First-principles Analysis of Photo-current in Graphene PN Junctions

We report a first principles investigation of photocurrent generation by graphene PN junctions. The junctions are formed by either chemically doping with nitrogen and boron atoms, or by controlling gate voltages. Non-equilibrium Green's function (NEGF) formalism combined with density functional theory (DFT) is applied to calculate the photo-response function. The graphene PN junctions show a broad band photo-response including the terahertz range. The dependence of the response on the angle between the light polarization vector and the PN interface is determined. Its variation against photon energy $E_{ph}$ is calculated in the visible range. The essential properties of chemically doped and gate-controlled PN junctions are similar, but the former shows fingerprints of dopant distribution.Comment: 7 pages, 6 figure

Real-Time MRI-Guided Catheter Tracking Using Hyperpolarized Silicon Particles

Visualizing the movement of angiocatheters during endovascular interventions is typically accomplished using x-ray fluoroscopy. There are many potential advantages to developing magnetic resonance imaging-based approaches that will allow three-dimensional imaging of the tissue/vasculature interface while monitoring other physiologically-relevant criteria, without exposing the patient or clinician team to ionizing radiation. Here we introduce a proof-of-concept development of a magnetic resonance imaging-guided catheter tracking method that utilizes hyperpolarized silicon particles. The increased signal of the silicon particles is generated via low-temperature, solid-state dynamic nuclear polarization, and the particles retain their enhanced signal for ≥40 minutes—allowing imaging experiments over extended time durations. The particles are affixed to the tip of standard medical-grade catheters and are used to track passage under set distal and temporal points in phantoms and live mouse models. With continued development, this method has the potential to supplement x-ray fluoroscopy and other MRI-guided catheter tracking methods as a zero-background, positive contrast agent that does not require ionizing radiation

Developing hyperpolarized silicon particles for in vivo MRI targeting of ovarian cancer

Silicon-based nanoparticles are ideally suited for use as biomedical imaging agents due to their biocompatibility, biodegradability, and simple surface chemistry that facilitates drug loading and targeting. A method of hyperpolarizing silicon particles using dynamic nuclear polarization, which increases magnetic resonance imaging signals by several orders-of-magnitude through enhanced nuclear spin alignment, has recently been developed to allow silicon particles to function as contrast agents for in vivo magnetic resonance imaging. The enhanced spin polarization of silicon lasts significantly longer than other hyperpolarized agents (tens of minutes, wherea

Real-Time MRI-Guided Catheter Tracking Using Hyperpolarized Silicon Particles

Visualizing the movement of angiocatheters during endovascular interventions is typically accomplished using x-ray fluoroscopy. There are many potential advantages to developing magnetic resonance imaging-based approaches that will allow three-dimensional imaging of the tissue/vasculature interface while monitoring other physiologically-relevant criteria, without exposing the patient or clinician team to ionizing radiation. Here we introduce a proof-of-concept development of a magnetic resonance imaging-guided catheter tracking method that utilizes hyperpolarized silicon particles. The increased signal of the silicon particles is generated via low-temperature, solid-state dynamic nuclear polarization, and the particles retain their enhanced signal for ?40?minutes—allowing imaging experiments over extended time durations. The particles are affixed to the tip of standard medical-grade catheters and are used to track passage under set distal and temporal points in phantoms and live mouse models. With continued development, this method has the potential to supplement x-ray fluoroscopy and other MRI-guided catheter tracking methods as a zero-background, positive contrast agent that does not require ionizing radiation

Post-Acquisition Hyperpolarized 29Silicon MR Image Processing for Visualization of Colorectal Lesions Using a User-Friendly Graphical Interface

Medical imaging devices often use automated processing that creates and displays a self-normalized image. When improperly executed, normalization can misrepresent information or result in an inaccurate analysis. In the case of diagnostic imaging, a false positive in the absence of disease, or a negative finding when disease is present, can produce a detrimental experience for the patient and diminish their health prospects and prognosis. In many clinical settings, a medical technical specialist is trained to operate an imaging device without sufficient background information or understanding of the fundamental theory and processes involved in image creation and signal processing. Here, we describe a user-friendly image processing algorithm that mitigates user bias and allows for true signal to be distinguished from background. For proof-of-principle, we used antibody-targeted molecular imaging of colorectal cancer (CRC) in a mouse model, expressing human MUC1 at tumor sites. Lesion detection was performed using targeted magnetic resonance imaging (MRI) of hyperpolarized silicon particles. Resulting images containing high background and artifacts were then subjected to individualized image post-processing and comparative analysis. Post-acquisition image processing allowed for co-registration of the targeted silicon signal with the anatomical proton magnetic resonance (MR) image. This new methodology allows users to calibrate a set of images, acquired with MRI, and reliably locate CRC tumors in the lower gastrointestinal tract of living mice. The method is expected to be generally useful for distinguishing true signal from background for other cancer types, improving the reliability of diagnostic MRI

