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Thermogels are an exciting class of stimuli responsive materials with many promising applications ranging from the medical field to additive manufacturing. This review focuses on the structure–property relationship of thermoresponsive block copolymers, with emphasis on the effect of architecture. Polymers based on Pluronic®, N-isopropylacrylamide, oligo(ethylene glycol) (meth)acrylate units, and 2-oxazoline units, which are amongst the most studied thermoresponsive units, are discussed. The effect of the polymer's architecture is crucial for controlling the thermoresponsive properties, such as cloud point and gelation temperature.

Thermoresponsive polymers based on oligo(ethylene glycol) (OEG) methyl ether methacrylate monomers have drawn much attention in recent years. In this investigation, copolymers based on oligo(ethylene glycol) methyl ether methacrylate (OEGMA, 300 g mol-1) and di(ethylene glycol) methyl ether methacrylate (DEGMA) or/and n-butyl methacrylate (n-BuMA) were successfully synthesised via group transfer polymerisation (GTP). The molar mass was kept constant around 10000 g mol-1, while the OEGMA content was varied from 80% w/w to 50% w/w. Three different structures including diblock bipolymer, diblock terpolymer and statistical copolymers were synthesised and compared. The thermoresponsive properties of the copolymers were investigated in deionised water and phosphate buffered saline (PBS), and in aqueous mixtures with Pluronic® F127. Interestingly, while the diblock polymers based on OEGMA and DEGMA were not able to form gel upon heating, they were found to lower the critical gelation concentration (CGC) of Pluronic® F127 from 15% w/w to 10% w/w and increase the gelation temperature from room temperature to near body temperature.

The Internet of Things has created an increasing demand for giant magnetoresistive (GMR) sensor owing to its high sensitivity, low power-consumption and small size. A full Wheatstone bridge GMR sensor is fabricated on 6-inch wafers with an annealing process on patterned devices. It can be observed that GMR resistors could have different pinning directions in one wafer by magnetic resistance measurements and MATLAB simulations. The full Wheatstone bridge device shows a sensitivity of 2 mV/V/mT in a linear range of ±6 mT, and its angular response to the surrounding magnetic field is as low as 0.08 mT. These results demonstrate a new approach to high-sensitive and low-cost GMR sensors with a controllable post annealing process.

The temperature dependence of magnetoresistance and switching characterization based on spin transfer torque (STT) effect of perpendicular magnetic tunnel junctions (p-MTJs) with MgO/CoFeB/W/CoFeB/MgO double-interface free layer was studied. The tunneling magnetoresistance (TMR) ratio increases from 95% to 176% for both 84 and 64 nm-diameter p-MTJs, upon decreasing the temperature from 400 to 20 K. This change of TMR is dominated by a steady increase in the resistance of antiparallel state while the parallel state conductance remains almost constant. Switching behavior at various temperatures is investigated for pulse voltage-dependent STT measurements; resistance versus voltage loops for both the switching directions become more symmetric with decreasing temperature. Furthermore, low-temperature measurements of magnetic properties suggest that the effect of stray field for STT becomes weaker as the temperature decreases, which suggests the p-MTJs design for cryogenic memories.

In this work, a novel method consisting of side-wall passivation and a top-metal reveal process is proposed for spintronics devices based on magnetic tunnel junctions (MTJs). The method can efficiently protect ferromagnetic metals and magnesium oxide, which are the key materials of MTJs, and effectively establish electrical contact with the interconnect metals for perpendicular MTJs (p-MTJs). The scheme consists of the passivation of MTJs with dual dielectrics – silicon nitride and silicon oxide – followed by planarization and selective wet etching. The proposed integration scheme was successfully demonstrated with 80-nm-diameter p-MTJ devices.

