Infrared (IR) spectral imaging is a powerful tool for component analysis and identification in the geological field. In this report, we originally use quantum dot infrared photodetector (QDIP) focal plane arrays (FPAs) with different peak-responsivity wavelengths to analyze the mineral composition of rock samples by IR spectral imaging and show the QDIP’s potential as a solution for some geological problems. After clarifying fundamental characteristics such as the blackbody responsivity, current noise density, and spectral responsivity of QDIPs, we present qualitative and quantitative analyses of mineral samples including conglomerate, sandstone, marble, and dolomite. In the qualitative analysis, we distinguish two different compositions in each rock. In the quantitative analysis, we measure the emittance of dolomite and show the emittance errors. Finally, we discuss which experimental factor determines the quantitative precision most dominantly.

红外（IR）光谱成像是用于地质领域中成分分析和识别的强大工具。在本报告中，我们最初使用具有不同峰值响应波长的量子点红外光电探测器（QDIP）焦平面阵列（FPA）通过IR光谱成像分析岩石样品的矿物成分，并显示出QDIP作为解决某些地质问题的潜力。在阐明了诸如QDIPs的黑体响应度，电流噪声密度和光谱响应度之类的基本特征之后，我们对矿物质样品（包括团块，砂岩，大理石和白云石）进行了定性和定量分析。在定性分析中，我们区分了每种岩石中的两种不同成分。在定量分析中，我们测量白云石的发射率并显示出发射率误差。