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LK-99 Endgame: What Happens Next & Market Size
If LK-99 is a room-temperature ambient-pressure superconductor, there are three distinct possibilities depending on its eventual engineering properties.
Here is a straightforward explanation of each scenario and estimated total market sizes in ARR:
The two limits on superconductor performance are:
- How much current it can carry
- How much magnetic field it can withstand
If either of these limits are exceeded, superconductors stop working. The scenarios are high/low field and high/low current, but you can't really get high-field without high-current, so only three scenarios
Scenario 1: Low-field, low-current ~$1.5 trn:
LK-99 saturates at relatively low fields, like 0.3T, and relatively low current densities, of ~1 amp / mm^2. It works in delicate electronics, small packages, at high efficiencies, with extremely high sensitivity.
It revolutionizes the following industries:
- Telecom hardware $650 bn; Cellphones $450 bn; Electronic Sensors $200bn; Satellites $70bn; GPUs $40bn; CPUs $20bn; Antennas $20bn.
Scenario 2: Low-field, high-current ~ $2 trn:
LK-99 can carry large current densities, on the order of >1000 amps / mm^2, but can't stand strong magnetic fields. It gains relevance in power transmission, switches, relays, and larger electrical equipment.
It revolutionizes the following industries:
Power transmission $320 bn; Wires + cables $200bn; Switches & Relays ~$ 25 bn and many others.
Scenario 3: High-field, high-current ~ $4.5 trn:
LK-99 can operate in high fields of several Tesla and high currents of >1000 amps / mm^2. It revolutionizes fundamental industries by replacing motors, generators, transportation equipment, and unlocks new energy sources like fusion.
It revolutionizes the following industries:
Power generation $1.8 trn; Electric Motors $300 bn; Rail freight $250 bn; Energy Storage $200 bn
~~~~
Some important considerations:
- "The totals don't add up" - If something works at high field, it works at low-field, and same for current. Therefore Scenario 1 is the base-case and adds to the bottom line of both other scenarios; it places the least engineering requirements on the material. All numbers for total market sizes are estimates found online in popular market reports for ~2022.
- To incorporate this material into micro-electronics means re-thinking the extremely-mature CMOS 300mm silicon wafer fabrication process, a process that would take a decade if not more to get right.
- A final consideration is the mechanical strain the material can withstand, which also affects the current and field tolerances of existing superconductors. Bulk deformations of the crystal lattice can disrupt superconducting properties - this issue has over-time been improved upon in modern high-temperature superconductors but is still present, and may limit applications in the long-run.
- Our current generation of YCBO-based high-temperature superconductors started out as low-field, low-current, highly strain-sensitive, and over 30+ years of engineering development, these now carry >1000 amps/mm^2 in fields as high as 10T (although these numbers trade off against each other). What this means is, with time, engineering, patience, and concerted effort, if TK-99 is a superconductor then Scenario #3 is highly likely within 10-20 years.
~~~~
Conservative estimate:
Current conservative estimates by an MIT professor put the probability of LK-99 being "it" at 5%.
Assuming a long-term achievement of Scenario 3, this gives an expectation value of a $225 billion annual market.
~~~~
Caveat: LK-99 is not yet confirmed to be a superconductor but has several suggestive corroborations from other experimentalists and simulations. I am reserving judgement until results are confirmed by a Department of Energy National Lab in the USA or a similarly regarded institution.
Since folks are asking:
The books I mentioned on @xai spaces are "Linear Algebra Done Right" by Axler and "Naive Set Theory" by Halmos. Other math books that I really enjoyed over the years:
"Introduction to Algorithms" by Thomas H. Cormen & Charles E. Leiserson & Ronald L. Rivest & Clifford Stein
"Information Theory, Inference and Learning Algorithms" by David J. C. MacKay
"Introduction to Quantum Mechanics" by David J. Griffiths
"Probability Theory: The Logic of Science" by E. T. Jaynes & G. Larry Bretthorst
"Topology" by James R. Munkres
"Representation Theory: A First Course" by William Fulton & Joe Harris
"Probability and Random Processes" by Geoffrey R. Grimmett & David R. Stirzaker
"Computational Complexity: A Modern Approach" by Sanjeev Arora & Boaz Barak
"A Course in Mathematical Logic for Mathematicians" by Yu. I. Manin & Neal Koblitz & B. Zilber
"Model Theory: An Introduction" by David Marker
"Category Theory" by Steve Awodey
"Quantum Computation and Quantum Information" by Michael A. Nielsen & Isaac L. Chuang
"Recursively Enumerable Sets and Degrees" by Robert I. Soare
"Introduction to Homotopy Theory" by Martin Arkowitz
"Set Theory" by Thomas Jech
"Computable Analysis: An Introduction" by Klaus Weihrauch
"Elements of Finite Model Theory" by Leonid Libkin
"Measure Theory vol 1 + 2" by Vladimir I. Bogachev
"Introduction to Smooth Manifolds" by John M. Lee
"An Introduction to Manifolds" by Loring W. Tu
"An Introduction to Algebraic Topology" by Joseph Rotman
"The Red Book of Varieties and Schemes" by David Mumford
"Categories for the Working Mathematician" by Saunders Mac Lane
"Algebra" by Saunders Mac Lane & Garrett Birkhoff
"Introductory Functional Analysis With Applications" by Erwin Kreyszig
"An Introduction to Homological Algebra" by Charles A. Weibel
"Modal Logic" by Patrick Blackburn & Maarten de Rijke & Yde Venema
"Riemannian Manifolds: An Introduction to Curvature" by John M. Lee
"Introduction to Topological Manifolds" by John M. Lee
"Analysis of Boolean Functions" by Ryan O'Donnell
"Certified Programming With Dependent Types: A Pragmatic Introduction to the Coq Proof Assistant" by Adam Chlipala
"Machine Learning: A Probabilistic Perspective " by Kevin P. Murphy
"Methods of Information Geometry" by Shun-Ichi Amari & Hiroshi Nagaoka
"Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering" by Steven Henry Strogatz
"An Introduction to Ergodic Theory" by Peter Walters
"Mathematical Control Theory: Deterministic Finite Dimensional Systems" by Eduardo D. Sontag
"Reinforcement Learning: An Introduction" by Richard S. Sutton & Andrew G. Barto
"Lectures on Polytopes" by Günter M. Ziegler
"Combinatorial Commutative Algebra" by Ezra Miller & Bernd Sturmfels
"Information, Physics, and Computation" by Marc Mézard, Andrea Montanari
"Topics in Random Matrix Theory" by Terence Tao
"A Course in P-Adic Analysis" by Alain M. Robert
"What Is a Quantum Field Theory?" by Michel Talagrand
Chris, Imprint user: "I find myself putting down social media and picking up Imprint. My brain and my development thanks you.Chris, Imprint user: "I find myself putting down social media and picking up Imprint. My brain and my development thanks you."