Diameter-dependent ultra-high thermoelectric performance of ZnO nanowires

Zinc oxide(ZnO)shows great potential in electronics,but its large intrinsic thermal conductivity limits its thermoelectric applications.In this work,we explore the significant carrier transport capacity and diameter-dependent thermoelectric characteristics of wurtzite-ZnO(0001)nanowires based on first-principles and molecular dynamics simulations.Under the synergistic effect of band degeneracy and weak phonon-electron scattering,P-type(ZnO)_(73) nanowires achieve an ultrahigh power factor above 1500μW·cm^(-1)·K^(-2)over a wide temperature range.The lattice thermal conductivity and carrier transport properties of ZnO nanowires exhibit a strong diameter size dependence.When the ZnO nanowire diameter exceeds 12.72A,the carrier transport properties increase significantly,while the thermal conductivity shows a slight increase with the diameter size,resulting in a ZT value of up to 6.4 at 700 K for P-type(ZnO)_(73).For the first time,the size effect is also illustrated by introducing two geometrical configurations of the ZnO nanowires.This work theoretically depicts the size optimization strategy for the thermoelectric conversion of ZnO nanowires.

Ion–Electron Coupling Enables Ionic Thermoelectric Material with New Operation Mode and High Energy Density

Ionic thermoelectrics(i-TE) possesses great potential in powering distributed electronics because it can generate thermopower up to tens of millivolts per Kelvin. However,as ions cannot enter external circuit, the utilization of i-TE is currently based on capacitive charge/discharge, which results in discontinuous working mode and low energy density. Here,we introduce an ion–electron thermoelectric synergistic(IETS)effect by utilizing an ion–electron conductor. Electrons/holes can drift under the electric field generated by thermodiffusion of ions, thus converting the ionic current into electrical current that can pass through the external circuit. Due to the IETS effect, i-TE is able to operate continuously for over 3000 min.Moreover, our i-TE exhibits a thermopower of 32.7 mV K^(-1) and an energy density of 553.9 J m^(-2), which is more than 6.9 times of the highest reported value. Consequently, direct powering of electronics is achieved with i-TE. This work provides a novel strategy for the design of high-performance i-TE materials.

Preparation and thermoelectric properties of ternary rare earth sulfide γ-Ce_(3–x)Eu_xS_4

The effect of Eu-substitution on the density and thermoelectric properties of ternary sulfide Ce3-xEuxS4 （0≤x≤0.8） compacts was investigated. Ce3-xEuxS4 powders were prepared via the sulfurization of the oxide using CS2 gas at 1473 K. The pressureless sintered Ce3-xEuxS4 compacts in the atmosphere were crystallized in the T-phase. The density of the Ce3-xEuxS4 compacts increased with the increasing of Eu-substitution. Eu-substitution yielded a higher Seebeck coefficient and lower electrical resistivity. The highest value of the thermoelectric power factor of 1.41×10^-4 W/K^2m was obtained for the Ce2.2Eu0.8S4 compact at 673 K. It indicated that Eu-substitution was effective for improving thermoelectric properties of Ce3-xEuxS4.

WEAK SOLUTION TO THE INCOMPRESSIBLE VISCOUS FLUID AND A THERMOELASTIC PLATE INTERACTION PROBLEM IN 3D

In this paper we deal with a nonlinear interaction problem between an incompressible viscous fluid and a nonlinear thermoelastic plate.The nonlinearity in the plate equation corresponds to nonlinear elastic force in various physically relevant semilinear and quasilinear plate models.We prove the existence of a weak solution for this problem by constructing a hybrid approximation scheme that,via operator splitting,decouples the system into two sub-problems,one piece-wise stationary for the fluid and one time-continuous and in a finite basis for the structure.To prove the convergence of the approximate quasilinear elastic force,we develop a compensated compactness method that relies on the maximal monotonicity property of this nonlinear function.

铁碳内电解耦合蕹菜(Ipomoea aquatica)对黑臭污水脱氮效果的研究

构建了铁碳内电解耦合蕹菜技术体系,用于原位净化河道黑臭污水,采用单因素模拟实验,探究耦合体系植株密度、铁碳填料用量和陶粒用量对黑臭污水脱氮效果的影响规律.结果表明,在植株密度为80株/m 2、铁碳填料用量为18 g/L和陶粒用量为52 g/L的适宜组合下,处理22 d后,TN和NH4^+-N的去除率分别为74.1%和99.6%,其质量浓度分别稳定在(13.65±1.24)mg/L和(0.18±0.04)mg/L.水体微生物丰度和多样性有了显著提高,主要优势细菌门是Proteobacteria、Firmicutes和Bacteroidetes,主要优势细菌属为Pseudomonas、Escherichia-Shigella和Diaphorobacter,微生物群落演化更适宜脱氮.耦合体系通过协同作用净化水质,其作用过程包括:铁碳内电解产生质子[H]和Fe^2+提供电子促进自养反硝化、蕹菜根际泌氧促进微生物硝化、陶粒生物膜与根际微生物之间的硝化反硝化作用、陶粒吸附氮.该研究为采用铁碳内电解耦合挺水植物净化河道黑臭污水提供了依据.

