Plasmonic coupling effect in Ag nanocap-nanohole pairs for surface-enhanced Raman scattering

journal articleA plasmonic coupling structure composed of Ag nanocap-nanohole pairs was fabricated through a novel and facile method. Both surface-enhanced Raman scattering (SERS) measurements and numerical simulations show that the cap-hole system produces much larger electric field enhancement and SERS signal than the isolated structures, which is due to the plasmonic coupling effect between the gap of the cap and the hole. Additionally, the plasmonic enhancement is sensitive to the gap size, which can be controlled by the Ag layer thickness during the evaporation process. A maximum enhancement factor of 1.1×108 can be obtained with optimized gap size

Parallel Emergence of Rigidity and Collective Motion in a Family of Simulated Glass-Forming Polymer Fluids

The emergence of the solid state in glass-forming materials upon cooling is accompanied by changes in both thermodynamic and viscoelastic properties and by a precipitous drop in fluidity. Here, we investigate changes in basic elastic properties upon cooling in a family of simulated polymer fluids, as characterized by a number of stiffness measures. We show that $\tau_{\alpha}$ can be expressed quantitatively both in terms of measures of the material ``stiffness'', $G_p$ and $\langle u^2 \rangle$, and the extent $L$ of cooperative particle exchange motion in the form of strings, establishing a direct relation between the growth of emergent elasticity and collective motion. Moreover, the macroscopic stiffness parameters, $G_p$, $B$, and $f_{s, q^*}$, can all be expressed quantitatively in terms of the molecular scale stiffness parameter, $k_{\mathrm{B}}T / \langle u^2 \rangle$ with $k_{\mathrm{B}}$ being Boltzmann's constant, and we discuss the thermodynamic scaling of these properties. We also find that $G_p$ is related to the cohesive energy density $\Pi_{\mathrm{CED}}$, pointing to the critical importance of attractive interactions in the elasticity and dynamics of glass-forming liquids. Finally, we discuss fluctuations in the local stiffness parameter as a quantitative measure of elastic heterogeneity and their significance for understanding both the linear and nonlinear elastic properties of glassy materials.Comment: 69 pages, 18 figure

Optical nanolithography with λ/15 resolution using bowtie aperture array

We report optical parallel nanolithography using bowtie apertures with the help of the interferometric-spatial-phase-imaging (ISPI) technique. The ISPI system can detect and control the distance between the bowtie aperture, and photoresist with a resolution of sub-nanometer level. It overcomes the difficulties brought by the light divergence of bowtie apertures. Parallel nanolithography with feature size of 22 ± 5 nm is achieved. This technique combines high resolution, parallel throughput, and low cost, which is promising for practical applications.United States. Defense Advanced Research Projects Agency (Grant N66001-08-1-2037)National Science Foundation (U.S.) (Grant CMMI-1120577

High precision dynamic alignment and gap control for optical near-field nanolithography

The authors demonstrate the use of interferometric-spatial-phase-imaging (ISPI) to control a gap distance of the order of nanometers for parallel optical near-field nanolithography. In optical near-field nanolithography, the distance between the optical mask and the substrate needs to be controlled within tens of nanometers or less. The ISPI technique creates interference fringes from checkerboard gratings fabricated on the optical mask, which are used to determine the gap distance between the mask and the substrate surfaces. The sensitive of this gapping technique can reach 0.15 nm. With the use of ISPI and a dynamic feedback control system, the authors can precisely align the mask and the substrate and keep variation of the gap distance below 6 nm to realize parallel nanolithography. (C) 2013 American Vacuum Society

Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models

The recent success of large language models (LLMs) has shown great potential to develop more powerful conversational recommender systems (CRSs), which rely on natural language conversations to satisfy user needs. In this paper, we embark on an investigation into the utilization of ChatGPT for conversational recommendation, revealing the inadequacy of the existing evaluation protocol. It might over-emphasize the matching with the ground-truth items or utterances generated by human annotators, while neglecting the interactive nature of being a capable CRS. To overcome the limitation, we further propose an interactive Evaluation approach based on LLMs named iEvaLM that harnesses LLM-based user simulators. Our evaluation approach can simulate various interaction scenarios between users and systems. Through the experiments on two publicly available CRS datasets, we demonstrate notable improvements compared to the prevailing evaluation protocol. Furthermore, we emphasize the evaluation of explainability, and ChatGPT showcases persuasive explanation generation for its recommendations. Our study contributes to a deeper comprehension of the untapped potential of LLMs for CRSs and provides a more flexible and easy-to-use evaluation framework for future research endeavors. The codes and data are publicly available at https://github.com/RUCAIBox/iEvaLM-CRS.Comment: Accepted by EMNLP 202

