• 19) A new era for energy politics - 2018-02-02
  • At this insightful panel discussion at the World Economic Forum Meeting in Davos, it became apparent how a number of simultaneous technological, economic and political developments have generated an irreversible trend towards an electrified energy landscape based predominantly on solar power and electrochemical energy storage.
  • 1) Solar power has become the most competitive way to produce electricity in most areas and allows addressing the issues of climate change, air pollution, energy independence, and economic competitiveness.
  • 2) The electrification of automotive transport is the only feasible way to address inner city pollution. Because this problem is most acute in emerging countries, these countries are leading investments into next generation industries that will push fossil technologies into niche applications across the globe.
  • 3) Digital technologies accelerate these trends and allow for additional efficiency gains.
  • 17) Commercialization of battery materials - 2017-11-12
  • A recently published article by Prof. Vinayak Dravid from Northwestern University and coworkers very nicely illustrates the challenges of converting battery-related inventions demonstrated at the R&D bench level to real life applications. A systematic framework is proposed based on observations from the pharmaceutical industry. Because battery performance is typically limited by interface effects, it is important to emphasize that the more different material combinations are tested at each successive technology readiness level, the higher the likelyhood that a battery material will be incorporated into a real life system.
  • 16) Patent applicant analysis based on curated machine learning models - 2017-10-07
  • On our revised title page, we now offer a demonstration of the unique insights that can be gained by the use of curated machine learning models. Users can enter a patent applicant of interest and rate its patents according to machine learning models that cover different battery types and components. Consequently, a quick characterization can be obtained regarding the recent specialization and potential future areas of commercialization pursued by an organisation. Upon registration, these machine learning tools can be used in a more comprehensive manner.
  • 15) The Battery Show North America in Novi (MI), USA - 2017-09-17
  • Attendance at The Battery Show North America grew by more than 15% compared to 2016. Despite the rapid growth of this industry, the mood cannot be characterised as exuberant, presumably because of increasing competition along the battery supply chain.
    Our booth was well-frequented by visitors who are interested in achieving better situational awareness in the rapidly evolving battery technology sector by identifying relevant patents and technological trends across the globe with the help of machine translations and machine learning.
  • 14) Which metals are used in batteries? - 2017-09-03
  • Our database allows us to answer this question in a convenient and forward-looking manner. A keyword search (title or abstract) in patents published this year shows that for 41% of patents in which a metal or metalloid is mentioned, lithium is the metal that is patented, followed by lead with 11%.

    Metal type in batteries

    Silicon is ranked third with 6%. The graph below demonstrates that silicon is patented much more frequently in batteries nowadays as compared to the years 2001 and 2010. A further analysis aided by machine learning models that identify relevancy with respect to Li-ion battery cathodes and anodes shows that a good part of the reason why silicon is mentioned more often is its relevancy with respect to negative electrodes of Li-ion batteries. A relevancy score of 30 (100: highly relevant, 30: relevant, 0: not relevant) has been used as a cut-off in the graphs below.
    Although aluminum is also relevant to Li-ion battery electrodes (especially cathodes), it is patented more often in other contexts in the battery field, such as packaging.
    For nickel and iron, an increase in patenting activity can be observed and these metals remain highly relevant to Li-ion battery cathodes.

    Trend metal type in batteries Si, Al, Ni, Fe

    An increasing number of patents can also be observed for copper, but not specifically in relation to Li-ion battery electrodes.
    Manganese and cobalt are confirmed to be of very high relevance for Li-ion battery cathodes, which is the context in which they are typically patented in batteries.
    On a relative basis, zinc is being patented less frequently in relation to batteries as compared to the year 2001, and its relevance with respect to Li-ion battery electrodes remains low.

    Trend metal type in batteries Cu, Mn, Co, Zn
  • 13) Availability of machine translated patents - Update - 2017-08-26
  • English machine translations of titles & abstracts are now available for all patents without a patent family member that already contains this information. Most translations were made for newly published patents from China, Korea, Japan, Russia, Germany and France.
  • 12) Availability of machine translated patents - 2017-08-12
  • Patents added to our database after July 22nd now contain an English machine translation of the title & abstract, if no patent family member can be found that contains an English title & abstract. During the public test phase, this feature is available to all users without limitation.
  • 11) Origin of recently filed battery patents - 2017-08-05
  • Origin of battery patents published in 2017

    An analysis of recently published battery patents listed in the database of the European Patent Office (EPO) shows that more than 70% originate in China, Japan or Korea. As these patents are not filed in English, any patent search that does not involve translations is substantially incomplete. The EPO does offer very nice machine translation services, but many patents in its database remain without English abstract and will therefore not show up in a conventional search. We are working on providing machine translations for the titles and abstracts of all battery patents that are newly added to the EPO database for which no English version is available. We will announce the availablity of this feature on this Blog.
  • 10) Update of Privacy Policy - 2017-08-01
  • The following sentence was added to the privacy policy: "In case explicit permission is received from an organisation, training data can be incorporated into community machine learning models, which may not contain more than 20% of training data provided by a single organisation.". This change will allow for the introduction of additional voluntary features that enable collaborative harvesting of knowledge between researchers.
  • 9) Exposition at The Battery Show North America / Critical Power Expo / EV Tech Expo - 2017-07-21
  • The Battery Show North America

