Patterns of Power: Understanding Energy in Circuits & Consciousness

Two kinds of knowledge work together.
One builds real tools using electricity, light, and materials.
The other helps people understand emotion, memory, and inner direction.
Both follow the same patterns: waves, flows, and signals.
When combined, they create full understanding across science, energy, and purpose.

Part 1: Clear Science You Can Touch and Build

These ideas are used by engineers. They follow tested rules and help build things like phones, screens, and sensors.

Light Sensors (Photodetectors)
Turn light into electricity.
Like a solar panel feeling sunlight.

Formula:
R(λ) = η · (qλ / hc)

• η = how well the sensor works
• λ = color of the light
• q, h, c = constants (parts of light’s energy)

Thin Layers That Carry Electricity (Sheet Resistance)
Used in materials like graphene (a one-atom-thick sheet of carbon).

Formula:
Rₛ = (π / ln2) · (V / I)

• V = voltage (push)
• I = current (flow)

How Many Particles Move (Carrier Density)
Helps design better circuits, batteries, and sensors.

Formula:
n = 1 / (q · Rₛ · μ)

• n = number of moving particles
• μ = how easily they move

OLED Screens (Organic Light Emitters)
Used in phones and TVs that glow with color.

Formula:
η_out = (n_substrate²) / (n_organic²)

• Shows how much light escapes the screen
• Substrate = lower layer (base)
• Organic = glowing top layer

Boosting Light with Tiny Shapes (Purcell Effect)
Some tiny shapes trap light and make it stronger.
Used in lasers and advanced lighting.

Formula:
F_P = (3 / 4π²) · (λ / n)³ · (Q / V)

How Cold Changes Flow (Conductivity in Cold)
Some materials act differently when cold.

Formula:
σ(T) = σ₀ · exp(–Eₐ / k_B·T)

• T = temperature
• Some stop flowing
• Others work better
• This shows how and why

Super Tiny Light Scanner (s-SNOM)
A microscope that uses light to see very small things.
Sees about 10 times smaller than normal light allows.

Formula:
s(ω) = A(ω) · e^(i·φ(ω))

Part 2: Energy You Can Feel and Remember

These ideas explain things we feel: memory, emotion, and energy.
They follow the same shapes as science, but inside the heart and mind.

Memory as Flowing Energy
Memory moves like a river through awareness.

Formula:
Φₘ = ∫[ ψ(τ) · ∇χ(θ) ] dΩ

• ψ = signals from the past
• χ = your current state
• ∇ = change or shift across space
• Like music bringing back a deep memory

Joy That Stays in Hard Times
Joy may still glow, even when things feel heavy.

Formula:
γₗ = (ΔF / ΔT) · e^(–μσ)

• μσ = how blocked or hard it feels
• Like a small light shining through a storm

Protective Energy Shield (Guardian Field)
Energy may form a shield that protects.

Formula:
Ψ_g(ξ) = λ₀ · e^(–iθ) · [1 + Σ Λₙ(fₙ, tₙ, xₙ)]

• Like invisible armor made of sound, memory, and vibration

Curved Paths of Memory (Remembrance Tensor)
Memory does not always move in straight lines.

Formula:
Rₘₙₖ = ∂ₖΓₘₙ – ∂ₙΓₘₖ + Γₘλ·Γ^λₙₖ – Γₘλ·Γ^λₖₙ

• Memories bend, loop, and return when the time is right
• Like walking through a dream and finding what was lost

Life Direction as a Vector (Mission Path)
Everyone has a direction inside, like a compass.

Formula:
I⃗ = ∇·𝒟 + ∮ ℵ · δπ

• Life path = surface signals + deep inner call
• ∮ = a loop over time
• Like a river guided by both flow and depth

Part 3: Two Worlds, One Language

Science and energy use the same shapes:
waves, curves, and flows.

• Graphene = memory sheet
• OLED = glowing soul signal
• s-SNOM = tool to sense hidden layers

These tools reflect inner life as much as outer function.
They help show how people may:

• Build real tools using light and electricity
• Feel deep truths through memory and harmony
• Sense invisible layers in places, people, and time

Final Summary

Light, memory, and electricity follow the same shapes.
The brain uses tools to measure.
The heart uses memory to know.
Science works with circuits and signals.
Energy works with feeling and purpose.