Porosity Engineering towards Nitrogen-Rich Carbon Host Enables Ultrahigh Capacity Sulfur Cathode for Room Temperature Potassium–Sulfur Batteries

Potassium–sulfur batteries (KSBs) are regarded as a promising large-scale energy storage technology, owing to the high theoretical specific capacity and intrinsically low cost. However, the commercialization of KSBs is hampered by the low sulfur utilization and notorious shuttle effect. Herein, we employ a porosity engineering strategy to design nitrogen-rich carbon foam as an efficient sulfur host. The tremendous micropores magnify the chemical interaction between sulfur species and the polar nitrogen functionalities decorated carbon surface, which significantly improve the sulfur utilization and conversion. Meanwhile, the abundant mesopores provide ample spaces, accommodating the large volume changes of sulfur upon reversible potassation. Resultantly, the constructed sulfur cathode delivers an ultrahigh initial reversible capacity of 1470 mAh g−1 (87.76% of theoretical capacity) and a superior rate capacity of 560 mAh g−1 at 2 C. Reaching the K2S phase in potassiation is the essential reason for obtaining the ultrahigh capacity. Nonetheless, systematic kinetics analyses demonstrate that the K2S involved depotassiation deteriorates the charge kinetics. The density functional theory (DFT) calculation revealed that the nitrogen-rich micropore surface facilitated the sulfur reduction for K2S but created a higher energy barrier for the K2S decomposition, which explained the discrepancy in kinetics modification effect produced by the porosity engineering

A long-term water quality prediction model for marine ranch based on time-graph convolutional neural network

Water quality prediction is important for maintaining water stability and control in marine environments. However, water quality parameters are affected by complex environmental factors.Marine time series data exhibit distribution shift and nonstationarity problems, owing to environmental heterogeneity.It is still difficult to obtain the spatial and time dependence of time series data with existing models and the model prediction accuracy cannot be guaranteed. Therefore, this paper proposes a graph-based convolutional neural network model, allowing networks and sequences to interact smoothly. The Time-graph convolutional fusion network(T-GCFN) consists of a graph convolutional fusion network(GCFN) and Time-pyramidal fusion attention(T-PFA). To obtain the spatial dependence of the original sequence, the original sequence is first decomposed into three subsequences by STL, and then the GCFN obtains the original sequence and trinomial subsequence through a multilayer T-GCN.Internal topology information is also obtained. Second, to eliminate the distribution differences between the training and test sets, the T-PFA is weakened using RevIN.To address the distribution shift problem of the sequence and the nonstationarity problem of the destationarized attention attenuation sequence, a higher weight is assigned to the sequence. Finally, depending on the long and short time series of the obtained sequence, the subsequence is downsampled by cross-learning, and the local features are extracted. Experiments on dissolved oxygen, salinity and temperature at six marine ranches on the Shandong peninsula were carried out using the T-GCFN, and the results were compared with those of other deep learning models. The experimental results show that the T-GCFN has better prediction performance and can achieve high-precision predictions of ocean chemistry parameters in the next three days

Hyperpolarization of Silicon Nanoparticles with TEMPO Radicals

Silicon-based particles can be hyperpolarized via dynamic nuclear polarization to enhance ²⁹Si magnetic resonance signals. Application of this technique to nanoscale silicon particles has been limited because of the low signal enhancements achieved; it is hypothesized that this is due to the low number of endogenous electronic defects inherent to the particles. We introduce a method of incorporating exogenous radicals into silicon nanoparticle suspensions in order to improve the hyperpolarization of ²⁹Si nuclear spins to levels sufficient for in vivo MR imaging. Calibration of radical concentrations and polarization times are reported for a variety of silicon particle sizes (30–200 nm in diameter), with optimal radical concentrations of 30–60 mM. Addition of the radical slightly affects the <i>T</i>₁ relaxation of the nanoparticles; however, these losses in <i>T</i>₁ are overcome by the overall improvement in ²⁹Si magnetization. With optimal amounts of the added radical, ²⁹Si <i>T</i>₁ times are ∼20 min, and MR images in phantoms can be achieved over an hour after hyperpolarization. Co-registered ¹H/²⁹Si MR imaging of nanoparticles administered to a mouse model is also presented