Hongrui Jiang

Bio: Hongrui Jiang is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Microlens & Lens (optics). The author has an hindex of 32, co-authored 195 publications receiving 4485 citations. Previous affiliations of Hongrui Jiang include Cornell University & Wisconsin Alumni Research Foundation.

Adaptive liquid microlenses activated by stimuli-responsive hydrogels

Abstract: The trend towards miniaturization in optical imaging, diagnostics and lab-on-a-chip technology is creating a demand for sophisticated microlenses. A new type of smart liquid microlens has been developed that differs from most current devices in that it is self-focusing. The key component is a stimuli-responsive hydrogel integrated into a microfluidic system and acting as a container for a liquid droplet. The hydrogel simultaneously senses stimuli and actuates a change in droplet shape — and hence focal length. Stimuli can include biological and chemical agents and physical parameters. At this micrometre scale, pinned liquid-liquid interfaces are used to attain stable devices, and response times of ten to a few tens of seconds. Lenses can have virtually any focal length and are readily integrated into arrays. Despite its compactness, the human eye can easily focus on different distances by adjusting the shape of its lens with the help of ciliary muscles1. In contrast, traditional man-made optical systems achieve focusing by physical displacement of the lenses used. But in recent years, advances in miniaturization technology have led to optical systems that no longer require complicated mechanical systems to tune and adjust optical performance. These systems have found wide use in photonics, displays and biomedical systems. They are either based on arrays of microlenses with fixed focal lengths2,3,4,5, or use external control to adjust the microlens focal length6,7,8,9,10,11,12. An intriguing example is the tunable liquid lens, where electrowetting or external pressure manipulates the shape of a liquid droplet and thereby adjusts its optical properties. Here we demonstrate a liquid lens system that allows for autonomous focusing. The central component is a stimuli-responsive hydrogel13 integrated into a microfluidic system and serving as the container for a liquid droplet, with the hydrogel simultaneously sensing the presence of stimuli and actuating adjustments to the shape—and hence focal length—of the droplet. By working at the micrometre scale where ionic diffusion and surface tension scale favourably14, we can use pinned liquid–liquid interfaces to obtain stable devices and realize response times of ten to a few tens of seconds. The microlenses, which can have a focal length ranging from -∞ to +∞ (divergent and convergent), are also readily integrated into arrays that may find use in applications such as sensing, medical diagnostics and lab-on-a-chip technologies15,16,17,18,19.

An infrared-light responsive graphene-oxide incorporated poly(N-isopropylacrylamide) hydrogel nanocomposite

Abstract: We demonstrate a new light-responsive poly(N-isopropylacrylamide) (PNIPAAm) hydrogel nanocomposite incorporating glycidyl methacrylate functionalized graphene oxide (GO–GMA) instead of metallic nanoparticle fillers. GO–GMA is synthesized by esterification with glycidyl methacrylate. GO–GMA incorporated hydrogels are synthesized by photopolymerization of NIPAAm including 4-dimethylaminopyridine (DMAP) and N,N′-methylenebisacrylamide (NMBA) in GO–GMA dispersed dimethyl sulfoxide (DMSO) solution. Results show that such a nanocomposite hydrogel can undergo a large volumetric change in response to infrared (IR) light illumination, due to the highly efficient photothermal conversion of GO–GMA. It also exhibits significantly larger water uptake compared to conventional PNIPAAm hydrogel by 3 times. Based on the developed IR-responsive nanocomposite hydrogel, we have also realised a microvalve that controls the fluidic flow within a microfluidic channel through remote IR light actuation.

Autonomous microfluidics with stimuli-responsive hydrogels

Abstract: There has been increasing interest in integrated microfluidic systems because performing biological and chemical laboratory tasks on a single chip is appealing. One straightforward approach to constructing these ‘lab on chips’ is to fabricate individual components and to assemble them for desired functionalities. As the functionalities of the microfluidic systems become increasingly complicated, more functional components and relevant controls need to be integrated on a miniaturized chip, especially when a closed loop is needed for autonomous functionality. Instead, an emerging approach is to incorporate stimuli-responsive hydrogels directly into microfluidics to reduce the system complexity. Due to the hydrogels' ability of transducing stimuli into mechanical actions in response to their surrounding aqueous environment, hydrogel-based microfluidic elements can act as both sensors and actuators simultaneously, alleviating the requirement of most controls and even power sources. This provides microfluidic systems with autonomous functionalities. In this article, we will focus on a few autonomous microfluidic devices including valves, flow sorters, pH regulators, pumps, mixers, drug-delivery devices, fluidic cooling devices, and liquid microlenses.

