Intrinsic Defect Limit to the Growth of Orthorhombic HfO2 and (Hf,Zr)O2 with Strong Ferroelectricity: First-Principles Insights

It is believed that promoting the fraction of ferroelectric orthorhombic phase (o-phase) through O-poor growth conditions can increase the spontaneous polarization of HfO₂ and (Hf,Zr)O₂ thin films. However, the first-principles calculations show that the growth may be limited by the easy formation of point defects in the orthorhombic and tetragonal phases of HfO₂, ZrO₂, and (Hf,Zr)O₂. Their dominant defects, O interstitial (O_i) under O-rich conditions and O vacancy (V_O) under O-poor condition, have low formation energies and quite high density (10¹⁶–10¹⁹ cm⁻³ for 800–1400 K growth temperature). Especially, O_i has negative formation energy in tetragonal HfO₂ under O-rich condition, causing non-stoichiometry and limiting the crystalline-seed formation during o-phase growth. High-density defects can cause disordering of dipole moments and increase leakage current, both diminishing the polarization. These results explain the experimental puzzle that the measured polarization is much lower than the ideal value even in O-poor thin films and highlight that controlling defects is as important as promoting the o-phase fraction for enhancing ferroelectricity. The O-intermediate condition (average of O-rich and O-poor conditions) and low growth temperature are proposed for fabricating HfO₂ and (Hf,Zr)O₂ with fewer defects, lower leakage current, and stronger ferroelectricity, which challenges the belief that O-poor condition is optimal.     

硫化矿石自燃灾害预警的RBF神经网络方法

硫化矿石自燃灾害预警可以快速确定灾害预警等级，进而为灾害防控提供决策以减少矿山损失。通过深入分析硫化矿石自燃典型案例，按照预警指标选取原则，从矿山生产人员、硫化矿石自燃倾向性、环境条件、管理水平等4个方面构建硫化矿石自燃灾害预警系统指标体系。运用RBF预警模型对硫化矿石自燃灾害预警等级进行预测，采用所选的21组样本数据完成了RBF神经网络的学习与训练。应用学习好的预警模型对江西某高硫矿山的硫化矿石自燃灾害预警等级进行预测。结果表明：该矿山硫化矿石自燃灾害预警等级为III级，即自燃危险性一般，与该采场的实际状况相一致。该模型具有很强的实用性，能应用于硫化矿石自燃灾害预警等级的预测。     

三软煤层综采工作面防治煤层自然发火技术研究

针对超化煤矿22011A三软煤层工作面在采掘接替计划安排中需长期停产存在煤层自然发火隐患的问题，提出了多种防治煤层自然发火技术方案，并从每种方案的经济性、安全性、操作性等方面进行论证、比较，择优采取工作面正常通风情况下的防治煤层自然发火的技术方案，确保综采工作面停采期间的安全性，取得了显著的经济效益，对三软煤层自然发火防治工作具有重要的指导意义。     

四川省植被覆盖时空演变及未来变化趋势分析

四川省地处长江上游,是长江流域重要的生态屏障;解析该区域植被覆盖的时空演变特征,对长江上游的生态环境修护与治理具有重要意义。基于长时间序列的MODIS NDVI数据,解析2000~2016年间四川省植被的空间分布格局与时间变化特征;采用趋势分析法和Hurst指数,预测未来植被的变化趋势及持续性。结果表明:(1)四川省NDVI多年平均值为0.50,植被覆盖整体上呈现川东高于川西的空间分布特征;(2)2000~2016年间,四川省的NDVI值在0.48至0.53之间波动,整体呈上升趋势,增长率为0.002 5/a;(3)植被覆盖度在未来变化将呈现改善大于退化的趋势;植被持续性改善的面积大于持续性退化的面积。     

浸水过程对长焰煤自燃特性的影响

为揭示长期浸水长焰煤的自燃特性及影响机制,实验研究了长焰煤原始煤样和长期浸水风干煤样的低温氧化特性,分析了长期浸水对煤微观结构、氧化升温过程及活化能等方面的影响规律。研究结果表明:长期被水浸泡煤样的表面孔隙结构更发达,平均孔径、介孔孔容和微孔孔容都有不同程度的增大;同时,浸水煤样表面的部分有机物和无机物会溶解在水中,煤中自由基浓度增加,基团分布与原煤相比存在明显变化;与原煤样相比,经过90,180 d浸水过程后的煤体,低温氧化过程的气体产生量和产生速率更高,交叉点温度由原煤的160.9℃降低至157,151.5℃,活化能分别降低了3.84,4.18 k J/mol,表现出更高的自燃倾向性。研究结果可为西部浅埋藏近距离煤层群开采上覆采空区长期浸水煤的自燃防治提供借鉴。     