Magnetic tunnel junctions (MTJs) based on MgO/CoFeB/W structures are of particular interest for magnetic random access memories due to their high tunnel magnetoresistance, low damping, and stable properties at high annealing temperature. One of the major challenges is to obtain a strong interfacial perpendicular magnetic anisotropy (PMA) for sufficient thermal stability during data storage. Here we investigate magnetic anisotropy energies (MAEs) in the ferromagnet (FM)/W structure with different FM materials and interface insertions. We find that the Fe/W interface exhibits a remarkable PMA, whereas the Co/W interface displays a large in-plane anisotropy, which reduces the PMA in the MgO/CoFeB/W structure. By inserting a thin Fe layer at the CoFe/W interface, the interfacial PMA can be enhanced to 3.34 mJ/m2. Microscopic mechanism behind these phenomena is explained with the changes of orbital-resolved MAEs due to the charge redistribution at the interface. These findings pave a new way for the enhancement of PMA and point toward the possibility of achieving high thermal stability in small-node MTJs.

The development of online social environments has changed the manner of social interaction and communication, which are driven by individual human actions. Thus temporal variations in interaction networks are deeply impacted by the temporal dimension of human activity. In this paper, we address this issue through a detailed analysis on the retweets and comments of 550,000 Twitter users. We propose a temporal network model to represent the interaction network on Twitter, in which each node contains an activity window and the emergence of the edges between nodes are dependent on it. Specifically, the activity window is defined as the backtracking length from the message flow posted by the user’s friend, which represents the user’s social ability. It complies with a power-law distribution with an exponential cut-off. The interaction network is sparser and more clustered than the followee-follower network, in which the interaction stability and burstiness fluctuate with the activity window or with the degree to which the two users are involved in the communication. Finally, the effect of activity window on the aggregating degrees of the interaction network is examined.

Bi metal attached BiOBr with oxygen defect (BiOBr(3)-Bi(x%, x = 10, 20, 30)) nanosheets was prepared via the hydrothermal process in this study. The different characterization techniques of x-ray diffraction, x-ray photoelectron spectrometer, electron spin resonance (ESR), field emission scanning electron microscope, and high resolution transmission electron microscope were used to distinguish the composition, crystal structure, and morphology of the samples. Under visible light irradiation, the BiOBr(3)-Bi(x%, x = 10, 20, 30) samples exhibited improved photocatalytic activity for the degradation of colored dyes (RhB) and colorless tetracycline hydrochloride. Such an improvement was ascribed to the widened visible light absorption and enhanced separation of the photogenerated electron–hole pairs because of the synergistic effect of oxygen vacancies and Bi metal with plasmon resonance effects. A possible photocatalytic mechanism of the quasi Z-scheme process was proposed on the basis of ESR measurements and radical-trapping experiments.

Voltage control of magnetism promises great energy efficiency in writing magnetic memory. Here, using Cr/Mo/CoFeB/MgO multilayers stable under high annealing temperatures up to 590°C, we significantly enhance the interfacial crystallinity, thereby the interface-originated perpendicular magnetic anisotropy (PMA), voltage-controlled magnetic anisotropy (VCMA), and interface magnetoelectric (ME) effect. High interfacial PMA of 1.35 mJ/m2, VCMA coefficient of −138 fJ/(V m), and interface ME coefficient, which is 2–3 orders of magnitude larger than ab initio calculation results are simultaneously achieved after annealing at 500°C. These promising results enabled by the industry-applicable sputtering process will pave the way for high-density voltage-controlled spintronic devices.

We experimentally demonstrate the field-free and ultra-low-power switching of perpendicular magnetization by combination of spin-orbit torque (SOT), exchange bias (EB) and voltage-controlled magnetic anisotropy (VCMA) effect. Field-free SOT switching is achieved with the aid of an inplane exchange bias generated in the perpendicularly magnetized IrMn/CoFeB/MgO structure. By applying a gate voltage of 0.6 V, the SOT switching current can be reduced by 49% (to 6.2 MA/cm2). Finally, we successfully demonstrate the prototype of a high-density and ultra-low-power voltagegated spintronic memory by both experiments and simulations.

