concepts and physical phenomena are confirmed by numerical simulations and experiments through metasurfaces.

Broadband Ground-Plane Cloak

Abstract: The possibility of cloaking an object from detection by electromagnetic waves has recently become a topic of considerable interest. The design of a cloak uses transformation optics, in which a conformal coordinate transformation is applied to Maxwell's equations to obtain a spatially distributed set of constitutive parameters that define the cloak. Here, we present an experimental realization of a cloak design that conceals a perturbation on a flat conducting plane, under which an object can be hidden. To match the complex spatial distribution of the required constitutive parameters, we constructed a metamaterial consisting of thousands of elements, the geometry of each element determined by an automated design process. The ground-plane cloak can be realized with the use of nonresonant metamaterial elements, resulting in a structure having a broad operational bandwidth (covering the range of 13 to 16 gigahertz in our experiment) and exhibiting extremely low loss. Our experimental results indicate that this type of cloak should scale well toward optical wavelengths.

Electromagnetic reprogrammable coding-metasurface holograms.

Abstract: Metasurfaces have enabled a plethora of emerging functions within an ultrathin dimension, paving way towards flat and highly integrated photonic devices. Despite the rapid progress in this area, simultaneous realization of reconfigurability, high efficiency, and full control over the phase and amplitude of scattered light is posing a great challenge. Here, we try to tackle this challenge by introducing the concept of a reprogrammable hologram based on 1-bit coding metasurfaces. The state of each unit cell of the coding metasurface can be switched between ‘1’ and ‘0’ by electrically controlling the loaded diodes. Our proof-of-concept experiments show that multiple desired holographic images can be realized in real time with only a single coding metasurface. The proposed reprogrammable hologram may be a key in enabling future intelligent devices with reconfigurable and programmable functionalities that may lead to advances in a variety of applications such as microscopy, display, security, data storage, and information processing. Realizing metasurfaces with reconfigurability, high efficiency, and control over phase and amplitude is a challenge. Here, Li et al. introduce a reprogrammable hologram based on a 1-bit coding metasurface, where the state of each unit cell of the coding metasurface can be switched electrically.

Conformal surface plasmons propagating on ultrathin and flexible films

Abstract: Surface plasmon polaritons (SPPs) are localized surface electromagnetic waves that propagate along the interface between a metal and a dielectric. Owing to their inherent subwavelength confinement, SPPs have a strong potential to become building blocks of a type of photonic circuitry built up on 2D metal surfaces; however, SPPs are difficult to control on curved surfaces conformably and flexibly to produce advanced functional devices. Here we propose the concept of conformal surface plasmons (CSPs), surface plasmon waves that can propagate on ultrathin and flexible films to long distances in a wide broadband range from microwave to mid-infrared frequencies. We present the experimental realization of these CSPs in the microwave regime on paper-like dielectric films with a thickness 600-fold smaller than the operating wavelength. The flexible paper-like films can be bent, folded, and even twisted to mold the flow of CSPs.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming

Abstract: Intelligent reflecting surface (IRS) is a revolutionary and transformative technology for achieving spectrum and energy efficient wireless communication cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each being able to reflect the incident signal independently with an adjustable phase shift so as to collaboratively achieve three-dimensional (3D) passive beamforming without the need of any transmit radio-frequency (RF) chains. In this paper, we study an IRS-aided single-cell wireless system where one IRS is deployed to assist in the communications between a multi-antenna access point (AP) and multiple single-antenna users. We formulate and solve new problems to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users’ individual signal-to-interference-plus-noise ratio (SINR) constraints. Moreover, we analyze the asymptotic performance of IRS’s passive beamforming with infinitely large number of reflecting elements and compare it to that of the traditional active beamforming/relaying. Simulation results demonstrate that an IRS-aided MIMO system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains. We also draw useful insights into optimally deploying IRS in future wireless systems.