Key progresses of MOE key laboratory of macromolecular synthesis and functionalization in 2022

In 2022,The MOE Key Laboratory of Macromolecular Synthesis and Functionalization in Zhejiang University had achieved several important results.First,a series of well-defined dinuclear organoboron catalysts were developed to precisely control the enchainment of ether and carbonate segments during the copolymerization of CO_(2)and epoxides.Second,polyester had been synthesized through cationic copolymerization of cyclic anhydride.Third,ring-opening polymerization of carbon dioxide based valerolactone had been achieved,revealing the prospect of 3-ethylidene-6-vinyltetrahydro-2H-pyran-2-one(EVL)in utilizing CO_(2)and synthesizing functional polymers.Fourth,machine learning methods have been applied to biomaterial research,enabling high-throughput screening of functional biomaterial surfaces for implantable devices,and searching for potent antimicrobial peptides in whole combinatorial peptide libraries.Fifth,methods of characterization of biomacromolecule RNA transcription and manipulation of nucleoside modification were developed.Sixth,artificial enzymes-armed Bifidobacterium Longum probiotics were established to tune down gut inflammation.Seventh,three-dimensional(3D)printing technologies were used to engineer tough supramolecular hydrogels.Eighth,hydroplastic foaming graphene frameworks for acoustic and conductive polymer composites were provided for application.Ninth,aggregate photophysics about the nature of through-space interactions(TSIs)and manipulating their strength in small molecules with non-conjugated structure had been elucidated.Tenth,the forming mechanism of a newfound nested texture in poly(L-lactic acid)(PLLA)spherulitic films had been revealed.Finally,the isotropically dyeing mechanism of KDP single crystals grown from hydrogels have been explored.The related works are reviewed in this paper.

Ultrafast Response and Threshold Adjustable Intelligent Thermoelectric Systems for Next‑Generation Self‑Powered Remote IoT Fire Warning

Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.

自溯源型MOEMS加速度计谐振子设计仿真研究

MOEMS加速度计是加速度传感器未来的发展趋势之一,光学位移检测手段是决定测量精度的核心因素,与之配套的谐振子设计、匹配关系是充分发挥其性能的关键要素。自溯源光栅干涉仪是一种超精密位移测量方法,具有测量直接溯源、精度高、小型化等优势,非常契合MOEMS加速度计的位移测量需求。结合自溯源光栅干涉仪特性,计算、设计并仿真了自溯源型MOEMS加速度计谐振子。基于谐振子力学理论模型,计算了谐振子刚度和固有频率,采用COMSOL软件仿真了谐振子谐振模态、不同轴向的灵敏度与应力分布,设计了位移灵敏度高达10.01μm/g,同时具有超低横向串扰的谐振子,对直接溯源型高精度加速度测量方案的技术研发与性能优化具有重要意义。

Multiple control of thermoelectric dual-function metamaterials

Thermal metamaterials based on transformation theory offer a practical design for controlling heat flow by engineering spatial distributions of material parameters,implementing interesting functions such as cloaking,concentrating,and rotating.However,most existing designs are limited to serving a single target function within a given physical domain.Here,we analytically prove the form invariance of thermoelectric(TE)governing equations,ensuring precise controls of the thermal flux and electric current.Then,we propose a dual‐function metamaterial that can concentrate(or cloak)and rotate the TE field simultaneously.In addition,we introduce two practical control methods to realize corresponding functions:one is a temperature‐switching TE rotating concentrator cloak that can switch between cloaking and concentrating;the other is an electrically controlled TE rotating concentrator that can handle the temperature field precisely by adjusting external voltages.The theoretical predictions and finite‐element simulations agree well with each other.This work provides a unified framework for manipulating the direction and density of theTE field simultaneously and may contribute to the study of thermal management,such as thermal rectification and thermal diodes.