The processing-in-memory (PIM) paradigm has been considered as a promising alternative to break the bottlenecks of conventional von-Neumann architecture by realizing the unity of data storage and processing in the same die. On the road toward implementing such an architecture, finding a novel memory that can support both dense data storage and efficient logic processing is the critical step. In this letter, we report a voltage-controlled magnetic tunnel junction (MTJ), which is a potential candidate for PIM implementation. Stateful Boolean logic functions can be realized with a single device through the memory-like write/read operations. The device was fabricated and characterized at room temperature. Afterwards, typical Boolean logic operations, e.g., “OR”, “AND”, and “NXOR”, were experimentally demonstrated with the fabricated MTJ device. The proposed approach opens up a new way for PIM implementation in spintronic memories.

The high current density required by magnetic tunneling junction (MTJ) switching driven by the spin transfer torque (STT) effect leads to large power consumption and severe reliability issues, hindering the timetable for STT magnetic random access memory to mass market. By utilizing the voltage-controlled magnetic anisotropy (VCMA) effect, the MTJ can be switched by the voltage effect and is postulated to achieve ultralow power (fJ). However, the VCMA coefficient measured in experiments cannot meet the requirement for MTJ with dimensions below 100 nm. And an external in-plane magnetic field usually is demanded for precessional VCMA switching. Here, in this paper, a novel approach for the amplification of the VCMA effect, which borrows ideas from negative capacitance, is proposed. The feasibility of the proposal is proved by physical simulation and in-depth analysis. Since the amplified VCMA effect, the external magnetic field can be eliminated. A three-terminal novel MTJ memory cell is designed with which both low power and high speed can be achieved.

Stateful in-memory logic (IML) is a promising paradigm to realize the unity of data storage and processing in the same die, exhibiting great feasibility to break the bottleneck of the conventional von Neumann architecture. On the roadmap toward developing such a logic platform, a critical step is the effective and efficient realization of a complete set of logic functions within a memory. In this paper, we report a realization of stateful reconfigurable logic functions via a single three-terminal magnetic tunnel junction (MTJ) device within a spintronic memory by exploiting the novel voltage-gated spin Hall-effect driven magnetization switching mechanism. This proposed reconfigurable IML methodology can be implemented within either a typical memory array or a cross-point array architecture. The feasibility of the proposed approach is successfully demonstrated with hybrid MTJ/CMOS circuit simulations. We believe our work may promote the research and development of the revolutionary IML for future non-von Neumann architectures.

In the manufacturing process of the microfiber synthetic leather, various types of filling agents were selected to fill the microfiber synthetic leather base to improve the sanitary properties, in which a zirconium tanning agent was used commonly. In this study, the softness, moisture absorption, water vapor permeability and mechanical properties of the base were used as indexes, and the type and dosage of the filling agent were optimized. The results indicated that the sanitary properties of the base treated by the filling agent were improved generally compared with that of the blank base. Among them, the moisture absorption increased by 28–45%, the water vapor permeability increased by 50–56% and the mechanical properties were significantly improved. The bases before and after being filled were characterized by Fourier infrared spectroscopy, the water contact angle, atomic force microscopy, scanning electron microscopy and the specific surface area. The results showed that the filling agent’s cross-linking effect on the base fiber led to the active group content and wettability of the base increasing, the fiber surface structure changing obviously and the fiber gap becoming larger with looser dispersion. Moreover, the specific surface area of the base increased.

Magnetic tunnel junctions (MTJs) with interfacial perpendicular magnetic anisotropy (PMA) attract much attention due to their utilization in spin-transfer torque magnetic random-access memory (STT-MRAM). Large interfacial PMA provides high thermal stability, which is critical for large-capacity MTJ arrays. We investigate the thermal stability and interfacial PMA needed for STT-MRAM applications. A thermal stability factor of 75 is required for data retention time of 10 years, which implies an interfacial PMA value of 4.7 mJ/m2 as device sizes scale down to 10 nm. Even though a small retention time (e.g., 1 ms) is sufficient in some applications, such as cache memory, an interfacial PMA greater than 3.1 mJ/m2 would be necessary for 10 nm MTJ pillars. When read disturbance is taken into consideration, the PMA should be larger. These findings provide guidelines for the design of sub-20 nm MTJ devices for large-capacity STT-MRAM.

