AI and LENR - The Bots Get Busy.

  • Spotted by former member Greg Goble, this paper which is a first major effort at data mining over 4,500 LENR research reports was presented at an IEEE meeting in Tokyo. Professor David Nagel who along with Professor Anasse Bari was an advisor to the team kindly sent me a copy, which is attached.


    Computer science majors Yvonne Wu, Emos Ker, Charles Wang, Benjamin Kang, and Dongjoo Lee, together with their advisors Professors Anasse Bari and David Nagel (George Washington), and other co-authors published a paper, "Towards Understanding Low Energy Nuclear Reactions: Structuring the Literature and Applying Data Analytics"


    Abstract— After more than three decades of research, Low Energy Nuclear Reactions (LENR) still pose a challenge to comprehensive understanding. In this study, we introduce a preliminary framework of analytical tools that could assist the LENR community in accessing literature and applying machine learning for mining insights. We first collected and structured a dataset of over 4,500 LENR publications. Following that, we designed and deployed a descriptive analytics tool to search and draw insights by using a platform that allows data slicing based on keywords, authors, publication dates, and other metadata.

    Additionally, we applied unsupervised machine learning algorithms to the data to generate clusters of publications based on semantics and other features. Through interactive interfaces, we enable targeted investigation of specific reported phenomena. Findings provide data-driven insights into the connections between concepts like heat, helium, transmutation, and other measured effects. The analysis also identifies key contributing authors, organizations, and publication venues.

    By moving beyond isolated results to higher level knowledge, this work aims to advance the field by providing revealing relationships in the collective evidence. Our preliminary results and the first version of our tools will be useful for scientists already in the LENR field, as well as for those considering research on the topic. Additionally, they will benefit other scientists and policymakers. We conclude that data science approaches show promise for demystifying and

    advancing LENR, and merit further application to this complex scientific challenge.


    Dave Nagel Bari LENR AI paper.pdf

  • Knowing what is known is important. However, this is not the problem. The problem starts when the behaviors are combined to create a model explaining their relationship to the fusion reaction. Everyone selects a different set of behaviors to support their imagined models. As a result, no agreement is possible no matter how much is known about the behaviors. I did this data collection the hard way and published the results in two books. Although the books are occasionally cited, the ideas and conclusions are very seldom acknowledged. In other words, no matter how much information is available, people will use only the part that confirms what they want to believe. This problem can only be solved by teaching new minds what is known at university where new relationships between the behaviors can be explored under the supervision of someone who understands material science and nuclear behavior.

  • Additionally, we applied unsupervised machine learning algorithms to the data to generate clusters of publications based on semantics and other features. Through interactive interfaces, we enable targeted investigation of specific reported phenomena.

    That sounds do-able. That is the kind of thing computers excel at. Especially AI computers.


    By moving beyond isolated results to higher level knowledge, this work aims to advance the field by providing revealing relationships in the collective evidence.

    Well . . . a generative ChatGPT style AI is like Hamlet's ghost. It can never tell you something you don't know already. Or I should say, it can only tell you something that someone, somewhere, knew and wrote down. It cannot have an original thought, or synthesize new knowledge. It is a superfast idiot savant assistant who actually understands nothing.


    Other AI models and future AI will generate original ideas and come up with connections that people did not.


    An AI can reveal relationships to you because you cannot possibly read all of the literature, or remember every detail, or see every connection that the authors and their words reveal. That is extremely valuable. For that matter, an old fashioned printed paper encyclopedia was valuable. A Google Search is valuable. An AI is even better because it addresses your question by finding what you want to know and excluding information you are not looking for. An encyclopedia may have many paragraphs describing aspects of your question that you don't want to read, and it may not have the part you are looking for.


    Our preliminary results and the first version of our tools will be useful for scientists already in the LENR field, as well as for those considering research on the topic.

    I hope so. Scientists apparently did not find my AI useful. Or perhaps they just did not think to use it.


    People sometimes fail to make use of new technology. They do not realize what advantages it has. They do not know how to use it.


    When the first public telegraph was installed between Washington DC and Baltimore in 1844, no one used it for weeks because no one understood the benefit of instant communication. Finally, people began using it for stock market quotes, where knowing something first is a big advantage. It became very popular. Within a few years, telegraph companies were big business.


