Sensor-based XRF separating non-magnetic high-alloy ferrous fractions.
In development
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Updated Sept 17, 2026
Electronic waste recovery covers identifying and separating what is in a mixed scrap stream. On Halo, the solutions cover sorting by spectroscopy, and sorting by vision and learning. Every solution comes from the team that developed it, so you can reach the people behind the work directly. Sign up to search the full network and post your specific need.
Sorting by spectroscopy
Laser-induced breakdown spectroscopy identifying scrap and grading it.
In developmentSupplier
Lawrence Technical University
Powder X-ray diffraction reading zinc content in real time.
In developmentUniversity
GG
Machine learning applied to spectroscopy for metal identification.
ConceptualStartup
MP
Maastricht University
Optical and spectral imaging identifying material in bulk scrap.
In developmentUniversity
BB
Geospatial Technology Associates
A spectral imaging system built for automated material identification.
In developmentStartup
Pectin side streams used to recover critical metals selectively.
Co-developmentIn developmentStartup
Sorting by vision and learning
NK
UHV Technologies
AI-driven identification and sorting, running on the scrap line itself.
In marketSupplier
RGB vision, hyperspectral and X-ray transmission on one robot.
In developmentStartup
KB
Geometric Data Analytics
Actively learned segmentation, so the model improves on the operator's stream.
In developmentStartup
RD
Northeastern University
Hyperspectral imaging paired with tactile sensing on the same stream.
In developmentUniversity
APJ Abdul Kalam Technological University
Deep learning applied to automated ferrous sorting in steel recycling.
In developmentUniversity
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Who is working on electronic waste recovery
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Organizations in electronic waste recovery
Universities, startups, and suppliers with solutions in electronic waste recovery.
E-waste recycling organizationsAbout electronic waste recovery
Almost every entry on Halo is a sorting instrument. Seven identify material by its spectrum, using XRF, laser breakdown, X-ray diffraction or hyperspectral imaging, and seven more use vision and machine learning, including one that sorts by the sound a piece makes. Recovery chemistry barely appears. On Halo it spans two groups: sorting by spectroscopy, and sorting by vision and learning.
Stage of development. Work on electronic waste recovery on Halo comes mostly from companies. 38% of the solutions are in market. Co-development and licensing are the usual partnering routes, and about 25% of the solutions that state terms offer sponsored research.
Three trends in e-waste recycling solutions on Halo
Fourteen sorters and one chemist. Thirteen entries identify and separate material and only one recovers a metal chemically. Electronic waste is valuable because of what is in it, and the commercial bottleneck is telling one alloy from another fast enough to matter on a belt, not the metallurgy that follows.
Every physics gets tried. X-ray fluorescence, laser-induced breakdown spectroscopy, powder X-ray diffraction, hyperspectral imaging, X-ray transmission, RGB vision, tactile sensing, and machine learning over several of these at once. One system combines four modalities on a single robot. No single signal identifies every material, which is why the multi-sensor approaches keep appearing.
The model learns on the operator's own stream. Actively learned segmentation and classification, deep learning trained on ferrous imagery, high-speed vision with AI in the loop. Scrap composition varies by region, supplier and season, so a model trained centrally is worth less than one that adapts to the material arriving at a particular yard.
138organizations
138solutions listed
62%from startups and companies
38%in market
Frequently asked questions
What are e-waste recycling solutions?
Electronic waste recovery covers identifying and separating the materials in a discarded device or a mixed scrap stream. It spans sorting by spectroscopy, sorting by vision and machine learning, and the chemistry that recovers a critical metal once separated. Recyclers, smelters and metal traders are the buyers. On Halo the work leans toward sorting by spectroscopy, and sorting by vision and learning.
What are examples of e-waste recycling solutions?
Two examples of e-waste recycling solutions on Halo include:
What are the latest e-waste recycling innovations?
The most recently updated e-waste recycling solutions on Halo include:
Which companies and suppliers are developing e-waste recycling solutions?
There are 138 organizations with e-waste recycling solutions on Halo, 25 of them universities and research institutions. Among them are Fraunhofer USA, ZORTENET PC, and Lawrence Technical University. Most offer co-development or licensing. Sign up to see every organization working in the area and to send them your specific need.
How do I find e-waste recycling research partners?
Browsing e-waste recycling solutions on Halo is free. Sign up to search the full network and save the ones you want. Post your specific need to get exact matches. Organizations reply directly on the platform.
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