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Learn more about Purency and microplastics


Microplastics Finder: Why, What and How?

A typical dataset generates millions of spectra which can range from approx. 5-70GB. To access the full value of this chemical information, a robust data analysis method is needed.

"FTIR and AI in Microplastics analysis" - Blog Post by Bruker

To unlock the full value of the chemical information from FTIR Images, a robust data analysis method is needed. New blog post explains how FTIR and machine learning join forces.

Purency im LABO Magazin: Maschinelles Lernen für die Mikroplastikanalytik

Purency wrote an article for LABO - Fit for Lab magazine explaining the differences between machine learning and conventional spectral library searches.

Purency increases involvement in standardisation of microplastics analysis

Purency team member Michaela Radl joins the joint working group "Plastics (including microplastics) in waters and related matrices" at ISO.

Microplastics Finder R2021a in new publication from Chinese researchers

Are we measuring the same metrics? This question was raised by a team of researchers investigating automated analysis approaches for microplastics detection.

Austrian federal government starts action plan regarding microplastics

The Austrian government published the first draft of the action plan for microplastics (Aktionsplan Mikroplastik). The public is now able to comment and contribute to the draft.

Publication evaluates machine learning-automated analysis of μFTIR-imaging

New publication evaluates the advantages of computer-assisted microplastics analysis based on μFTIR-images of several environmental samples and machine learning-based data analysis

Purency joins the new joint working group at ISO

Purency joins the ISO joint working group "Plastics (including microplastics) in waters and related matrices".

First prototype of machine learning-based data analysis for Raman

In cooperation with leading researchers, Purency has developed a first prototype to automate the data analysis of microplastics meeasurements using Raman spectroscopy.

Purency joins research project Microplastics@Food

Microplastics at Food: International project strengthens efforts of science and industry in microplastics research.

Microplastics in fresh water - Introducing a fast analysis pipeline

What began as laborious manual processing in 2016 has now become one of the fastest and most accurate analysis pipelines for microplastics analysis. Learn more!

Purency's Microplastics Finder in LABO - Fit for Lab Magazine

Purency's Microplastics Finder wurde in der LABO - Fit for Lab anhand von einer Meersalzprobe vorgestellt.
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Purency Founder win European Young Innovators Award 2022 by WSA

Purency is among the 15 winners of the WSA European Young Innovators award! The award aims to connect and highlight purpose driven entrepreneurs under the age of 30.

Digitalization 4 Climate - best Practices from Austria at the COP27

Purency Co-Founder Valerie Hengl and other Austrian companies join the live stream of the COP27 on sustainable best practices from Austria.

Visit to Aalborg for the MONPLAS meeting at the Micro2022 conference

Purency, represented by Michaela Radl, was invited to present and discuss at this year's MONPLAS meeting at the University of Aalborg as well as Micro2022 conference.

Presenting Purency at the Microplastics2022 conference in Ascona

Co-Founder Aurelia Liechtenstein joins more than 100 scientists from around the globe and presents at the Microplastics2022 conference in Ascona.

Purency receives the ACR startup prize

The ACR (Austrian Cooperative Research) startup prize was awarded to Purency for the joint work with partner OFI in the research project microplastics@food.

Purency speaks at GründerinnenTag 2022 by WIENERIN & Austrian Standards

Co-Founder and Co-CEO Valerie Hengl gives her Inspo-Talk about her journey at Purency and the importance of standards at the WIENERIN Gründerinnentag 2022.

Purency participates at GoSeoul 2022 by GIN Austria

Aurelia Liechtenstein and Michaela Radl are representing Purency in Korea during the GoSeoul programme 2022 by Global Incubator Network Austria (GIN) and ADVANTAGE AUSTRIA.

"Fachgespräch mikroPLASTIK" in Vienna 2022

After the publishing of the "Aktionsplan Mikroplastik" from the Federal Ministry of Austria, the BMK invites experts to talk about microplastics.

Purency joins 7th International Marine Debris Conference in South Korea

Purency visits Busan (South Korea) for one week to join 7IMDC together with close to 1000 participants from science, policy and business.