    The U.S. Navy lost the Battle of Savo Island in part because officers and ship captains did not understand radar, and did not take advantage of it. Granted, it was imperfect and difficult to use. See:


    Reversal of Fortune
    How the bitter defeat at the Battle of Savo Island in 1942 inspired a tactical reset that led to U.S. Pacific victories in 1943.
    www.usni.org


    QUOTE:


    "The maritime environment in the South Pacific, which differed greatly from the North Atlantic, where initial SC radar testing had been accomplished, also significantly reduced detection ranges and sensitivity, unbeknownst to U.S. commanders. Lack of knowledge about radar meant a lack of trust among more senior naval officers throughout the subsequent battles around Guadalcanal. Even Commander Arleigh Burke, who would learn to capitalize on the radar advantage, hesitated in his first action against the enemy because of his mistrust of the information provided by his radar operator."

  • Knowing what is known is important.

    Yup. And an AI can be a big help with this.


    However, this is not the problem. The problem starts when the behaviors are combined to create a model explaining their relationship to the fusion reaction.

    Today's AI itself cannot create a model. However, if an author somewhere proposed a model, you -- the reader -- probably did not hear about it. Because there are so many authors and so many models in the literature. So, if you ask the AI to find a model with thus-and-such characteristics, that addresses this-and-that experimental data, the AI might find what you are looking for. It will find it much faster and more easily than you would by manually slogging through the papers.


    I might find it with my local computer text search program FileLocatorPro. It indexes every paper in the LENR-CANR.org collection plus the Storms collection papers. The problem is that it finds far too much. In the LENR document file, you put in a search for:


    model NEAR "high loading"


    (Meaning the word "model" near the words "high loading")


    It comes up with 21 papers. With quotes such as:


    "2. Equation of State Models for H2


    As discussed in Section 1, our understanding of the chemical potential of hydrogen in palladium hydride at high loading requires an understanding of the equation of state of gaseous and liquid hydrogen at high pressure. In connection with the discussion below, we recall the ideal gas law written as . . ."


    BiberianJPcondensed.pdf


    It gives too much unorganized information. An AI does a much better job, in response to a query such as:


    "What models have been proposed to explain the role of high loading in bulk-Pd D2O cold fusion?"

  • An AI does a much better job, in response to a query such as:


    "What models have been proposed to explain the role of high loading in bulk-Pd D2O cold fusion?"

    Okay, I think a dedicated bot with a database of cold fusion papers would do a better job. The general purpose ChatGPT bot does not do a good job addressing this question. It says:



    The phenomenon often referred to as "cold fusion" in the context of palladium (Pd) and heavy water (D2O) has been a subject of controversy and interest since it was first reported in 1989. Various models have been proposed to explain observations of anomalous heat and nuclear products in such systems, particularly under high loading conditions where the palladium lattice is highly saturated with deuterium. Here are some of the main models that have been proposed:

    1. Electron Screening Model: This model suggests that electrons in the palladium lattice reduce the Coulomb barrier between deuterium nuclei (deuterons), facilitating nuclear reactions at lower energies than would normally be required in thermonuclear fusion. The dense electron cloud surrounding the palladium lattice is thought to partially shield the positive charges of the deuterons, allowing them to come close enough to undergo fusion.

    2. Boson Condensation Model: In this model, deuterium loaded into a palladium lattice is proposed to form a Bose-Einstein condensate. This quantum state could potentially enable nuclear reactions at room temperatures due to quantum mechanical effects that allow overlapping wave functions of deuterons. The theory suggests that under certain conditions, a collective state can be achieved where multiple deuterons occupy the same quantum state, leading to an increased probability of tunneling through the Coulomb barrier.

    3. Quantum Mechanical Tunneling: This approach focuses on the quantum mechanical property of tunneling, where particles traverse energy barriers that they classically should not be able to overcome. High loading of deuterium in palladium increases the probability of deuterons being close enough to tunnel through the Coulomb barrier and fuse, despite the low kinetic energies involved at room temperature.

    4. Fracto-fusion Models: These models propose that micro-cracks and imperfections in the palladium lattice under high deuterium loading conditions could create localized sites where fusion is more likely to occur. The idea is that mechanical stress and the resulting fracturing could generate hot spots or unusual conditions conducive to fusion.

    5. Metal Hydride Models: In this scenario, the unique properties of palladium hydride and deuteride under high loading conditions alter the nuclear properties of deuterium atoms embedded within the lattice. These altered properties might include changes in the electron screening potential or modifications of the deuterium nuclear states, potentially leading to enhanced fusion rates.

