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The near-infrared photoluminescence intrinsic to semiconducting single-walled carbon nanotubes is ideal for biological imaging owing to the low autofluorescence and deep tissue penetration in the near-infrared region beyond 1 µm. However, biocompatible single-walled carbon nanotubes with high quantum yield have been elusive. Here, we show that sonicating single-walled carbon nanotubes with sodium cholate, followed by surfactant exchange to form phospholipidpolyethylene glycol coated nanotubes, produces in vivo imaging agents that are both bright and biocompatible. The exchange procedure is better than directly sonicating the tubes with the phospholipid-polyethylene glycol, because it results in less damage to the nanotubes and improves the quantum yield. We show whole-animal in vivo imaging using an InGaAs camera in the 1-1.7 µm spectral range by detecting the intrinsic near-infrared photoluminescence of the 'exchange' single-walled carbon nanotubes at a low dose (17 mg l −1 injected dose). The deep tissue penetration and low autofluorescence background allowed high-resolution intravital microscopy imaging of tumour vessels beneath thick skin.Single-walled carbon nanotubes (SWNTs) have shown potential for biological and medical 1 applications because of their intrinsic optical properties and ability to load both targeting ligands and chemotherapy drugs, in vitro 2,3 and in vivo 4-6. Their unique optical properties make SWNTs attractive candidates for biological imaging7 -11 and sensing12. In particular, the near-infrared (NIR) photoluminescence of semiconducting SWNTs13 has made them promising as NIR fluorescent contrast agents in biological systems8 -11. SWNT NIR fluorescent probes with emission mostly in the infrared-A (IR-A, 1-1.4 µm) region (Fig. 1) are ideal as biological probes because of the inherently low autofluorescence in the NIR range (0.8-1.7 µm) 14 and large Stokes shift between the excitation and emission bands, which allows excitation in the biological transparency window15 near 800 nm while further reducing the background effects of autofluorescence and scattering. Work carried out by Lim and colleagues16 has predicted that NIR fluorophores with emission in the 1,100-1,400 nm range have higher tissue penetration than those near 800 nm by considering the

We address the problem of acoustic source separation in a deep learning framework we call "deep clustering". Rather than directly estimating signals or masking functions, we train a deep network to produce spectrogram embeddings that are discriminative for partition labels given in training data. Previous deep network approaches provide great advantages in terms of learning power and speed, but previously it has been unclear how to use them to separate signals in a classindependent way. In contrast, spectral clustering approaches are flexible with respect to the classes and number of items to be segmented, but it has been unclear how to leverage the learning power and speed of deep networks. To obtain the best of both worlds, we use an objective function that to train embeddings that yield a low-rank approximation to an ideal pairwise affinity matrix, in a classindependent way. This avoids the high cost of spectral factorization and instead produces compact clusters that are amenable to simple clustering methods. The segmentations are therefore implicitly encoded in the embeddings, and can be "decoded" by clustering. Preliminary experiments show that the proposed method can separate speech: when trained on spectrogram features containing mixtures of two speakers, and tested on mixtures of a held-out set of speakers, it can infer masking functions that improve signal quality by around 6dB. We show that the model can generalize to three-speaker mixtures despite training only on twospeaker mixtures. The framework can be used without class labels, and therefore has the potential to be trained on a diverse set of sound types, and to generalize to novel sources. We hope that future work will lead to segmentation of arbitrary sounds, with extensions to microphone array methods as well as image segmentation and other domains.

Potassium-ion batteries (PIBs) are interesting as one of the alternative metal-ion battery systems to lithium-ion batteries (LIBs) due to the abundance and low cost of potassium. We have herein investigated SnP/C composite as a novel anode material for PIBs. The electrode delivered a reversible capacity of 384.8 mA h g at 50 mA g and a good rate capability of 221.9 mA h g, even at 1 A g. Its electrochemical performance is better than any anode material reported so far for PIBs. It was also found that the SnP/C electrode displays a discharge potential plateau of 0.1 V in PIBs, slightly higher than for sodium-ion batteries (SIBs) (0.01 V), and well above the plating potential of metal. This diminishes the formation of dendrites during cycling, and thus SnP is a relatively safe anode material, especially for application in large-scale energy storage, where large amounts of electrode materials are used. Furthermore, a possible reaction mechanism of the SnP/C composite as PIB anode is proposed. This work may open up a new avenue for further development of alloy-based anodes with high capacity and long cycle life for PIBs.

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Structural phase transitions can be used to alter the properties of a material without adding any additional elements and are therefore of significant technological value. It was found that the hexagonal-SnS2 phase can be transformed into the orthorhombic-SnS phase after an annealing step in an argon atmosphere, and the thus transformed SnS shows enhanced sodium-ion storage performance over that of the SnS2, which is attributed to its structural advantages. Here, we provide the first report on a SnS@graphene architecture for application as a sodium-ion battery anode, which is built from two-dimensional SnS and graphene nanosheets as complementary building blocks. The as-prepared SnS@graphene hybrid nanostructured composite delivers an excellent specific capacity of 940 mAh g(-1)and impressive rate capability of 492 and 308 mAh g(-1) after 250 cycles at the current densities of 810 and 7290 mA g(-1), respectively. The performance was found to be much better than those of most reported anode materials for Na-ion batteries. On the basis of combined ex situ Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and ex situ X-ray diffraction, the formation mechanism of SnS@graphene and the synergistic Na-storage reactions of SnS in the anode are discussed in detail. The SnS experienced a two-structural-phase transformation mechanism (orthorhombic-SnS to cubic-Sn to orthorhombic-Na3.75Sn), while the SnS2 experienced a three-structural-phase transformation mechanism (hexagonal-SnS2 to tetragonal-Sn to orthorhombic-Na3.75Sn) during the sodiation process. The lesser structural changes of SnS during the conversion are expected to lead to good structural stability and excellent cycling stability in its sodium-ion battery performance. These results demonstrate that the SnS@graphene architecture offers unique characteristics suitable for high-performance energy storage application.