    Critical Power Expo

    EV Tech Expo

    Please visit us at The Battery Show North America / Critical Power Expo / EV Tech Expo at booth 2202. We will be happy to demonstrate our patent search and collaboration tools to you, and we will introduce new features related to automatic machine translations.
  • 8) Name change to - 2017-07-16
  • We have changed our name to We think compared to our prior name, our new name better reflects our role as an enterprise that first targets an impact according to our proposed 'theory of change' by connecting battery researchers, while targeting a financial profit as a secondary goal. 5% of any payout to shareholders will be shared with other stakeholders. Targeting of a financial profit gives us the option to provide shares to our employees and to be funded by impact investors, while formation as a non-profit whould have made us dependent on donations that are frequently awarded only on a project basis for 1-2 years.
  • 7) Change to privacy policy - 2017-07-05
  • Our privacy policy was changed regarding the use of cookies: "Permanent cookies with a validity of up to seven days are created locally on the user computer. No third party cookies are created."
  • 6) The time-consuming process of establishing material transfer agreements - 2017-06-27
  • A survey from 2009 by the Association of University Technology Managers (AUTM) discusses how the duration to establish Material Transfer Agreements (MTA) between for-profit and non-profit (receiving) organisations took longer than one month in 55% of the evaluated cases, longer than 3 months in 21% of the evaluated cases, and longer than 6 months in 8% of the evaluated cases. The most sensitive topics in MTA negotiations were IP ownership, confidentiality, and publication rights.

    With, we hope to reduce administrative delays in battery R&D by offering different kinds of standard technology transfer agreements that will allow battery R&D institutions to more quickly find partners which agree on the same technology transfer terms.
  • 5) ees Europe, Munich, Germany - 2017-06-02
  • An impressive number of companies are making an aggressive push into the home and industrial energy storage market, including companies that have originally been active in the automotive sector: Tesla and Mercedes Benz. It becomes increasingly clear that a whole new energy infrastructure is taking form in which all devices communicate with each other, from where energy is produced to where it is consumed. Due to the lack of standards, several companies try to build their business model on connecting different parts of the energy supply and consumption chain and on capturing the resulting value. While such strategies offer huge benefits for the market leader if successful, an interesting question is whether a consortium of companies along the energy supply and consumption chain will form that tries to establish non-proprietary standards to segment the market and allow participants to focus on their core competencies.
  • 4) Machine learning as a prediction tool for researchers - 2017-05-17
  • This article in the Harvard Business Review describes very well what the role of machine learning should be for knowledge workers, a prediction tool that allows for better-informed judgements. Machine learning can be very helpful to search and filter data to assemble a comprehensive set of relevant information at a speed that was not feasible previously. The creative task of designing experiments and judging among different options should remain firmly in the hands of the researcher, and should always be driven by a clearly formulated hypothesis.
  • 3) 5th Heat & Electricity Storage Symposium at Paul Scherrer Institute, Switzerland - 2017-05-09
  • One of the big topics at this symposium was how startup companies in the energy sector generally exhibit much higher capital requirements as compared to startup companies in the ICT sector.
    Jan Wurzbacher from the ETH Zurich spin-off Climeworks explained how the following ingredients have allowed them to acquire large investments from private investors:
    - an important mission that - if sucessfully executed - will make a measurable impact in the area of climate change mitigation.
    - a strong patent portfolio, which will allow for the establishment of a sustainable market position with high barriers of entry.
    - a step-wise strategy implementation that focuses on first establishing a strong, economically viable market position in a niche.
  • 2) The European Battery Show & Conference in Sindelfingen, Germany - 2017-04-05
  • During the presentations, it became apparent how very large investments are being made in Asia and in North America into expanding Li-ion battery production capacities.
    These large investments allow for very significant process technology improvements that allow for substantial production cost reductions, but not necessarily dramatic energy density increases.
    Because the transportation of large Li-ion battery packs across continents is difficult, additional investments in Li-ion battery production plants by leading battery producers are also expected in Europe.
    Big questions for the European battery industry are the extent to which large Li-ion battery producers will establish local supply chains, as well as whether new disruptive battery technologies will allow new battery manufacturers to enter the market.
  • 1) Applied Machine Learning Days at EPFL, Switzerland - 2017-01-30
  • The first 'Applied Machine Learning Days' were held at EPFL in Lausanne, Switzerland. A highly interesting set of presentations demonstrated how machine learning makes data analysis more efficient in many areas of science, technology, business and in the non-profit sector.
    The panel discussion resulted in a consensus that technological advances in this field have to be carefully accompanied by politics and social sciences, which should define a legal framework and philosophical guidelines, and by sufficient investments in education.