We analyze five big data sets from a variety of online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors. For example, there is linear growth associated with online recommendation and sharing platforms, a plateaued (or an ``S''-shape) type of growth behavior in a web service devoted to helping users to collect bookmarks, and an exponential increase on the largest and most popular microblogging website in China. Does a universal mechanism with a common set of dynamical rules exist, which can explain these empirically observed, distinct growth behaviors? We provide an affirmative answer in this paper. In particular, inspired by biomimicry to take advantage of cell population growth dynamics in microbial ecology, we construct a base growth model for meme popularity in OSNs. We then take into account human factors by incorporating a general model of human interest dynamics into the base model. The final hybrid model contains a small number of free parameters that can be estimated purely from data. We demonstrate that our model is universal in the sense that, with a few parameters estimated from data, it can successfully predict the distinct meme growth dynamics. Our study represents a successful effort to exploit principles in biology to understand online social behaviors by incorporating the traditional microbial growth model into meme popularity. Our model can be used to gain insights into critical issues such as classification, robustness, optimization, and control of OSN systems., Comment: 18 pages, 13 figures

In this review we discuss how synthetic biology facilitates the task of investigating genetic circuits that are observed in naturally occurring biological systems. Specifically, we give examples where experimentation with synthetic gene circuits has been used to understand four fundamental mechanisms intrinsic to development and disease: multistability, stochastic gene expression, oscillations, and cell-cell communication. Within each area, we also discuss how mathematical modeling has been employed as an essential tool to guide the design of novel gene circuits and as a theoretical basis for exploring circuit topologies exhibiting robust behaviors in the presence of noise.

Perpendicular magnetic tunnel junctions (MTJs) based on MgO/CoFeB structures are of particular interest for spin-transfer torque magnetic random access memories (STT-MRAMs). However, their major challenges of combining both a large tunnel magneto-resistance ratio (TMR) and a low junction resistance, a strong interfacial perpendicular magnetic anisotropy (PMA) for the high thermal stability and a low STT switching critical current density are still to be met. In this paper, we show our recent progress in studying the pertinence of capping layers to several principal spintronic effects such as PMA, TMR and Gilbert damping. And we predict and experimentally prove the performance optimization the by the interfacial property tuning of heavy metal/CoFeB.

A challenging problem in network science is to control complex networks. In existing frameworks of structural or exact controllability, the ability to steer a complex network toward any desired state is measured by the minimum number of required driver nodes. However, if we implement actual control by imposing input signals on the minimum set of driver nodes, an unexpected phenomenon arises: due to computational or experimental error there is a great probability that convergence to the final state cannot be achieved. In fact, the associated control cost can become unbearably large, effectively preventing actual control from being realized physically. The difficulty is particularly severe when the network is deemed controllable with a small number of drivers. Here we develop a physical controllability framework based on the probability of achieving actual control. Using a recently identified fundamental chain structure underlying the control energy, we offer strategies to turn physically uncontrollable networks into physically controllable ones by imposing slightly augmented set of input signals on properly chosen nodes. Our findings indicate that, although full control can be theoretically guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control cost to achieve physical control.

We report a robust perpendicularly magnetized β-W/CoFeB/MgO multilayer structure. For the first time, we demonstrate efficient spin–orbit torque (SOT) switching and a highly thermally stable annealing process with this structure using X-ray diffraction tests, the harmonic technique, and SOT-driven magnetization switching measurements. These results may enable applications of SOT-based magnetic random access memory, which is required for integration in the CMOS back-end-of-line process.

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control., Complex networks, including physical, biological and social systems are ubiquitous, but understanding of how to control them is elusive. Here Wang et al. develop a framework based on the concept of attractor networks to facilitate the study of controllability of nonlinear dynamics in complex systems.

