AI responses may confabulate and track hyperlink activity.

While "orgonite" is considered a pseudoscientific concept, you can model its theoretical physical structure (a random array of metallic particles in a dielectric resin) using high-end Computational Electromagnetics (CEM) software rather than standard electrochemical tools.

To draft and animate this specific 3D schematic, the following software suites are most capable:

COMSOL Multiphysics (AC/DC Module): This is the gold standard for your specific requirements. You can use its Geometry tools to create a random distribution of 3D objects (acting as your secondary inductors) within a block (the dielectric medium). It allows for 3D inductor modeling and can simulate how these particles interact with external electromagnetic fields to visualize potential "filtration" or attenuation effects.

Ansys HFSS: A premier 3D electromagnetic field solver used for complex high-frequency structures. It is highly effective for simulating how random metallic arrays scatter or absorb electromagnetic waves, which aligns with your goal of animating "white noise filtration" activity.

CST Studio Suite (SIMULIA): Offers specialized solvers for charged particle dynamics and optical frequencies. It is excellent for visualizing wave behavior in "matter" and can generate high-quality animations of electric and magnetic fields as they pass through composite materials.

Remcom XFdtd: This full-wave 3D EM simulation software is specifically designed for analyzing EM fields in complex, high-fidelity devices. It includes a specialized FDTD solver that is efficient for problems with a high number of unknowns, such as a "random array" of many small components.

Implementation Strategy

Drafting: Use the software's internal CAD tools or import a 3D model. You can noscript a randomized placement of metallic spheres or coils (the "secondary inductors") within a defined resin volume.
Material Properties: Assign a high dielectric constant to the medium (resin) and high conductivity/permeability to the metal particles.

Simulation: Apply a White Gaussian Noise signal as the input electromagnetic field.

Animation: Use "Field Plots" to animate the Poynting vector or electric field lines, showing how energy is dissipated or redirected by the internal array.

Are you looking for a free/open-source alternative (like OpenEMS) or a commercial-grade suite for professional prototyping?

AI Overview
+20
The
Nash Equilibrium (NE) is a central concept in game theory describing a stable state in a non-cooperative game where no player can improve their outcome by unilaterally changing their strategy, given the other players' strategies remain unchanged. The "long and short of it" is that every player is making their best possible decision as a response to the decisions of everyone else, creating a point of stability where individual incentives to deviate are non-existent.
History and Timeline
The concept has roots predating John Nash's formal definition, but his work in the 1950s was the breakthrough that expanded its application.

1838: Antoine Augustin Cournot introduced a similar idea (Cournot equilibrium) in his theory of oligopoly, focused on firms maximizing profit based on competitors' output.
1944: John von Neumann and Oskar Morgenstern published Theory of Games and Economic Behavior, focusing on two-person, zero-sum games and mixed-strategy equilibria.
1950: John Nash, a mathematics graduate student at Princeton, introduced his equilibrium concept for n-person non-cooperative games in a one-page paper.
1951: Nash published "Non-Cooperative Games" in Annals of Mathematics, where he proved that every finite game has at least one Nash equilibrium (pure or mixed strategy) using the Kakutani fixed-point theorem.
1960s-1980s: Other theorists, including John Harsanyi, Reinhard Selten, Robert Aumann, David Kreps, and Robert Wilson, refined and extended the concept with ideas like subgame perfect equilibrium and Bayesian Nash equilibrium to address more complex scenarios (e.g., incomplete information, dynamic inconsistencies).
1994: Nash, Harsanyi, and Selten were awarded the Nobel Memorial Prize in Economic Sciences for their pioneering analysis of equilibria in non-cooperative game theory.

Comparative Studies
The Nash Equilibrium is the most widely used solution concept for non-cooperative games, but it has led to other, more refined concepts:

Dominant Strategy: A strategy that yields the best outcome for a player regardless of the opponent's strategy. The Nash equilibrium is a broader concept; a game may not have a dominant strategy equilibrium, but it will have a Nash equilibrium.
Pareto Optimal Outcome: An outcome where no player's payoff can be improved without hurting another player. A Nash equilibrium is not necessarily Pareto optimal (e.g., the Prisoner's Dilemma, where both prisoners confessing is the NE, but both staying silent is the Pareto optimal outcome).
Subgame Perfect Equilibrium: A refinement for dynamic (sequential) games that eliminates Nash equilibria based on "non-credible threats"—strategies a rational player would not actually carry out at a later stage of the game.
Strong Nash Equilibrium: A concept where no coalition of players, not just a single player, can cooperatively deviate to benefit all members.

Interdisciplinary Applications
The Nash Equilibrium has profoundly impacted a wide array of fields, serving as a unifying theory across social sciences:

Economics: Used to model market competition (oligopolies), auction theory, bargaining, and the provision of public goods.
Political Science: Applied to analyze arms races, international diplomacy, negotiation strategies, and voting behavior.
Biology: The concept of an Evolutionarily Stable Strategy (ESS) is a refinement of the Nash equilibrium applied to population dynamics, explaining long-term stability of behavioral traits in species.
Computer Science and Artificial Intelligence: Used in algorithm design, network traffic analysis, and robot navigation in crowds.
Other Areas: Applied to understanding everyday phenomena like driving conventions (driving on the left or right side of the road), social conventions like forming queues, and the adoption of technical standards.

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AI Overview

Hennig Brandt and the Discovery of Phosphorus | Science ...
The alchemy of urine drinking, a real 17th-century pursuit for the Philosopher's Stone, a legendary substance for turning lead to gold, led to the accidental discovery of phosphorus by alchemist Hennig Brand; he boiled down massive amounts of urine, hoping to extract gold, but instead found a glowing, waxy substance that produced light and flame, revealing the element's existence.
The Process & Beliefs

The Goal: Alchemists, including Brand, believed urine's golden color and natural salts might hold the key to the Philosopher's Stone, a substance said to transmute metals or grant immortality.
Brand's Experiment: He collected huge quantities (thousands of gallons) of urine from local pubs, boiled it down to a thick syrup, and heated the residue intensely.
The Discovery: This heating process released a white vapor that condensed into a waxy, glowing substance, which Brand named phosphorus (light-bearer).

Significance

Accidental Science: While failing to find the Philosopher's Stone, Brand's urine-based experiment revealed a new element, phosphorus, a key step in modern chemistry.
Symbolism: For some modern interpretations, urine alchemy symbolizes spiritual transformation, turning the "base" self (like urine) into a purified, enlightened state (the Stone).

https://open.substack.com/pub/lisevoldeng/p/dont-worry-boys-are-hard-to-find?r=1w188r&utm_medium=ios&shareImageVariant=overlay

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