Microplastics Analysis

微塑料颗粒可以分类为一级和次级颗粒。主要的MP颗粒（MPP）是专门为工业用途生产的，例如化妆品中的剥离颗粒。必威东盟体育

Secondary MPPs are formed by physical, biological and chemical degradation of macroscopic plastic parts and are the main source of micro particles released into the environment. They are mainly formed by the degradation of improperly disposed plastic waste, tire abrasion and washing of synthetic textiles.

While the threat to marine life is mostly understood, its full extent cannot be assessed at present. However, uptake by marine organisms and fish leads to contamination of the human food chain by microplastics. As MPPs may contain problematic plasticizers and can also adsorb other organic pollutants, the long-term effects are fairly unpredictable.

The typical workflow of microplastics analysis:

化学分析通常以液态样品的形式开始，该液态根据其起源而不同。将该样品过滤到IR-Transparent底物上，并通过FT-IR成像以整体测量，以捕获过滤器上存在的所有颗粒。然后，通过健壮的机器学习算法自动分析化学图像。

FT-IR显微镜是微型研究中最常见的方法。工作流程非常简单，结果提供了很高的精度，最重要的是可靠性。尤其是焦距平面阵列检测器的FT-IR成像是最新的解决方案。如果您想进一步了解我们的FT-IR仪器设置，请查看我们的FT-IR显微镜。

The Strengths of FT-IR Imaging

红外辐射与micropl交互astic particles, creating characteristic IR absorption patterns. These patterns are then used to identify the particles. If you want to catch up on theFT-IR的基础知识, click here.

By far the biggest benefit of FT-IR is its exceptional reliability and easy application. Any kind of plastic particle (dark coloured, filled, fluorescent, ...) can be analyzed requiring minimal user effort.

True imaging detectors unlock the potential of FT-IR

但是 - 当您将FT-IR与焦距阵列（FPA）探测器相结合时，事情变得非常有趣。结果是非常powerful imaging tool capable simplifying microplastics analysis to routine levels. To learn aboutFT-IR imaging, click here.

这涉及到一个完全自动化的方法,can tolerate a lot of contamination on the filter (e.g. from a sediment) without any negative impact on the measurement results. Ultimately, FT-IR imaging ensures that no particle remains undetected, providing utmost reliability and measurement speed.

The secret to microplastics is the right compination of hard- and software

Besides the analytical method, the software is crucial to analyze microplastics. Traditionally, microplastics spectral reference libraries and provide statistical analysis of size, number and identity. But there is a limit to what such libraries can offer. If you need a very reliable and robust analysis, you must greatly increase the number of spectra within the library, which slows down the analysis considerably.

But in order to make microplastic analysis scalable and routine, data analysis must become faster and, above all, more intelligent. Using huge libraries is simply not practical when time is of the essence. That's why researchers have developed new methods that use machine learning, which fully exploit the immense potential of chemical imaging.

在这里，不用单独检查每个频谱是否有其身份，而是立即处理整个FT-IR图像。智能算法立即分析整个FT-IR图像，使分析顺序更快，更可靠。为了将其投放市场，布鲁克与纯净为了提供和端到端的微型塑料解决方案，涵盖了高工作负载实验室和研究人员的仪器和软件分析。

After taking a sample, it might have to undergo pre-treatment, depending on the contamination from the source, and is atferwards filtered unto compatible filer materials. Very clean samples like drinking water are usually filtered directly onto a suitable filter. But environmental samples like ocean water, river sediments or soil may contain sand or plant material and must be prepared prior to FT-IR analysis.

To remove larger, non-micro particles, mutiple, differently-sized filters are used. These bigger particles are later analyzed by macroscopicFT-IR光谱仪like the ALPHA II. After this, the samples are treated with salt solutions of different concentrations, which is called density separation. During the process, sand and other non-plastic particles sink to the bottom and can be easily removed afterwards.

但是，像鱼或贻贝这样的更复杂的样品呢？这样的样品需要一种复杂的处理来去除解剖后留下的所有有机物。通常，在过滤之前进行酶消化，酸性或碱性处理。

We previously mentioned that aluminum oxide filters are the best choice for microplastics analysis. But of course there are other materials available, like silicon, PTFE, or gold-coated polycarbonate filters which all have distinct advantages and disadvanatges. However, since aluminium oxide filters have become the standard for FT-IR analysis of microplastics, we will also adhere to those standards in our website and videos.

Out of the three avilalbe measurements modes of FT-IR (transmission, reflection and ATR) transmission is the most suited for a fast and hassle-free analysis. Why? Well, ATR is a contact based method and particles can stick to the crystal which requires a user to clean it, making it unsuitable for automation. In reflection, thicker particles are hard to measure and produce spectral artifacts, making it less reliable. Finally, analysis in transmission iscontactlessand will give好的光谱in a short amount of time.

The use of machine learning in the analysis of microplastics is on the rise. With it, researchers have found a reliable way to make data evaluation easy to use for anyone. Following best practices, Bruker teamed up with Purency to promote the Microplastics Finder (MPF).The MPF is a software that automatically analyzes whole FT-IR images of microplastic samples within a few minutes. It yields a comprehensive statistics of all particles present on the filter and classifies them by number, identity and size. All with just one click.

The classifying algorhithm is was trained by real world data that has been evaluated by different microplastic experts. In short, it brings you their combined knowledge into your lab and at your fingertips. Hence, the Microplastics Finder is the optimal tool for routine analysis of microplastic samples and one of the most promising candidates for future standardizaton. The goal is, to guarantee comparability between different laboratories, researchers and analytical insitutes around the world, eleminating human bias altogether.