Key progresses of MOE key laboratory of macromolecular synthesis and functionalization in 2021

In 2021,The MOE Key Laboratory of Macromolecular Synthesis and Functionalization in Zhejiang University had achieved several important results.First,a series of versatile organoboron catalysts were synthesized for ring-opening(co)polymerizations.Second,a catalyst-free polycondensation mechanism was proposed for the production of polyesters with high molecular weights.Third,a co-assembly method that can fabricate films and coatings with controllable structures and properties on various substrates was demonstrated,providing a platform for the construction of novel surface coatings.Forth,facile methods for producing high-productivity poly(propylene carbonate)and semicrystalline polyester have been discovered.And linear non-conjugated polyesters exhibiting yellow-green clusteroluminescence were developed for the first time.Fifth,a supramolecular prodrug nano-assembly strategy has been developed for reactive nitrogen species potentiated chemotherapy.Sixth,a series of tough and stiff supramolecular hydrogels with shape memory properties have been used for information encryption.Seventh,reversible fusion and fission of wet-spun graphene oxide fibers has been successfully achieved.Eighth,three non-conjugated polypeptides were synthesized and the mechanism of clusteroluminescence was studied.Ninth,a series of conducting covalent organic frameworks with high electrical conductivity and carrier mobility have been used as high-performance chemiresistor,electrocatalyst,and organic field-effect transistor.Tenth,the exploration of non-fused electron acceptors,and their photostable mechanism are exemplified for developing high-performance,low-cost and eco-friendly polymer solar cells.Finally,gel-grown long-range ordering bulk-heterojunctions has achieved improved X-ray detector performance.

ChatGPT的工作原理、关键技术及未来发展趋势

ChatGPT是自然语言处理领域的一项重要技术突破,专注于对话生成任务,在多种任务中表现出卓越的性能。主要探讨ChatGPT的演变历程、关键技术,并分析了其未来可能的发展方向。首先,介绍了ChatGPT的模型架构和技术演进过程。随后,重点讨论了ChatGPT的关键技术,包括提示学习与指令微调、思维链、人类反馈强化学习。然后,分析了由于基于概率生成原理所造成的固有局限,包括事实性错误、垂直领域深度性弱、潜在的恶意应用风险、可解释性及模型实时性差等。最后,探讨了其在典型应用中存在的问题和相应的解决途径,包括在训练评估过程中考虑道德和安全性因素,以降低潜在风险;结合外部专家知识和迁移学习,以提高模型对特定领域的理解能力,更好地适应特定任务场景;引入多模态数据,以提高模型信息理解能力,增强模型通用性和泛化性。通过对ChatGPT模型框架、技术演变与关键技术的分析,为深入理解ChatGPT提供帮助;结合原理分析其固有缺陷,并结合实际应用中存在的问题,挖掘未来可能的研究方向,为自然语言处理领域的深入研究提供有益参考。

机器学习方法在盾构隧道工程中的应用研究现状与展望

随着盾构隧道工程信息化水平的提升,隧道掘进设备作业过程监测技术日益完善,记录的工程数据蕴含了掘进设备内部信息及其与外部地层的相互作用关系。机器学习因其数据分析能力强,无需先验的理论公式和专家知识,相较于传统的建模统计分析方法具有更大的应用空间。通过机器学习方法对收集的信息与数据进行深度挖掘并分析其内在联系,有助于提升盾构隧道工程建设的效率和安全保障水平。简述机器学习方法的基本原理,总结和分析机器学习方法在盾构工程中的应用研究状况,综述基于机器学习的盾构设备状态分析、盾构设备性能预测、围岩参数反演、地表变形预测和隧道病害诊断等5个方面的进展,并分析当前研究的不足。最后,分析盾构隧道工程向智能化方向发展需重点攻克的难题。

深层、超深层定向钻井中若干基础研究进展与展望

深层、超深层定向钻井具有“垂深大与水平延伸远”的双重特征,受到复杂地层、高温高压、超长裸眼等多重因素约束,其安全高效作业面临着更大的全方位技术挑战。为此,着眼于深层、超深层定向钻井的提速提效问题,系统总结了定向钻井的发展概况与技术特点,选取了深层、超深层定向钻井中力学方面的几个重要基础问题,分析了国内外专家学者的相关研究进展和最新研究成果,最后展望了深层、超深层定向钻井基础理论研究发展趋势并提出相关建议。研究结果表明:①大小偏差融合控制算法兼顾了井眼轨迹的控制精度、光滑度等多目标约束,适应于深层、超深层条件下井眼轨迹实时控制要求;②合理优化振动减阻工具个数、安放位置及其激励力幅值,可显著降低井下管柱摩阻,并有效提高机械钻速;③基于误差补偿机制的机械钻速融合预测模型既保留了机理模型的可解释性,又具有较高的预测精度;④套管复合磨损预测模型突破了经典“单月牙”模式的局限性,实现了复合模式下套管磨损形状与深度的同步预测。结论认为,深层、超深层定向井和水平井是未来油气井工程的重要发展方向之一,需要加强多因素耦合机理、钻井延伸极限、机理与数据融合驱动等方面的基础研究,以推动复杂油气井工程基础理论的创新与发展,为深层、超深层钻井工程技术进步提供必要的基础理论支撑。