Magnetic tunnel junction nanopillar with interfacial perpendicular magnetic anisotropy (PMA-MTJ) becomes a promising candidate to build up spin transfer torque magnetic random access memory (STT-MRAM) for the next generation of non-volatile memory as it features low spin transfer switching current, fast speed, high scalability, and easy integration into conventional complementary metal oxide semiconductor (CMOS) circuits. However, this device suffers from a number of failure issues, such as large process variation and tunneling barrier breakdown. The large process variation is an intrinsic issue for PMA-MTJ as it is based on the interfacial effects between ultra-thin films with few layers of atoms; the tunneling barrier breakdown is due to the requirement of an ultra-thin tunneling barrier (e.g.

We study the impact of Mg insertion layer at the CoFeB|MgO interface on the domain wall depinning field and motion as well as other magnetic properties in a perpendicular magnetized Ta/CoFeB/Mg(wedged)/MgO structure. With the increase of the Mg layer from 0.4 nm to 0.8 nm, the field-induced domain wall moving velocity increases while the depinning field decreases. The minimum depinning field of around 10 Oe for as-grown sample and 7 Oe for annealed sample is found with a 0.8 nm Mg insertion layer, which is 2 times lower than the ones reported before. Further increase of the Mg layer leads to a lower velocity and higher depinning field. Similar phenomena happens to the magnetic properties such as the saturation magnetization and perpendicular magnetic anisotropy. Both for as-grown and annealed samples, the tendency is similar. This may be explained by the oxidation and crystallinity manipulation of the CoFeB|MgO interface. These results show an ultra-low depinning field in the Ta/CoFeB/MgO system as well as a possible way for controlling the depinning field.

Beyond memory and storage, future logic applications put forward higher requirements for electronic devices. All spin logic devices (ASLDs) have drawn exceptional interest as they utilize pure spin current instead of charge current, which could promise ultra-low power consumption. However, relatively low efficiencies of spin injection, transport, and detection actually impede high-speed magnetization switching and challenge perspectives of ASLD. In this work, we study partial spin absorption induced magnetization switching in asymmetrical ASLD at the mesoscopic scale, in which the injector and detector have the nano-fabrication compatible device size (>100 nm) and their contact areas are different. The enlarged contact area of the detector is conducive to the spin current absorption, and the contact resistance difference between the injector and the detector can decrease the spin current backflow. Rigorous spin circuit modeling and micromagnetic simulations have been carried out to analyze the electrical ...

Spin transfer torque-based magnetoresistive random access memory (STT-MRAM) promises to be the next-generation low-power universal memory thanks to the non-volatility, infinite endurance and fast switching speed. In particular, recently the research and application of the STT-MRAM have been greatly advanced by the launch of the commercial chip. In this paper, we firstly present the basic principle and development history of the STT-MRAM, highlighting the improvement in the write technology and magnetic anisotropy. Then the recent progresses are reviewed including the following three aspects: first, much research effort has been made to explore the influence of the fabrication process and device structure on the interfacial perpendicular magnetic anisotropy; second, CoFeB-MgO double-interface structure has been proposed to enhance the thermal stability of the magnetic tunnel junction (MTJ) without the increase in the write current; third, emerging spin-orbit torque (SOT) has attracted massive research interest since it promises to overcome the speed bottleneck and high-risk barrier breakdown suffered by the conventional STT. Finally, the recent development of the STT-MRAM chips is summarized.

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks.

One key process in data-driven methodology is how to use the data easily and efficiently. In this paper, an immune-enhanced unfalsified controller (IEUC) is proposed to act as an efficient process to deal with data. The IEUC consists of two parts, the first part is a unfalsified controller deriving from data-driven methodology; the second part is an immune feedback controller inspired from biologic intelligent methodology. In order to examine control effectiveness of the IEUC, we apply it to a complex plant in high-speed spinning model and compare it with a simple unfalsified control scheme. Simulation results demonstrate that the IEUC can decrease system overshoot as well as reduce rising time successfully and effectively.

Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.