Waste Processing & Conversion – Subtopic Landscape

A synthetic biology perspective

The subset of SynBio – waste processing & conversion related patents were further investigated to identify subtopics and assess trending areas. The topic model leverages a hybrid approach based on the optimised extractive summary for each publication. Using a combination of topic discovery via fine-tuned transformer based deep learning and ground truth cross referencing via keyword and classification codes. The process enables a patent to belong to more than one topic for accurate multi-classification trends, accounting for multiple invention embodiments. Please see the topic model page for further details regarding the topic model methodology to avoid duplication here.

Subtopic landscape

The synthetic biology – waste processing & conversion topic model is visualised in figure 6.9, based on the dimensionality reduction of vector embeddings to map each patent to a contextually relevant x & y coordinate, the categorical clusters are colour coded to support review. The visual is based on patents assigned to one key subtopic for simplicity. However, trend analysis also enables a patent to belong to more than one subtopic which is consistent with the topic model methodology throughout this project.

Subtopic model – technology cluster totals

The hybrid topic model methodology identified 15 diverse topics which are ranked based on the total number of published applications in figure 6.10. A patent application can be counted more than once as it can belong to multiple topics.

In figure 6.10, the analysis enables multilabel classification for each patent application, to account for multiple invention embodiments. During the 20 year publication period 2004-2023, nearly 85% of the waste processing and conversion dataset was classified within the top ranked biofuel subtopic (84.4%). The International Energy Agency identifies a significant increase in biofuel production is needed to get on track with net zero emissions by 2050. Advanced feedstock innovation must expand enabling biofuels from waste and residues and non-food energy crops to meet over 40% of biofuel demand by 2030 (currently 9% in 2021). Biomass (73.5%) and in particular cellulose / lignocellulose sources (56.9%) represents an important waste feedstock. Ethanol (37.3%) is a key biofuel produced from waste. Beyond biofuels, there is evidence of plastic and rubber recycling (7%) and the use of waste to produce bioplastics, biodegradable and artificial materials (4%).

The waste processing & conversion subtopic publication year trends are shown in figure 6.11. Publication trends discussed below are based on EP A1/A2 applications, identified patents can belong to more than one subtopic due to multiple invention embodiments.

In figure 6.11, the waste processing & conversion subtopics have declined since an earlier peak. However, there are subtopics with signs of resurgence in 2023. During 2022-23 there were notable year-on-year increases; Biofuel related (19.1%), biomass / feedstock (37.7%), cellulose / lignocellulose (14.2%), bacteria related (20.4%) and wood / forestry (100%). There were no topics with significant compound annual growth rates during 2014-23 due to the biofuels related drop-off. However, bioplastics, biodegradable & artificial materials (2.2%) and animal feed (1.3%) showed positive signs of growth with waste related feedstocks growing in importance within these areas, offering improved sustainability and recycling benefits.

Subtopic top 20 assignees distributions (2014-23)

The patent portfolios of the top 20 assignees within the SynBio – waste processing & conversion dataset are analysed in figure 6.12. The portfolios are restricted to publications during 2014-23, mapped to the 15 subtopics identified, the counts represent total EPO publications.

The heatmap in figure 6.12 reveals the distribution of the top 20 waste processing & conversion assignees during 2014-23, publications can be assigned to more than one subtopic, reflecting multiple invention embodiments. Amongst the top 20 assignees identified, XYLECO is a leader for bioplastics, biodegradable and artificial materials from waste / biomass including wood and forestry waste sources. Although the company appears to rely on cellulose / lignocellulose feedstock. LANZATECH is a well-established biofuel specialist which uses GMOs for waste processing which is predominantly bacteria related. XYELCO and EVONIK are both active in the animal nutrition fields via animal feed, harnessing and converting waste products.

The analysis does not account for earlier publications prior to 2014, which may have contributed to companies developing market share, etc. and potential licensing and acquisitions (subsidiaries). Data cleaning was carried out to clean names and consolidate. The analysis is an informative guide as some specific subtopics have strict content boundaries to enable differentiation, whilst others are broader to capture more generic areas.