2General Relativity predicts that a star passing close to a supermassive black hole should exhibit a relativistic redshift. We test this using observations of the Galactic center star S0-2. We combine existing spectroscopic and astrometric measurements from 1995-2017, which cover S0-2's 16-year orbit, with measurements in 2018 March to September which cover three events during its closest approach to the black hole. We detect the combination of special relativistic-and gravitational-redshift, quantified using a redshift parameter, Υ. Our result, Υ = 0.88 ± 0.17, is consistent with General Relativity (Υ = 1) and excludes a Newtonian model (Υ = 0 ) with a statistical significance of 5 σ.General Relativity (GR) has been thoroughly tested in weak gravitational fields in the Solar System (1), with binary pulsars (2) and with measurements of gravitational waves from stellarmass black-hole binaries (3,4). Observations of short-period stars in our Galactic center (GC) (5-8) allow GR to be tested in a different regime (9): the strong field near a supermassive black hole (SMBH) (10,11). The star S0-2 (also known as S2) has a 16 year orbit around Sagittarius A* (Sgr A*), the SMBH at the center of the Milky Way. In 2018 May, it reached its point of closest approach, at a distance of 120 astronomical units (au) with a velocity reaching 2.7% of the speed of light. Within a 6 months interval of that date, the star also passed through its maximum (March) and minimum velocity (September) along the line-of-sight, spanning a range of 6000 km s −1 in radial velocity (RV - Fig. 1). We present observations of all three events and combine them with data from 1995-2017 ( Fig. 2).During 2018, the close proximity of S0-2 to the SMBH causes the relativistic redshift, which is the combination of the transverse Doppler shift from special relativity and the gravitational redshift from GR. This deviation from a Keplerian orbit was predicted to reach 200 km s −1 (Fig. 3) and is detectable with current telescopes. The GRAVITY collaboration (9) previously reported a similar measurement. Our measurements are complementary: i) we present a 3 complete set of independent measurements with 3 additional months of data, doubling the time baseline for the year of closest approach, and including the third turning point (RV minimum) in September 2018, ii) we use three different spectroscopic instruments in 2018, which allows us to probe the presence of instrumental biases, iii) we perform an analysis of the systematic errors that may arise from an experiment spanning over 20 years to test for bias in the result, and iv) we publicly release the stellar measurements and the posterior probability distributions.We use a total of 45 astrometric positional measurements (spanning 24 years) and 115 RVs (18 years) to fit the orbit of S0-2. Of these, 11 are new astrometric measurements of S0-2 from 2016 to 2018 and 28 are new RV measurements from 2017 and 2018 ( Fig 1). Astrometric measurements were obtained at the W. M. Keck Observatory using speckle imaging (a ...

A graphene/TiO 2 nanocrystals hybrid has been successfully prepared by directly growing TiO 2 nanocrystals on graphene oxide (GO) sheets. The direct growth of the nanocrystals on GO sheets was achieved by a two-step method, in which TiO 2 was first coated on GO sheets by hydrolysis and crystallized into anatase nanocrystals by hydrothermal treatment in the second step. Slow hydrolysis induced by the use of EtOH/H 2 O mixed solvent and addition of H 2 SO 4 facilitates the selective growth of TiO 2 on GO and suppresses growth of free TiO 2 in solution. The method offers easy access to the GO/TiO 2 nanocrystals hybrid with a uniform coating and strong interactions between TiO 2 and the underlying GO sheets. The strong coupling gives advanced hybrid materials with various applications including photocatalysis. The prepared graphene/TiO 2 nanocrystals hybrid has superior photocatalytic activity to other TiO 2 materials in the degradation of rhodamine B, showing an impressive three-fold photocatalytic enhancement over P25. It is expected that the hybrid material could also be promising for various other applications including lithium ion batteries, where strong electrical coupling to TiO 2 nanoparticles is essential. KEYWORDSGraphene, titanium oxide, photocatalyst, hydrolysis Its interesting electrical and mechanical properties, and high surface area make graphene a novel substrate for forming hybrid structures with a variety of nanomaterials [1][2][3]. Graphene hybrids with metal oxides, metals and polymers have been developed recently for various applications [4][5][6]. Nanocrystal growth on graphene sheets is an important approach to produce nanohybrids, since controlled nucleation and growth affords optimal chemical interactions and bonding between nanocrystals and graphene sheets, leading to very strong electrical and mechanical coupling within the hybrid. Several methods have been proposed to form nanocrystals on graphene sheets, such as electrochemical deposition [7], sol-gel process [8] and gas phase deposition [9,10]. Recently, we developed a controlled, two-step solution phase synthesis of nanocrystals of Ni, Fe, and Co hydroxides or oxides on graphene sheets, which is highly selective in that there is no growth of free nanocrystals in solution [1]. We demonstrated the excellent performance of nickel hydroxide nanoplates grown on graphene for electrochemical pseudocapacitive energy storage, utilizing Nano Res. 2010, 3(10): 701-705