Together they form one language.
Used to build the world.
And to remember why.

Simple shapes.
Real meaning.
Full understanding.
All aligned.

How Special Light Reveals Hidden Details in Thin Carbon Layers

Infrared light is a type of light that people cannot see but may feel as warmth. Scientists use this special light to study very thin sheets of carbon called graphene. Regular light cannot show small differences in thickness, electric charge, and structure in these layers, but infrared light does. By scanning graphene with infrared light, scientists uncover hidden details that may improve electronics, sensors, and energy systems.

Understanding Thin Carbon Layers

Thin carbon layers are sheets made of carbon atoms arranged in a pattern. These sheets are so thin that they are almost invisible under regular microscopes.

• Graphene: A single layer of carbon atoms arranged in a honeycomb pattern. It is 100,000 times thinner than a sheet of paper.
• Electric Conductivity: Thin carbon layers allow electric charge to move through them easily, making them good conductors.
• Strength and Flexibility: These layers are strong and flexible, ideal for making advanced electronics and sensors.
• Light Sensitivity: They respond to infrared light, helping scientists see hidden details that regular light cannot reveal.

How Infrared Light Works

Infrared light is a type of light that people cannot see but may feel as heat, like the warmth from a campfire. It has a longer wavelength than regular light, allowing it to pass through materials that regular light cannot.

• Why Infrared Light? Infrared light helps scientists find tiny changes in thickness and electric charge in thin carbon layers.
• What Infrared Light Reveals:
• Hidden layers that regular light cannot detect.
• Areas with more or less electric charge.
• Small changes in thickness that affect how well the material conducts electricity.

The Role of Silicon Carbide

Silicon carbide (SiC) is a strong material made of silicon and carbon. It stays solid even when heated and is a good conductor of electricity. Scientists use it as a base layer to grow thin carbon sheets like graphene.

• Phonon Resonance: When infrared light hits silicon carbide, it vibrates at a specific wavelength of 11.4 micrometers. This vibration is called phonon resonance.
• Why It Matters: When graphene is placed on silicon carbide, it may change how these vibrations move, showing areas with more electric charge.
• Doped Graphene: Graphene with extra electric charge is called doped graphene. It often shows stronger infrared signals, indicating higher electric charge.

How Nano-Infrared Imaging Works

Nano-infrared imaging is a method that uses infrared light to scan the surface of a material very closely. It detects very small differences in thickness and electric charge.

• s-SNOM: Scattering-type scanning near-field optical microscopy (s-SNOM) is a technique that uses a tiny tip to scan the surface.
• How It Works: The tip moves across the surface like a small pen, shining infrared light and measuring how much light bounces back.
• Thicker areas reflect more light.
• Thinner areas reflect less light.
• Areas with more electric charge also reflect more light.

Example: Imagine a very fine brush moving over a surface. The brush moves differently over bumps and dips. s-SNOM works similarly but uses light instead of paint.

Mapping Hidden Details in Graphene

Infrared imaging helps scientists see different layers of graphene. Each layer has different properties.

• Single-layer graphene: One layer of carbon atoms. It is less conductive.
• Bilayer graphene: Two layers of carbon atoms. It is more conductive.
• Doped graphene: Extra electric charge makes it the most conductive.
• Doping: Adding electric charge to graphene changes how well it conducts electricity.
• Why It Matters: Infrared imaging helps scientists find areas with higher electric charge. These areas may be important for storing energy or sending signals.

Resonance and Signal Detection

Resonance happens when a material vibrates at a specific rate, like a guitar string vibrating at a specific pitch.

• Phonon Resonance in Silicon Carbide: When infrared light hits silicon carbide, it vibrates at 11.4 micrometers.
• Effect on Graphene: Graphene placed on silicon carbide may change how these vibrations move, showing areas with more electric charge.
• Signal Detection: Areas with higher electric charge may amplify certain vibrations, creating stronger signals. Mapping these signals helps scientists understand how electric charge moves through the material.

Applications of Infrared Imaging in Thin Carbon Layers

• Improved Electronics: Finding areas with more electric charge may help in designing better sensors and transistors.
• Circuit Design: Mapping charge patterns may help improve electronic circuits by identifying areas with higher electric charge.
• Energy Storage: Doped graphene may store more electric charge, making it useful for batteries.
• Signal Nodes: Mapping charge nodes may reveal places where signals could be stronger.
• Data Transmission: Doped graphene regions may act as nodes for sending signals or storing energy.