Purency presents at the ASTM International Symposium in Seattle

Purency attends the ASTM International Symposium on "Microplastics Analytical and Reference Standards - Opportunities to Advance Microplastic Science" in Seattle (USA).

Purency gives expert talk at Austrian Standards event

Missing standards and harmonization are both an opportunity and a challenge for comoanies. Purency presents these points during and expert-talk at Austrian Standards.

Purency at Future Labs Live 2022 - DIGITAL. AUTOMATED. CONNECTED.

Co-founder and Co-CEO Michael Stibi gave a pitch about Purency and the Microplastics Finder software at Future Labs Live 2022 in Basel.

5-HT Digital Hub: “Purency makes microplastics visible”

In an interview by 5-HT Digital Hub, Co-Founder and CEO of Purency Michael Stibi talks about how the Microplastics Finder software makes microplastics visible.

Bündnis Mikroplastikfrei hosts event about Microplastic at in Vienna

The association bündnis mikroplastikfrei hosts an information event about the issue of mictoplastics in Vienna with stakeholders from politics, science and business.

Greentech: “Mikroplastik-Messung aus dem Valley”

Greentech presents Purency and its solution, the Microplastics Finder software, and how it makes microplastics visible based on machine learning.

Purency's journey covered by Forbes in issue on "innovation & research"

Forbes 2-22 issue published with two-page article on Purency and it's journey.

Purency participates in the Scaleup Globally 2022 Workshop

The Scaleup Globally 2022 provides an 8 week long workshop including indivudual coaching on better selecting target markets and to improve product market fit.

Purency joins UNEA-5.2 in Nairobi: global agreement on plastic pollution

Valerie Hengl joins UNEA-5.2 in Nairobi to connect and discuss (micro)plastics pollution with international policy makers and stakeholders.

Purency accepted into prestigious funding program by AWS

Purency has been accepted into the prestigious public Seed-Funding program by Austria Wirtschaftsservice (AWS).

All Purency Co-Founders are on the Forbes 30 under 30 DACH list

More than 10% of this years' Forbes 30 unter 30 DACH are coming from Purency.

We are GEWINNer 2021

Purency ranks among the Top100 Start-Ups in Austria.

MISSOURI project concludes with a two-day workshop on microplastics studie

Finding microplastics in soil is a complex undertaking. Find out how machine learning can pave a road in these demanding circumstances.

"Ich seh, ich seh, was du nicht siehst: Mikroplastik im Mikroskop"

DiePresse erscheint am 11.9.2021 mit einem Artikel zu Purency. Co-Founder Benedikt Hufnagl und Aurelia Liechtenstein berichten zur Mikroplastikanalyse und Purency's Plänen.

Purency contributes at SETAC Europe's 31st annual meeting

Purency contributes at SETAC's annual meeting with a presentation on the "Automated Ultra-Fast Analysis of Microplastics in large µFTIR Imaging Datasets From Environmental Samples"

Nomination for CEN and CENELEC Standards + Innovation Award

Purency Co-Founder Benedikt Hufnagl has been nominated for the CEN and CENELEC Standards + Innovation award in the category Young Researcher!

Machine Learning & Databases: question of speed, accuracy and scalability

Machine Learning is a game-changing technology that has a track record of disrupting and challenging the status quo. Learn more about its potential impact on microplastics analysis

Webinar: Get your lab ready for Microplastics Analysis.

A promising approach for an all-in-one microplastics solution. Purency is supporting Bruker with the Microplastics Finder in order to provide a complete solution for microplastics

Co-Founders join microplastics talk at EWMD Austria

European Women Management Development (EWMD) has invited Valerie and Aurelia to join an evening talk regarding microplastics. Sign up for free to learn more about microplastics.

Purency@IT-Kolloquium 2021: Digitalisierung zum Erreichen der Klimaziele

Purency hält einen Vortrag beim IT-Kolloquium 2021 des Österreichischen Verband für Elektrotechnik (OVE) zum Thema "Digitalisierung zum Erreichen der Klimaziele".

Futurezone: "Start-up macht Mikroplastik mit Datenanalyse sichtbar"

Purency erläutert im Interview mit Futurezone mehr zu Mikroplastik und der Datenanalyse von Mikroplastikmessungen.