Improving Efficiency of Evaporated Cu 2

A 20 nm Ag coating on Mo back contact was adopted to improve the back contact of evaporated Cu2ZnSnS4 (CZTS) solar cells. The Ag layer helped reduce the thickness of MoS2 which improves fill factor (FF) significantly; additionally, it reduced secondary phases ZnS and SnS2−x, which may help carrier transport; it was also involved in the doping of the absorber layer, which compensated the intrinsic p-type doping and therefore drags down the doping level. The doping involvement may enlarge the depletion region and improve lifetime of the absorber, which led to enhancing open circuit voltage (VOC), short circuit current density (JSC), and efficiency significantly. However, it degrades the crystallinity of the material slightly

Association Between Social Integration and Health Among Internal Migrants in ZhongShan, China

Internal migrants are the individuals who migrate between regions in one country. The number of internal migrants were estimated at 245 million in China in 2013. Results were inconsistent in the literature about the relationship between their health statuses and social integration. The main difference exists on how to measure the social integration and whether health statuses of internal migrants improve with years of residence. To complement the existing literature, this study measured social integration more comprehensively and estimated the internal migrants\u27 health statuses with varying years of residence, and explored the associations between the migrants\u27 social integration and health. We used the data from 2014 Internal Migrant Dynamic Monitoring Survey of Health and Family Planning in ZhongShan, China. Health status was measured from four aspects: self-reported health, subjective well-being, perception of stress, mental health. We measured social integration through four dimensions: economy, social communication, acculturation, and self-identity. The analyses used multiple linear regressions to examine the associations between selfreported health, subjective well-being, and perception of stress, mental health and social integration. The analytical sample included 1,999 households of the internal migrants and 1,997 local registered households, who were permanent residents in ZhongShan. Among the internal migrants, Adults in the labor force, who were aged 25 to 44 years old, accounted for 91.2% of the internal migrant population, while 74.6% of the registered population were in that age group. Median residential time among migrants was 2.8 (1.3-6.2) years, and 20.2% of them were migrating in the same Guangdong province. Except for mental health, other health statuses among migrants had significant differences compared with local registered population, e. g. self-reported health was better, but subjective well-being was worse. However, these health measurements were improved with more years of residence. Moreover, our results show that two aspects of social integration, economic integration and selfidentity, were significantly associated with health status. Subjective feeling of relative social status levels were more associated with health, which prompted the attention to social fairness and the creation of a fair and respectful culture. More interventions could be experimented, such as encouraging internal migrants to participate in community activities more actively, educating local registered residents to treat internal migrants more equally, and developing self-identity among internal migrants. Better social, economic, and cultural environment can benefit internal migrants\u27 health statuses

Alleviating the Long-Tail Problem in Conversational Recommender Systems

Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are very crucial. However, existing CRS datasets suffer from the long-tail issue, \ie a large proportion of items are rarely (or even never) mentioned in the conversations, which are called long-tail items. As a result, the CRSs trained on these datasets tend to recommend frequent items, and the diversity of the recommended items would be largely reduced, making users easier to get bored. To address this issue, this paper presents \textbf{LOT-CRS}, a novel framework that focuses on simulating and utilizing a balanced CRS dataset (\ie covering all the items evenly) for improving \textbf{LO}ng-\textbf{T}ail recommendation performance of CRSs. In our approach, we design two pre-training tasks to enhance the understanding of simulated conversation for long-tail items, and adopt retrieval-augmented fine-tuning with label smoothness strategy to further improve the recommendation of long-tail items. Extensive experiments on two public CRS datasets have demonstrated the effectiveness and extensibility of our approach, especially on long-tail recommendation.Comment: work in progres