We investigated thermal properties of the epoxy-based composites with a high loading fractionup to ≈ 45 vol. % -of the randomly oriented electrically conductive graphene fillers and electrically insulating boron nitride fillers. It was found that both types of the composites revealed a distinctive thermal percolation threshold at the loading fraction > 20 vol. %. The graphene loading required for achieving the thermal percolation, , was substantially higher than the loading, , for the electrical percolation. Graphene fillers outperformed boron nitride fillers in the thermal conductivity enhancement. It was established that thermal transport in composites with the high filler loading, ≥ , is dominated by heat conduction via the network of percolating fillers. Unexpectedly, we determined that the thermal transport properties of the high loading composites were influenced strongly by the cross-plane thermal conductivity of the quasi-twodimensional fillers. The obtained results shed light on the debated mechanism of the thermal × Contributed equally to the work. * Corresponding author (A.A.B.): balandin@ece.ucr.edu ; web-site: http://balandingroup.ucr.edu/ Thermal Percolation Threshold and Thermal Properties of Composites with Graphene and Boron Nitride Fillers, UCR (2018) 2 | P a g e percolation, and facilitate the development of the next generation of the efficient thermal interface materials for electronic applications. Main TextThe discovery of unique heat conduction properties of graphene 1-7 motivated numerous practically oriented studies of the use of graphene and few-layer graphene (FLG) in various composites, thermal interface materials and coatings [8][9][10][11][12][13][14][15] . The intrinsic thermal conductivity of large graphene layers exceeds that of the high-quality bulk graphite, which by itself is very high -2000 Wm −1 K −1 at room temperature (RT) 1,11,16,17 . The first studies of graphene composites found that even a small loading fractions of randomly oriented graphene fillers -up to = 10 vol. %can increase the thermal conductivity of epoxy composites by up to a factor of ×25 [Ref. 11]. These results have been independently confirmed by different research groups 18,19 . The variations in the reported thermal data for graphene composites can be explained by the differences in the methods of preparation, matrix materials, quality of graphene, lateral sizes and thickness of graphene fillers and other factors 3,20-25 . Most of the studies of thermal composites with graphene were limited to the relatively low loading fractions, ≤ 10 vol. %. The latter was due to difficulties in preparation of high-loading fraction composites with a uniform dispersion of graphene flakes. The changes in viscosity and graphene flake agglomeration complicated synthesis of the consistent set of samples with the loading substantially above = 10 vol. %.Investigation of thermal properties of composites with the high loading fraction of graphene or FLG fillers is interesting from both fundamental science and practical applicat...

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UC Riverside and Quantum Seed LLC (2015) 2 | P a g e AbstractWe report on heat conduction properties of thermal interface materials with self-aligning "magnetic graphene" fillers. Graphene enhanced nano-composites were synthesized by an inexpensive and scalable technique based on liquid-phase exfoliation. Functionalization of graphene and few-layer-graphene flakes with Fe3O4 nanoparticles allowed us to align the fillers in an external magnetic field during dispersion of the thermal paste to the connecting surfaces. The filler alignment results in a strong increase of the apparent thermal conductivity and thermal diffusivity through the layer of nano-composite inserted between two metallic surfaces. The selfaligning "magnetic graphene" fillers improve heat conduction in composites with both curing and non-curing matrix materials. The thermal conductivity enhancement with the oriented fillers is a factor of two larger than that with the random fillers even at the low ~1 wt. % of graphene loading.The real-life testing with computer chips demonstrated the temperature rise decrease by as much as 10 o C with use of the non-curing thermal interface material with ~1 wt. % of the oriented fillers.Our proof-of-concept experiments suggest that the thermal interface materials with functionalized graphene and few-layer-graphene fillers, which can be oriented during the composite application to the surfaces, can lead to a new method of thermal management of advanced electronics.