Patent family territory analysis

The INAPDOC patent families comprising the identified waste processing & conversion related EPO patents were analysed to identify the top 30 territories where patents are filed. Analysing the publication countries alone is insufficient as major countries such as France, the UK, Germany, etc. may not publish patents going through the European (EPO) route, especially when pending. To further supplement the available data, a bespoke analysis was conducted standardising the publication countries and including ‘protected countries’ to include patent rights which are pending or granted based on legal status. There are caveats which include:

  • The study methodology is focused on EPO patents and may not capture assignees/applicants that file only in home territories or don’t file in Europe via EPO filings.
  • The protected country data may not be fully up to date, due to INPADOC data availability and where EPO patents are recent filings.

The standardisation procedure ensures a territory is only counted once per family. The territory analysis is visualised in figure 6.13, EPO and WO (PCT) patents have been included for reference purposes. Despite the caveats, the analysis provides useful indicators regarding territories where applicants are filing patents within the waste processing & conversion field, based on 2014-23 publications for a relatively recent perspective.

In figure 6.13, approx.80% of the patent families identified had at least one US (80.4%) national filing. Other key territories with at least one national filing include China (56.9%) and Canada (54.2%). Below the 50% threshold, key territories include Brazil (49.3%), India (3%), Germany (34.1%), Australia (33.1%) and Japan (31.6%).

Investigating keyword trends provides a different perspective beyond the waste processing and conversion subtopic model. The smart summaries used during the topic model stage were data mined for the most contextually important keywords leveraging transformer based embeddings. Identifying keywords and phrases most similar to the document plus manual auditing for relevance to the SynBio project, visualised in figure 6.14. The visualisation indicates how the cumulative publication counts have changed between the publication periods during 2014-18 & 2019-23. The methodology aims to identify contextually relevant and reliable keywords as a source of ground truth, signify important keywords within the corpus and audit the topic model subtrend analysis already carried out.

In figure 6.14, the following key findings are observed and also support the trending areas identified by the subtopic modelling:

  • Given the large proportion of declining biofuel related patenting, unsurprisingly there are decreasing trends in biomass (499 to 311publications), fermentation (261 to 170 publications) and fuel (200 to 127 publications) keywords when contrasting 2014-18 with 2019-23.
  • The use of carbon based waste has been consistent (169 decreasing to 165 publications) and pyrolysis (100 decreasing to 91 publications) remains a popular methodology during both periods.
  • The use of microbial species has been consistent (74 publications) and the production of food increased from 50 to 73 publications during 2019-23, related to the production of animal feed, etc.

Subtopic keyword analysis

For a further perspective of contextually important keywords, a statistical procedure was applied selecting six subtopics from the corpus. The analysis contrasts how the usage or frequency of the keywords / phrases differs across the subtopics using a weighted log odds ratio. This aims to identify which differences are meaningful and weight the log odds ratio by a prior outlined in Monroe, Colaresi, and Quinn (2008). The statistical procedure requires the prior is estimated from the data itself rather than an uninformative prior, such as a Dirichlet prior. The procedure is an empirical Bayes approach with results identified in figure 6.15. A further motivation is to audit the subtopics for result relevance and transparency and provide insights into content. As a sidenote the transformer based keyword analysis provides powerful methods to review subtopics and extend the analytical power beyond procedures of evaluating a corpus such as TF-IDF (term frequency-inverse document frequency).

In figure 6.15, the keywords outlined are most characteristic of each subtopic based on the weighted log odds score which is labelled. Another implication of higher log odds scores is the ability to define the keyword identified as more likely to be used within the specific subtopic. This is interesting as some of the log odds scores are not very high, which is not surprising given the overlap encountered between the multiple subtopics identified within the specific topic landscape.

Some key findings observed are:

  • Biomass / feedstock is processed and converted by pyrolysis, producing gas and oil such as bio-oil. Biomass pellets which can be used as fuels are also produced.
  • Yeast strains can be engineered with Kinases and Acetaldehyhe Dehydrogenase (converting acetaldehyde to ethanol) enzymes.
  • Bioplastics and biodegradable materials are formed from biomass, such as cellulose or lignocellulosic feedstocks and plant sources.

It is difficult to distil and characterise the coverage of the subtopics via restricted keywords and phrases, this is also complicated by the weighting not always being frequency led but reflective of the terminology and context which is more characteristic of one subtopic in relation to others. It is fair to conclude that the subtopic model has successfully captured an extensive set of subtrends which are distinct, overlap exists but the trends are accurate once audited. The keywords are relevant to real word applications and suggest the insights identified are a useful tool to examine the specific topic landscape.