Homo-junction bottom-gate amorphous In-Ga-Zn-O TFTs with metal induced source /drain regions

A fabrication process for homo-junction bottom-gate (HJBG) amorphous In–Ga–Zn–O (a-IGZO) thin-film transistors (TFTs) is proposed, in which the a-IGZO section as source/drain (S/D) region is induced to a low resistance state by coating a thin metal Al film and then performing a thermal annealing in oxygen, and that as channel region is protected from back etching by depositing and patterning a protective layer. Experimental results show that with a 5 nm Al film and a 200 ºC annealing, the sheet resistance of the S/D a-IGZO is 803 Ω/□ and keeps stable during subsequent thermal treatment. In addition, the annealing generated thin Al2O3 film contributes to improve the thermal stability and ambient atmosphere immunity of the fabricated HJBG TFTs. Please click Additional Files below to see the full abstract

Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. I. Weighted Thermodynamics Perturbation

Free energy profile (FE Profile) is an essential quantity for the estimation of reaction rate and the validation of reaction mechanism. For chemical reactions in condensed phase or enzymatic reactions, the computation of FE profile at ab initio (ai) quantum mechanical/molecular mechanics (QM/MM) level is still far too expensive. Semiempirical (SE) method can be hundreds or thousands of times faster than the ai methods. However, the accuracy of SE methods is often unsatisfactory, due to the approximations that have been adopted in these methods. In this work, we proposed a new method termed MBAR+wTP, in which the ai QM/MM free energy profile is computed by a weighted thermodynamic perturbation (TP) correction to the SE profile generated by the multistate Bennett acceptance ratio (MBAR) analysis of the trajectories from umbrella samplings (US). The weight factors used in the TP calculations are a byproduct of the MBAR analysis in the post-processing of the US trajectories, which are often discarded after the free energy calculations. The results show that this approach can enhance the efficiency of ai FE profile calculations by several orders of magnitude

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of cancer-associated deaths. In recent years, significant progress has been achieved in basic and clinical research concerning the epidermal growth factor receptor (EGFR), and the treatment of lung adenocarcinoma has also entered a new era of individualized, targeted therapies. However, the detection of lung adenocarcinoma is usually invasive. 18F-FDG PET/CT can be used as a noninvasive molecular imaging approach, and radiomics can acquire high-throughput data from standard images. These methods play an increasingly prominent role in diagnosing and treating cancers. Herein, we reviewed the progress in applying 18F-FDG PET/CT and radiomics in lung adenocarcinoma clinical research and how these data are analyzed via traditional statistics, machine learning, and deep learning to predict EGFR mutation status, all of which achieved satisfactory results. Traditional statistics extract features effectively, machine learning achieves higher accuracy with complex algorithms, and deep learning obtains significant results through end-to-end methods. Future research should combine these methods to achieve more accurate predictions, providing reliable evidence for the precision treatment of lung adenocarcinoma. At the same time, facing challenges such as data insufficiency and high algorithm complexity, future researchers must continuously explore and optimize to better apply to clinical practice

Surface analytical investigation on organometal triiodide perovskite

In a little over a year, there has been an unexpected breakthrough and rapid evolution of highly efficient solid-state hybrid solar cells based on organometal trihalide perovskite materials. This technology has the potential to produce solar cells with the very highest efficiencies while retaining the very lowest cost. The authors have measured the electronic density of states of CH3NH3PbI3 using ultraviolet photoemission spectroscopy (UPS), inverse photoemission spectroscopy (IPES), and x-ray photoemission spectroscopy (XPS). The valence band maximum and conduction band minimum positions are obtained from the UPS and IPES spectra, respectively, by linear extrapolation of the leading edges. The authors investigate the Au/perovskite and C60/perovskite interfaces by UPS and XPS. An interface dipole of 0.1 eV is observed at Au/perovskite interface. The energy levels of perovskite shift upward by ca.0.4 eV with Au coverage of 64Å upon it, resulting in band bending, hence a built-in field in perovskite that encourages hole transport to the interface. The XPS results show a strong initial shift of core levels to lower binding energy in the perovskite, which indicates that electrons transfer from the perovskite film to fullerene molecules. Further deposition of fullerene forms C60 solid, accompanied by the reduction of the electron transfer. The strongest electron transfer happened at 1/4 monolayer of fullerene

Electronic structure evolution of fullerene on CH\u3csub\u3e3\u3c/sub\u3eNH\u3csub\u3e3\u3c/sub\u3ePbI\u3csub\u3e3\u3c/sub\u3e

The thickness dependence of fullerene on CH3NH3PbI3 perovskite film surface has been investigated by using ultraviolet photoemission spectroscopy (UPS), X-ray photoemission spectroscopy (XPS), and inverse photoemission spectroscopy (IPES). The lowest unoccupied molecular orbital and highest occupied molecular orbital (HOMO) can be observed directly with IPES and UPS. It is observed that the HOMO level in fullerene shifts to lower binding energy. The XPS results show a strong initial shift of core levels to lower binding energy in the perovskite, which indicates that electrons transfer from the perovskite film to fullerene molecules. Further deposition of fullerene forms C60 solid, accompanied by the reduction of the electron transfer. The strongest electron transfer happened at 1/4 monolayer of fullerene

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing machine-learning-assisted free energy simulation of solution-phase and enzyme reactions at the ab initio quantum-mechanical/molecular-mechanical (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy and forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (ΔMLP) is trained to reproduce the differences between the ai-QM/MM and semiempirical (se) QM/MM energies and forces. To account for the effect of the condensed-phase environment in both MLP and ΔMLP, the DeePMD representation of a molecular system is extended to incorporate the external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and ΔMLP reproduce the ai-QM/MM energy and forces with errors that on average are less than 1.0 kcal/mol and 1.0 kcal mol–1 Å–1, respectively, for representative configurations along the reaction pathway. For both reactions, MLP/ΔMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results at only a fraction of the computational cost

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216