羟基(—OH)对煤自燃侧链活性基团氧化反应特性的影响

针对煤结构及其氧化反应机理不明等问题,以羟基(—OH)和煤自燃侧链活性基团—OCH,—CHOHCH 3和—OCH 3为研究对象,采用密度泛函理论(DFT)的B3LYP-311G(d,p)方法,构建出了羟基(—OH)处于侧链活性结构邻位的小分子结构模型。基于前线轨道理论和量子化学理论,采用Gaussian 16软件对小分子模型的静电势、前线轨道的能级和电荷分布及煤氧复合反应过程中的热力学参数进行了模拟计算,探究了侧链活性基团的低温氧化特性和羟基(—OH)对其的影响。计算结果显示,在侧链活性结构中,氢原子周边呈强正电势,为亲核反应活性位点,而氧原子附近呈强负电势,为亲电反应活性位点。当羟基(—OH)处于侧链活性基团邻位时,会削弱侧链活性基团的亲电反应能力,增加—CHO和—CHOHCH 3的亲核反应能力,而使—OCH 3的亲核反应能力消失;通过分析各活性基团最高占据轨道(HOMO:Highest Occupied Molecular Orbital)和最低未占轨道(LUMO:Lowest Unoccupied Molecular Orbital)可知,侧链活性基团的稳定性与其前线轨道的成键能力并不一致,而活性基团与氧气发生复合反应的难易程度主要取决于该基团前线轨道中LUMO的成键能力,成键能力越强,复合反应越容易发生;由于羟基(—OH)改变了侧链活性基团前线轨道上的电子特性,故当其与侧链基团共存时,会使—CHO和—CHOHCH 3与氧气的复合反应更容易发生,而使—OCH 3与氧气的复合由自发的放热反应转变为非自发的吸热反应。该研究成果可为揭示煤自燃微观作用机理和研发煤自燃新型高效阻化材料提供参考。     

Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture

Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring a substantial labeling effort, both of which are scarce in precision agriculture. Additional design efforts are required to achieve commercially viable performance levels under varying environmental conditions and crop growth stages. In this paper, we explore the role of knowledge transfer between deep‐learning‐based classifiers for different crop types, with the goal of reducing the retraining time and labeling efforts required for a new crop. We examine the classification performance on three datasets with different crop types and containing a variety of weeds and compare the performance and retraining efforts required when using data labeled at pixel level with partially labeled data obtained through a less time‐consuming procedure of annotating the segmentation output. We show that transfer learning between different crop types is possible and reduces training times for up to 80%. Furthermore, we show that even when the data used for retraining are imperfectly annotated, the classification performance is within 2% of that of networks trained with laboriously annotated pixel‐precision data.     

珲春地区高瓦斯矿井煤自然发火标志气体研究

为了探究珲春地区高瓦斯矿井煤自然发火情况，选取该地区板石煤矿22、23a和八连城煤矿18#、26#共4个煤层进行程序升温特性实验，分析了CO及烃类气体产生量随温度的变化规律，优选自然发火标志气体，测算煤自燃临界温度。结果表明，板石22、23a和八连城18#、26#四个煤层的自燃临界温度分别为101.0℃、97.6℃、121.0℃、169.1℃。CO和C2H4的初现温度大约在30℃与80～120℃，且产生量随温度单调递增，可作为煤自燃预测预报的主要参考指标|而同时，为了保证检测的全面与准确，还可以将规律性良好的其他烃类气体、烯烷比和链烷比进行辅助参考。     

井下均压通风防灭火分析

以井下均压通风防灭火为对象开展探究。结合具体工程实际,在分析煤层自燃风险性的基础上,探究了均压通风防灭火的原理,并总结了均压通风防灭火技术的实践应用。结果表明,均压通风防灭火技术的应用实现了对采空区遗煤自燃的有效防治,对提升矿井作业安全性效果显著。