    These models aim to address the key challenge in cold fusion: explaining how nuclear reactions typically requiring high energies and temperatures could occur at room temperature and without significant radiation, as traditional nuclear reactions would predict. Despite ongoing research, cold fusion remains a contentious topic in the scientific community, with many experiments failing to reliably reproduce the initial claims, leading to skepticism about the feasibility of these processes as described. The models are largely theoretical and have not been conclusively proven or widely accepted in the scientific community.


  • 6. SHI (Simple Human Intelligence) The Hydrogen (protons) connect to the electron belonging to the 'neutron' that resides inside the receiving nucleus such as Palladium which has some extra 'neutrons' (the heavy isotopes). In doing so the proton that is fused together with the receiving neutron on the nucleus make the next deuteron (proton-electron-proton) and thus is immediately transmuted into a Silver. When the new deuteron is on a 'wrong' location making an invalid structure the nucleus can and will fission or spallate into smaller fragments. This is still theoretical but can proven or disproven as some elements / isotopes would not be receptible due to missing 'extra neutrons'.
    If proven correct we can make stable heavy elements fission with all the benefits that come from it.

  • These models aim to address the key challenge in cold fusion: explaining how nuclear reactions typically requiring high energies and temperatures could occur at room temperature and without significant radiation, as traditional nuclear reactions would predict. Despite ongoing research, cold fusion remains a contentious topic in the scientific community, with many experiments failing to reliably reproduce the initial claims, leading to skepticism about the feasibility of these processes as described. The models are largely theoretical and have not been conclusively proven or widely accepted in the scientific community.

    Dear JedRothwell !

    Everything great is always simple:

    We have no other choice but to turn the problem of cold nuclear fusion into a postulate and solve it in a philosophical and metaphysical way, namely:

    To postulate that cold nuclear fusion is a fundamental absolute property of the movement of our World. It occurs always and everywhere with any movement of matter. Our World is like this!

    It is necessary that such a conclusion follows.

  • Aleksandr Nikitin Nobody who understands cold fusion believes it is anything but a natural phenomenon. And if nothing moves, nothing changes, so movement is part of every change. So for me, your idea isn't new.

    Dear Alan Smith!

    Your criticism is of an uncertain nature, and when you write: “Your idea is not new,” you must indicate by whom it was previously expressed.

    I ask you to read my article more carefully. You didn't understand her. Maybe I'm not explaining it well, but very briefly my idea is this:

    1) in our World, it is not matter that is primary, but the non-mechanical movement of our World-Nature, the measure of which is energy. In our World, everything is relative, there is nothing absolute, that is, there is no state of rest, everything is in motion and change,

    2) the movement of our World is, at a fundamental level, cold nuclear fusion, which is material-neutrino-energy induction,

    3) Any engine (including supportless, motorless, non-mechanical, “anti-gravity” and so on) is a generator of cold nuclear fusion,

    4) The movement of a material body in space and time is possible in only one way, namely, by “consuming” mass, that is, turning it into neutrino radiation.

    Excuse me, who expresses such ideas?

    My idea is more developed in the article that I attach. Thank you.

  • Your criticism is of an uncertain nature, and when you write: “Your idea is not new,” you must indicate by whom it was previously expressed.

    The idea that unless something moves (changes) nothing happens is intrinsic to science and philosophy, even something as trivial as the quantum jump pf an electron cloud from one orbital to another is movement. This concept of the unstoppable and continual nature of change predates written records but was first expressed (as far as I know) by Heraclitus who said "All entities move and nothing remains still" or if you prefer it by Plato "Everything changes and nothing stands still" That was around 500BC, so as I said, is 'nothing new'.


    As for your interesting ideas about neutrinos, until we have dependable and practical means of detecting them your idea remains a speculation. Unfortunately I don't have room in my laboratory for a tank containing 50 kilotons of high-purity water and many thousands of photo-multipliers.




  • I agree with you. Of course, such ideas have been expressed since ancient times, for example, by Heraclitus, Aristotle, Plato. But I am rather a continuator of the ideas of Parmenides. But we live in the 21st century and it is incorrect to say in a scientific debate that everything already happened in Ancient Greece. Sorry, but maybe some of our contemporaries expressed such ideas?

    About neutrinos.

    1) a neutrino is a particle-wave-field,

    2) neutrino, so to speak, is a “displacement current”,

    3) in a laboratory experiment there is no need to focus on registering and detecting neutrinos, but it is necessary to register the PROCESS OF MATTER MOVEMENT that generates neutrinos,

    4) for me there is no longer a need for laboratory experiments: Nature has already performed a wonderful experiment: during the explosion of supernova 1987A, 99% of the star’s mass turned into a neutrino field and cold nuclear fusion occurred in the remains!

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