元地球与数字孪生:思想突破、技术变革与范式转换

数字孪生在航天、工业制造领域已应用了20多年,但引入海洋科学还是首次。通过数字孪生技术,实现真实地球与虚拟地球的融合,构建一个真实地球与数字地球的虚实共同体,这里称为“元地球”。本文介绍了元地球与早期提出的数字地球、虚拟地球、玻璃地球、智慧地球的本质区别,进而突出元地球理念或思想上的巨大突破。基于现今元宇宙BIGANT技术体系,构架跨越地球各圈层的实时、全天候、立体观测感知系统,打通地球系统各圈层动力学模拟隔阂,实现超越现今地球,再现深时地球,实现时空穿越,从而集数字地球、虚拟地球、玻璃地球、智慧地球、现今地球、深时地球的特性于一个共同体,这个深时的虚实共同体就是元地球。这一理念必将催生新的技术范式变革,进而超越现实地球、虚拟地球,开启人类认识地球、探测地球、开发地球的全新方式。在实现研究范式转换的同时,推动元地球的多场景应用,这也必将催生未来的万亿新产业。

陕北靖边高铬地下水中硝酸根分布及来源

天然高铬地下水通常含有较高浓度的硝酸根,然而高铬地下水中硝酸根来源及其联系却并不清楚。本文以陕北黄土高原靖边西南地区的高铬地下水为研究对象,采集了不同深度的地下水和沉积物样品,并测试了地下水样品中的溶解Cr、主要阴阳离子、δ^(18)O、δD、δ^(18)O-NO_(3)、δ^(15)N-NO_(3)等以及沉积物的主要组分和可溶性组分。研究结果表明,研究区地下水的水化学组分主要受水文地质条件的影响。第四系黄土潜水水化学类型主要为HCO_(3)-Na型和HCO_(3)-Ca-Mg型;白垩系环河组、洛河组砂岩承压水水化学类型复杂,主要为HCO_(3)-SO_(4)-Cl-Na-Mg型、HCO_(3)-SO_(4)-Na-Mg型、SO_(4)-Cl-Na-Mg型,地下水处于偏碱性、氧化的环境,具有较高的可溶盐含量。潜水的水化学组分主要来自含水层中硅酸盐风化;承压水水化学组分主要来源于蒸发盐的溶解。垂向上,承压水中硝酸根的平均浓度高于潜水和地表水;地下水硝酸根浓度超标率在研究区从东北到西南呈现高-低-高的趋势;沉积物中可溶性硝酸根与地下水样品在深度上具有相似的变化规律,表明地下水硝酸根主要来源于沉积物。δ^(18)O-NO_(3)和δ^(15)N-NO_(3)结果表明,硝化反应是研究区氮素循环转化的主要过程。在偏碱性氧化性地下水环境中,受溶解氧、硝酸根和硝化反应等多种因素的共同作用,铬趋于从岩石中氧化溶解,迁移进入地下水中。

微波视觉与SAR图像智能解译

高分辨率雷达成像技术和人工智能、大数据技术的快速发展,有力促进了雷达图像智能解译技术的进步。由于雷达传感器本身的特殊性和电磁散射成像物理的复杂性,雷达图像的解译缺乏光学图像的直观性,准确迅速识别分类的需求对雷达图像解译提出了迫切的挑战。在借鉴人脑光视觉感知机理和计算机视觉图像处理相关技术基础上,进一步融合电磁散射物理规律及其雷达成像机理,我们提出发展微波域雷达图像解译的“微波视觉”的新交叉领域研究。该文介绍微波视觉的概念与内涵,提出微波视觉认知模型,阐述其基础理论问题与技术路线,最后介绍了作者团队在相关问题上的初步研究进展。

