CAREER: Understanding the Thermal and Optical Behaviors of the Near Infrared (NIR)-Selective Dynamic Glazing Structures

这个教师早期职业发展（CAREER）计划奖的目的是了解由多层功能和近红外（NIR）选择性效应组成的窗户的热和光学行为。一个理想的窗户应该季节性地响应太阳热，同时透射可见光。然而，目前的窗户技术面临的挑战是独立于可见光来调节太阳热。纳米材料的最新进展已经证明了独立操纵近红外光的能力。本计画将整合奈米级的物理关系，以及奈米材料对多层玻璃结构的热与光学行为的影响。该项目的社会影响将构成一种新的建筑窗户，可以大大降低全国建筑物的总能耗。教育影响将包括专注于建筑窗户和围护结构的课程，这些课程将知识联系起来，并激发建筑和工程界之间的合作兴趣，以培养可持续建筑行业的未来专业人士。此外，本研究亦将设计实验模块，教导高中生自行制作窗户测量传感器，并提高社区及公众对节能窗户技术的认识。为达到此目的，本研究的方法包括：（1）将全球太阳辐照度分解为光谱波段分量，以建立随时间变化的近红外模型;（2）推导和实验验证NIR选择性玻璃窗结构的基本热和光学行为;以及（3）整合热光学模型和NIR模型以用于动态NIR选择性玻璃窗结构的评估和优化。这项研究将为理解纳米级现象的综合效应奠定基础（即，光激发）和微观到宏观玻璃窗结构性质（即，玻璃性能、光谱发射率、中间层隔热能力、层布置）。这些知识将大大提高我们将NIR选择性材料纳入建筑窗户的能力。新的分析模型，考虑到纳米级近红外吸收和散射功能将开发和实验验证。通过将开发的太阳光谱分解模型和计算方法耦合以量化玻璃窗性能，这项研究将提供一个显着的特点和模式的最佳时间依赖的热光学特性的近红外的理解，该奖项反映了NSF的法定使命，并通过使用基金会的知识产权进行评估，被认为值得支持。优点和更广泛的影响审查标准。

The objective of this Faculty Early Career Development (CAREER) Program award is to understand the thermal and optical behaviors of windows consisting of multi-layer functions and near infrared (NIR)-selective effects. An ideal window should seasonally respond to the solar heat, while transmitting the visible light. However, current window technologies are challenged to modulate solar heat independent of visible light. Recent advances in nanomaterials have demonstrated the ability to independently manipulate NIR light. This project will integrate the nanoscale physical relations and effects of nanomaterials on the thermal and optical behaviors of multi-layer glazing structures. The societal impacts of the project will constitute a new class of building windows that can greatly reduce the total building energy consumption in the nation. The educational impacts will include courses concentrating on building windows and envelopes, which bridge the knowledge and ignite collaborative interest between the architecture and engineering communities for cultivating future professionals in the sustainable building industry. Furthermore, experimental modules will be created to teach high school students to build their own sensors for window measurements and to raise community and public awareness of energy-efficient window technology.To achieve the objective, the research approach includes: (1) decomposing global solar irradiance into its spectral band components to achieve a time-dependent NIR model; (2) deriving and experimentally validating the fundamental thermal and optical behaviors of NIR-selective glazing structures; and (3) integrating the thermo-optical model and NIR model for the evaluation and optimization of dynamic NIR-selective glazing structures. This research will form the foundation to understand the combined effects of nanoscale phenomenon (i.e., photoexcitation) and micro-to-macroscale glazing structure properties (i.e., glazing properties, spectral emissivity, central-layer insulating abilities, layer placements). Such knowledge will significantly improve our ability to incorporate NIR-selective materials into building windows. New analytical models that take the nanoscale NIR absorption and scattering features into account will be developed and experimentally validated. By coupling the developed solar spectral decomposition model and computational method to quantify glazing performance, this research will provide an understanding of the salient characteristics and patterns of the optimal time-dependent thermo-optical properties of NIR-selective glazing structures to achieve a minimum level of energy use.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.