development of next generation of compact and flexible electronics. [1] The increase in computer usage and ever-growing dependence on cloud systems require better methods for dissipating heat away from electronic components. The important ingredients of thermal management are the thermal interface materials (TIMs). Various TIMs interface two uneven solid surfaces where air would be a poor conductor of heat, and aid in heat transfer from one medium into another. Two important classes of TIMs include curing and noncuring composites. Both of them consist of a base, i.e., matrix materials, and thermally conducting fillers. Commonly, the studies of new fillers for the use in TIMs start with the curing epoxybased composites owing to the relative ease of preparation and possibility of comparison with a wide range of other epoxy composites. Recent work on TIMs with carbon fillers have focused on curing composites, which dry to solid. [2][3][4][5][6][7] Curing TIMs are required for many applications, e.g. attachment of microwave devices, but do not cover all thermal management needs. Thermal management of computers requires specifically noncuring TIMs, which are commonly referred to as thermal pastes or thermal greases. They are soft pliable materials, which unlike cured epoxy-based composites, or phase change materials, remain soft once applied. This aids in avoiding crack formations in the bond line due to repeated thermal cycling of two connected materials with different temperature expansion coefficients. Noncuring TIMs also allow for easy reapplication, known as a TIM's reworkability property. Noncuring TIMs are typically cost efficient-an essential requirement for commercial applications. Various applications in electronics, noncuring grease-like (soft) TIMs are preferred. Examples of the applications include but are not limited to cooling of servers in large data centers [8] and personal devices which are the primary targets for these applications. Current commercially available TIMs perform in thermal conductivity range of 0.5-5 Wm −1 K −1 with combination of several fillers at high loading fractions. [9] State-of-the-art and next-generation electronic devices require thermal pastes with bulk thermal conductivity in the range of 20-25 Wm −1 K −1 . [10,11] This study focuses specifically on noncuring TIMs with graphene and few-layer graphene (FLG) fillers.Curing and noncuring TIMs consists of two main components-a polymer or oil material as its base and fillers, Development of next-generation thermal interface materials (TIMs) with high thermal conductivity is important for thermal management and packaging of electronic devices. The synthesis and thermal conductivity measurements of noncuring thermal paste, i.e., grease, based on mineral oil with a mixture of graphene and few-layer graphene flakes as the fillers, is reported. The graphene thermal paste exhibits a distinctive thermal percolation threshold with the thermal conductivity revealing a sublinear dependence on the filler loading. This behavior contrasts wi...

We report the results of an experimental study of thermal and magnetic properties of nanostructured ferrimagnetic iron oxide composites with graphene and graphite fillers synthesized via the current activated pressure assisted densification. The thermal conductivity was measured using the laser-flash and transient plane source techniques. It was demonstrated that addition of 5 wt. % of equal mixture of graphene and graphite flakes to the composite results in a factor of ×2.6 enhancement of the thermal conductivity without significant degradation of the saturation magnetization.The microscopy and spectroscopic characterization reveal that sp 2 carbon fillers preserve their crystal structure and morphology during the composite processing. The strong increase in the thermal conductivity was attributed to the excellent phonon heat conduction properties of graphene and graphite.The results are important for energy and electronic applications of the nanostructured permanent magnets. management 3 | P a g e

We report results regarding the electron transport in vertical quasi-2D layered 1T-TaS2 chargedensity-wave devices. The low-frequency noise spectroscopy was used as a tool to study changes in the cross-plane electrical characteristics of the quasi-2D material below room temperature. The noise spectral density revealed strong peaks -changing by more than an order-of-magnitude -at the temperatures closely matching the electrical resistance steps. Some of the noise peaks appeared below the temperature of the commensurate to nearlycommensurate charge-density-wave transition, possibly indicating the presence of the debated "hidden" phase transitions. These results confirm the potential of the noise spectroscopy for investigations of electron transport and phase transitions in novel materials. / R. Salgado et al., Low-Frequency Noise Spectroscopy of CDW Phase Transitions in Vertical Quasi-2D Devices / UCR 2 | P a g eThe charge-density-wave (CDW) phase is a macroscopic quantum state consisting of a periodic modulation of the electronic charge density accompanied by a periodic distortion of the atomic lattice in metallic crystals [1][2][3]. Recently, the field of CDW materials and devices experienced a true renaissance [4][5][6][7][8][9][10][11][12][13][14][15][16]. The renewed interest has been driven by layer-control of CDW materials, such as quasi-two-dimensional (2D) crystals of 1T-TaS2 and other transition metal dichalcogenides (TMDs). Unlike classical bulk CDW materials with the quasi-1D crystalline

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Network security encloses a wide set of technologies dealing with intrusions detection. Despite the massive adoption of signature-based network intrusion detection systems (IDSs), they fail in detecting zero-day attacks and previously unseen vulnerabilities exploits. Behaviour-based network IDSs have been seen as a way to overcome signature-based IDS flaws, namely through the implementation of machine-learning-based methods, to tolerate new forms of normal network behaviour, and to identify yet unknown malicious activities. A wide set of machine learning methods has been applied to implement behaviour-based IDSs with promising results on detecting new forms of intrusions and attacks. Innovative machine learning techniques have emerged, namely deep-learning-based techniques, to process unstructured data, speed up the classification process, and improve the overall performance obtained by behaviour-based network intrusion detection systems. The use of realistic datasets of normal and malicious networking activities is crucial to benchmark machine learning models, as they should represent real-world networking scenarios and be based on realistic computers network activity. This paper aims to evaluate CSE-CIC-IDS2018 dataset and benchmark a set of deep-learning-based methods, namely convolutional neural networks (CNN) and long short-term memory (LSTM). Autoencoder and principal component analysis (PCA) methods were also applied to evaluate features reduction in the original dataset and its implications in the overall detection performance. The results revealed the appropriateness of using the CSE-CIC-IDS2018 dataset to benchmark supervised deep learning models. It was also possible to evaluate the robustness of using CNN and LSTM methods to detect unseen normal activity and variations of previously trained attacks. The results reveal that feature reduction methods decreased the processing time without loss of accuracy in the overall detection performance.