深地工程多维信息感知与智能建造的发展与展望

随着大数据、云计算、人工智能等数字技术的加速演进,各领域智能化、信息化、数字化已成为未来的大势所趋。深地工程作为国家重大战略科技问题,必然面临智能化升级。然而,深部岩体“三高一扰动”的复杂特征给深地工程智能化转型带来严峻的挑战。为实现深地工程与数字技术的高效融合,研究基于“感知-传送-解译-分析-决策”的智能化实践路径,系统回顾了地下工程中智能感知、实时传输、信息解译、数据分析、智能决策等领域的代表性研究进展,并针对性提出了“多感知、快响应、大数据、优方法、精模型、强平台、易推广”的深地工程智能建造发展方向。研究表明:①前沿的深地工程感知技术包括:光纤传感器、MEMS传感器、计算机视觉、自动化机器人等,待数据采集完毕后,通过兼具配置简单、容错能力强、可移动性好等优点的无线通信协议完成数据的实时响应,以实现深地工程监测数据的精准感知与实时传输;②深地工程原位监测技术获取的数据类型主要包括图像、波、点云等,对原始数据解译及分析的模型众多,采用新一代的人工智能技术,如:人工神经网络和深度学习技术,可显著提高解译与分析的效率;③智能决策系统具备高效的学习能力,能够适应复杂环境下的不确定性,通过循环自主学习,以进行决策问题的智能解答。当前,我国深地工程智能建造的政策与产业体系已基本建立,大量智能建造系统已应用于实践。基于此,从智能感知与信息解译、围岩评价及安全评估、围岩控制与动态修复、平台开发及应用推广等4个方面展望了数智化深地工程的发展方向,进而构建了基于多源信息的深地工程围岩稳定性综合评价与分析系统构想。

基于倾角反演的隧道断面变形全方位监测方法

倾角传感器具有体积小、使用方便、测量连续等优点,在隧道变形监测领域有着巨大应用潜力,然而,现有基于倾角传感器的监测方法往往只能得到特定监测点的变形,在测量隧道断面整体变形方面还存在明显不足。为此,提出一种新的基于监测点倾角的隧道断面变形全方位监测方法。基于隧道断面曲线的形状特征,构造隧道分段变形插值函数,根据极坐标下隧道倾角与极径的关系,采用分段解析方法提出隧道倾角-变形数学模型,进一步通过协同变形假定,修正隧道测点极角,得到隧道倾角-变形算法;接着,建立隧道三维数值模型,通过均布荷载、对称非均布荷载和非对称荷载3种典型工况,采用误差分析方法分别研究算法的适用性;最后,通过室内试验进一步验证算法在实际应用中的准确性。研究结果表明:对于铁路隧道典型三心圆断面,推导的倾角-变形算法在均布荷载、对称非均布荷载和非对称荷载这3种典型工况下均具有良好的适应性,变形最大绝对误差均小于1 mm,平均相对误差均小于7%;在室内模型试验中,拱顶沉降监测误差小于8%,水平收敛监测误差小于5%,证明了监测方法的准确性。

基于平纵组合的山区高速公路连续下坡路段行车安全评价方法

受制于地理和经济条件,山区高速公路在建设中不可避免会存在连续下坡路段,其中平纵组合路段对车辆稳定性和安全性提出了更高的要求。为分析山区高速公路连续下坡平纵组合路段的行车安全,利用西南山区高速公路数据,以80 km/h的设计速度,在连续下坡路段的不同位置、不同平纵组合工况构建了驾驶仿真实验。根据驾驶者的心理数据、车辆速度变化数据和横向偏移数据推出综合评价指标;将综合评价指标与平曲线半径和纵坡进行相关性分析;再通过累计频率图划分评价阈值;提出了基于平纵组合的连续下坡路段行车安全评价方法,并依托评价方法提出了连续下坡路段坡顶、坡中和坡底位置的平纵组合设计建议值;并以西南山区某高速公路为例对该评价方法进行了应用与验证。研究结果表明:该方法能为高速公路连续下坡路段的行车安全评价提供有效的参考依据。

井深随钻测量误差校正与井眼位置不确定性计算方法

深井和超深井钻井过程中井下温度高、井内钻具承受的拉力大,导致随钻测量的井深误差较大。为此,考虑不同井深处井内温度、热膨胀系数、钻具轴向力和钻具规格等因素的影响,在测点处对井内钻具分段,结合井下温度随钻测量结果和井内钻具受力分析结果,建立了随钻测量井深的热膨胀校正模型和弹性拉伸校正模型,以及计算热膨胀校正误差限和弹性拉伸校正误差限的模型,并给出了随钻测量井深热膨胀和弹性拉伸校正后的井眼位置不确定性计算方法。实例计算表明,超深井钻井过程中由热膨胀和弹性拉伸导致的井内钻具伸长量可达10 m以上;随钻测量井深进行热膨胀和弹性拉伸校正后,可以显著减小测点垂深误差和误差椭球的大小。研究结果为提高井深随钻测量精度与科学计算井眼位置不确定性提供了理论依据。