On-chip spiral inductors suspended over deep copper-lined cavities

Abstract: A silicon micromachining method has been developed to fabricate on-chip high-performance suspended spiral inductors. The spiral structure of an inductor was formed with polysilicon and was suspended over a 30-/spl mu/m-deep cavity in the silicon substrate beneath. Copper (Cu) was electrolessly plated onto the polysilicon spiral to achieve low resistance. The Cu plating process also metallized the inner surfaces of the cavity, forming both a good radio-frequency (RF) ground and an electromagnetic shield. High quality factors (Qs) over 30 and self-resonant frequencies higher than 10 GHz have been achieved. A study of the mechanical properties of the suspended inductors indicates that they can withstand large shock and vibration. Simulation predicts a reduction of an order of magnitude in the mutual inductance of two adjacent inductors with the 30-/spl mu/m-deep Cu-lined cavity from that with silicon as the substrate. This indicates very small crosstalk between the inductors due to the shielding effect of the cavities.

Direct Sun-Driven Artificial Heliotropism for Solar Energy Harvesting Based on a Photo-Thermomechanical Liquid-Crystal Elastomer Nanocomposite

Abstract: Inspired by heliotropism in nature, artificial heliotropic devices that can follow the sun for increased light interception are realized. The mechanism of the artificial heliotropism is realized via direct actuation by the sunlight, eliminating the need for additional mechatronic components and resultant energy consumption. For this purpose, a novel reversible photo-thermomechanical liquid crystalline elastomer (LCE) nanocomposite is developed that can be directly driven by natural sunlight and possesses strong actuation capability. Using the LCE nanocomposite actuators, the artificial heliotropic devices show full-range heliotropism in both laboratory and in-field tests. As a result, significant increase in the photocurrent output from the solar cells in the artificial heliotropic devices is observed.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Abstract: We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1] . The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3] , DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac.uk/projects/segnet/ .

Emerging applications of stimuli-responsive polymer materials

Abstract: Responsive polymer materials can adapt to surrounding environments, regulate transport of ions and molecules, change wettability and adhesion of different species on external stimuli, or convert chemical and biochemical signals into optical, electrical, thermal and mechanical signals, and vice versa. These materials are playing an increasingly important part in a diverse range of applications, such as drug delivery, diagnostics, tissue engineering and 'smart' optical systems, as well as biosensors, microelectromechanical systems, coatings and textiles. We review recent advances and challenges in the developments towards applications of stimuli-responsive polymeric materials that are self-assembled from nanostructured building blocks. We also provide a critical outline of emerging developments.

Highly stretchable and tough hydrogels

Abstract: Hydrogels with improved mechanical properties, made by combining polymer networks with ionic and covalent crosslinks, should expand the scope of applications, and may serve as model systems to explore mechanisms of deformation and energy dissipation. Hydrogels are used in flexible contact lenses, as scaffolds for tissue engineering and in drug delivery. Their poor mechanical properties have so far limited the scope of their applications, but new strong and stretchy materials reported here could take hydrogels into uncharted territories. The new system involves a double-network gel, with one network forming ionic crosslinks and the other forming covalent crosslinks. The fracture energy of these materials is very high: they can stretch to beyond 17 times their own length even when containing defects that usually initiate crack formation in hydrogels. The materials' toughness is attributed to crack bridging by the covalent network accompanied by energy dissipation through unzipping of the ionic crosslinks in the second network. Hydrogels are used as scaffolds for tissue engineering1, vehicles for drug delivery2, actuators for optics and fluidics3, and model extracellular matrices for biological studies4. The scope of hydrogel applications, however, is often severely limited by their mechanical behaviour5. Most hydrogels do not exhibit high stretchability; for example, an alginate hydrogel ruptures when stretched to about 1.2 times its original length. Some synthetic elastic hydrogels6,7 have achieved stretches in the range 10–20, but these values are markedly reduced in samples containing notches. Most hydrogels are brittle, with fracture energies of about 10 J m−2 (ref. 8), as compared with ∼1,000 J m−2 for cartilage9 and ∼10,000 J m−2 for natural rubbers10. Intense efforts are devoted to synthesizing hydrogels with improved mechanical properties11,12,13,14,15,16,17,18; certain synthetic gels have reached fracture energies of 100–1,000 J m−2 (refs 11, 14, 17). Here we report the synthesis of hydrogels from polymers forming ionically and covalently crosslinked networks. Although such gels contain ∼90% water, they can be stretched beyond 20 times their initial length, and have fracture energies of ∼9,000 J m−2. Even for samples containing notches, a stretch of 17 is demonstrated. We attribute the gels’ toughness to the synergy of two mechanisms: crack bridging by the network of covalent crosslinks, and hysteresis by unzipping the network of ionic crosslinks. Furthermore, the network of covalent crosslinks preserves the memory of the initial state, so that much of the large deformation is removed on unloading. The unzipped ionic crosslinks cause internal damage, which heals by re-zipping. These gels may serve as model systems to explore mechanisms of deformation and energy dissipation, and expand the scope of hydrogel applications.