Purency in Der Standard: Dem Mikroplastik auf der Spur

Warum Daten, Forschung und Standards so wichtig sind, um Erkenntnisse zum Thema Mikroplastik zu gewinnen? Das hat Purency im Interview mit "der Standard" näher erläutert

Purency wins Living Standards Award 2021

The Living Standards Award 2021 by Austrian Standards was awarded to Purency in the category 'Developing Future Technologies'.

Purency x Klimaheldinnen - Das Nachhaltigkeitsmagazin

Purency goes national TV: Purency was broadcasted 12 times on national TV within the show Klimaheldinnen across the ProSiebenSat1.PULS4 Group in Austria.

We are GEWINNer 2020

GEWINN Wirtschaftsmagazin honors the top Austrian startups and founders of the year with it's 'Jungunternehmer' award.

TU Vienna press release: Purency joins Analytica 2020

Purency will join Analytica 2020, the leading laboratory trade fair, to introduce the flagship product "Microplastics Finder" to a global audience for the first time.

Purency among the 10 Finalists for YPO Scale-A-Thon 2021

Purency is among the 10 finalists YPO of the Plastic Waste Scale-A-Thon: Connecting with impactful startups, world leaders, CEOs, NGOs and other experts curated by YPO.
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Why does the Microplastics Finder outperform database-based approaches?
The analysis based on machine learning algorithms offers several key advantages over conventional methods of data analysis: Database-based analysis solutions often have a couple of hundred IR spectra in their library. The cross-checking of each pixel to the library is therefore quite slow and gets even slower as the library gets bigger. A more robust classification requires a bigger library which will slow down the process of the classification even further. With machine learning, however, you do not have a trade-off between quality and speed of the analysis: the Microplastics Finder makes the analysis more robust and the results more precise. All while being faster. A lot faster.
Do I need a powerful PC?
Our software runs on ordinary office PCs. However, please ensure that you have at least 16 GB of RAM. We recommend 32 or 64 GB of RAM since hyperspectral images can become very large (e.g. 20 GB). As our software is enhanced for multi-screen use, we highly recommend that you have two screens connected to your workstation.
Does the Microplastics Finder also work for Raman or FT-IR single-point measurements?
The Microplastics Finder is optimized for FT-IR imaging. However, we are always broadening our horizon. We are currently running tests for processing Raman data as well and enlarge the Microplastics Finder's capabilities. If you are using a Raman instrument and are interested in using our software, please contact us to explore the opportunities.
Do I need an FT-IR microscope for the Microplastics Finder?
The Microplastics Finder is a software product that automates the data analysis of microplastics measurements using FTIR imaging. Thus, an IR (imaging) microscope is needed for its usage. The real power of the Microplastics Finder lies within its ability of processing FTIR images fast and deliver robust classification results.
How long does it take to train the Microplastics Finder on other/new particles?
Microplastics Finder covers 99% of microplastics by covering the 20 most abundantly produced polymers. If you are looking to identify other particles, please contact us and we will explore the options. Generally speaking, the model would be trained to cover another type of particle and then a new model would be deployed.
How do I know whether the results of the Microplastics Finder are correct?
We have a built-in feature that states how certain the prediction algorithm is about its classification of the particle. With high values, you can be sure that the particle was classified correctly. With low values, you are able to manually check whether the classification was really correct by using the built-in spectral reference database.
Up to what size can particles be identified?
The Microplastics Finder classifies pixels. The size of particles that can still be detected, therefore, depends on the spatial resolution of the setup used.
Which type of particles can be found by the Microplastics Finder?
Currently, we offer the classification of 20 most abundantly produced polymer types. This covers more than 99% of current microplastics. As the Microplastics Finder purely focusses on finding microplastics, every non-polymer pixel that is identified will be treated as matrix.
Why is the Microplastics Finder more reliable than other methods?
The results provided by the Microplastics Finder are reproducible and transparent. Meanwhile the method eliminates the need for time-consuming manual rework, thereby, minimising subjective bias and maximising the comprehensibility.
Why is the Microplastics Finder more robust than other methods?
Our algorithm was trained by experts with over 12 000 spectra of microplastic particles in a vast number of matrices and on several different filter types. By design, this methodology ensures that the algorithm is extremely robust and classifies even noisy environmental samples reliably. A performance that a conventional database with a couple of hundred spectra cannot achieve.
