传感器融合发光测温：合则两利
Sensor fusion luminescence thermometry better together
AI总结：
针对单参数发光测温性能受限问题，将传感器融合（SF）统计方法引入发光测温，通过融合多探头或温度特征，有效提升了测量精度与可用温度范围，且兼容多种读出与激发方式。
摘要：
发光温度计在纳米测温、体内成像以及高电磁场、辐射和机械或化学应力等极端条件等利基应用中非常有效。提高测量精度、温度分辨率并扩大温度范围是这一快速发展研究领域的主要问题，这对研发行业工程师和科研人员的工作至关重要。传统上使用单参数进行传感会导致传感器性能不佳。传感器融合（SF）是一种成熟的统计工具，用于提高自动驾驶汽车、导航系统、医学成像和可穿戴设备的精度，现被引入发光测温领域，通过融合多个传感器探头，或将每个温度相关特征视为独立传感器，从而始终提高精度并扩大可用温度范围。SF是多元线性回归模型的替代和更优选择，因其多功能性而脱颖而出，能够使任何传感器探头材料达到性能极限。它兼容时间分辨和稳态读数，可独立或组合使用，支持单或多重激发。使用含有Mn5+、Yb3+/Er3+/Ho3+、Sm2+和Mn4+/Ho3+/Cr3+激活离子的探头展示了这些优势。
英文摘要：
Luminescent thermometers are highly effective in niche applications such as nanothermometry, in vivo imaging, and extreme conditions like high electromagnetic fields, radiation, and under mechanical or chemical stress. Advancing measurement precision, temperature resolution, and extending the temperature range are the main problems in this rapidly evolving research field, crucial in the work of R&D industry engineers and scientific researchers. Traditionally using single parameter for sensing leads to the sensor underperformance. Sensor fusion (SF), a well-established statistical tool used to enhance precision in autonomous vehicles, navigation systems, medical imaging, and wearable devices is here engineered for luminescent thermometry, by either fusing multiple sensor probes, or observing each temperature dependent feature as a separate sensor, resulting in always increased precision and extended usable temperature range. SF is a replacement and superior alternative to multiple linear regression models as it stands out for its versatility, enabling performance limits to be reached with any sensor probe material. It is compatible with both time-resolved and steady-state readouts, used independently or in combination, with single or multiple excitations. The benefits are illustrated using probes with Mn5+, Yb3+/Er3+/Ho3+, Sm2+, and Mn4+/Ho3+/Cr3+ activator ions.
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