Why is the Microplastics Finder faster than other methods?
The decision-making process of the algorithm to classify and assign each pixel to a predefined polymer class is an extremely fast process. It is an order of magnitude faster than other particle software. For example, using database-based approach means each pixel's spectrum is compared to every spectrum of the database, thus, the process takes longer the more spectra the database contains. Therefore, there is a trade-off between time and analytical quality which you do not have with a machine learning approach.
Why did Purency create the Microplastics Finder?
Spectroscopic approaches, and imaging techniques in particular, are very promising when it comes to analysing a sample for microplastics. However, the enormous amounts of complex data pose a challenge. A powerful tool was needed to reliably identify microplastics, even in complex samples: Based on years of experience we crafted the Microplastics Finder with the goal to raise the analysis of microplastics to the level of routine analysis. Microplastics analysis becomes scalable and new types of questions about the presence and origin of microplastics can be answered. Therefore, enabling risk assessments and quality control in an efficient manner.
Why should I use FT-IR Imaging and the Microplastics Finder to analyse my sample on microplastics?
An FT-IR image is densely packed with a ton of molecular information and the experimental procedure for data collection is quite easy. However, the enormous and complex amounts of data that are produced, make it difficult to obtain the relevant information about quantity, size and type of the polymer particles in the sample. Here, the Purency Microplastics Finder comes into play as it analyses the complete data set within a few minutes. This guarantees that no information gets lost and the full potential of FT-IR imaging is unlocked.
How does the Microplastics Finder work?
The Microplastics Finder checks each pixel of the hyperspectral image and assigns it to a predefined polymer class. This decision-making process is done by our built-in machine learning algorithm, which uses the characteristic regions of the spectra to distinguish the polymer types. After the entire image has been processed, neighbouring pixels with the same polymer class are labelled as particles. Further, properties such as the polymer type and the size of each particle are visualized in a clearly arranged results table.
How does the machine learning technology work and what is it?
At Purency, we use machine learning to automate certain processes that are too time-intensive to be done by humans. Machine learning models are ultimately mathematical models which were created from training data by a machine learning algorithm. So, to solve the microplastics classification problem, we trained a model to decide which pixel is a polymer and which one is not. We also taught it to distinguish between different types of polymers. There are different approaches to train machine learning models: supervised and unsupervised learning. In unsupervised learning you simply feed data into the algorithm and the algorithm learns by itself what the outcome should be. In supervised learning, the algorithm is trained with labelled data, which is the outcome of the classification process. Purency uses supervised learning and trains the model based on representative data which was compiled and analysed by microplastics experts around the world. Thereby, providing a fully trained, out of the box, and robust method to laboratories analysing microplastics – enabling you to identify not just what one person, but a group of microplastics experts would find in a sample.
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Microplastics are plastic, or polymer, particles with a diameter of less than 5mm. Polymer particles below the size of 0.001 mm, or 1 μm, are subsequently called nanoplastics. Microplastics are further divided into primary and secondary microplastics.

Primary Microplastics

Primary Microplastics are plastic particles that have been deliberately produced or are directly emitted in the size ranges that characterise microplastics.

Secondary Microplastics

Secondary microplastics are plastic particles within the characteristic size range that originate from larger pieces of plastic which fragmented over time. Examples include microplastics from bottles, fishing nets or plastic bags.

Fourier-Transform Infrared Spectroscopy (FTIR)

Fourier-Transform Infrared Spectroscopy (FTIR) is a technique used to obtain an infrared (IR) spectrum of absorption or emission of a solid, liquid, or gas. This spectrum is obtained by exposing a particle to infrared radiation. The absorption of the light is then recorded and is characteristic to a certain material. The information is represented in a spectrum that can be classified to identify a certain material.

FTIR Imaging

When FTIR Imaging is used, an IR spectrum is recorded for each pixel of an image. Thereby, whole (microplastic) particles can be identified based on the chemical information instead of just visual information.
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