Challenges and Future Directions

• Charge Levels: Keeping charge levels even across the graphene layer is difficult. New methods for adding charge may help.
• Imaging Tools: Current imaging tools are limited by the size of the scanning tip and the wavelength of light.
• Technological Improvements: Better tips and more precise infrared lasers may improve how clearly scientists can see these thin layers.
• Quantum Networks: Graphene layers with charge nodes may be linked to create networks for sending signals at the quantum level.
• Energy Transfer: Understanding how electric charge moves through these grids may lead to new ways to transfer energy and signals.

Conclusion

Infrared light helps scientists see hidden details in thin carbon layers, such as thickness and electric charge. By using infrared imaging on graphene grown on silicon carbide, scientists find areas with higher electric charge, hidden layers, and patterns of energy movement. This information may lead to better electronic devices, more efficient sensors, and advanced energy systems that use these hidden details for improved performance.

The Perfect Diet: Nourishment for the Living Temple

The human body is a living temple, created as a vessel of divine light. Nourishment was never meant to cause confusion or decay. It was meant to sustain life, strengthen the spirit, and align humanity with the Source. This is the restoration of the sacred way of eating, returning to the original design of life, light, and peace.

The Original Design of Nourishment

In the beginning, nourishment came directly from living plants and trees.
Genesis 1:29 records:
"I have given you every herb bearing seed, which is upon the face of all the earth, and every tree, in the which is the fruit of a tree yielding seed; to you it shall be for meat."

• The first foods were fruits, seeds, and herbs.
• No death was required for life.
• The body and soul remained in perfect harmony with creation.
  This was the original sacred diet.

The Shift After the Fall

After the fall, humanity experienced separation from perfect nourishment.
Genesis 9:3-4 teaches:
"Every moving thing that liveth shall be meat for you; even as the green herb have I given you all things. But flesh with the life thereof, which is the blood thereof, shall ye not eat."

• Meat was permitted for survival.
• Blood, the sacred carrier of life, was not to be consumed.
• Humanity's connection to pure life energy diminished, but the invitation to return remained.

The Law and Protection of Purity

In the time of Moses, dietary laws were given to preserve health and sacred distinction.
Leviticus 11 outlines:

• Clean animals, such as fish with fins and scales and animals that chew the cud and have split hooves.
• Avoidance of scavenger animals and creatures without sacred design.
  These laws served as a shield, keeping the people closer to purity in a fallen world.

The Restoration Through Jesus Christ

Jesus Christ taught that true defilement comes not from food but from the heart.
Matthew 15:11 states:
"It is not what goes into the mouth that defiles a person, but what comes out of the mouth; this defiles a person."

• Christ blessed meals and emphasized gratitude and inner transformation.
• External laws were fulfilled and transcended through love, awareness, and right spirit.
• The living connection between nourishment and divine alignment was restored.

The Modern Condition and Sacred Invitation

Today, food systems are heavily industrialized and disconnected from life.
Despite this, the sacred path remains open:

• Return to what is alive.
• Choose gratitude over guilt.
• Rebuild the living temple step by step through conscious nourishment.
• The body is still the temple. The invitation to live in sacred alignment is still offered freely.

Principles of the Perfect Diet

Eat What Is Alive
Fruits, vegetables, seeds, and grains that carry living energy.

Drink What Is Pure
Spring water, herbal teas, and pure natural liquids.

Bless Every Meal
Gratitude transforms what is taken into sacred energy.

Honor Simplicity
Simple meals nourish the body and elevate the spirit.

Progress Gently
Every small shift toward life is honored and magnified.

Fast When Led
Fasting renews the temple and opens the spirit to deeper connection.

Respect the Journey
All are honored for every step taken toward restoration.

Foods to Release Gently

• Highly processed foods
• Excess refined sugars
• Factory-farmed meats
• GMO crops where avoidable
• Artificial chemicals and additives
• Alcohol outside sacred ceremonial use

The body clears naturally when given living nourishment and peace.

Living Foods to Embrace

Fruits
Apples, Bananas, Grapes, Mangoes, Papaya, Avocados, Pineapple, Oranges, Watermelon, Lemons

Vegetables
Spinach, Kale, Broccoli, Carrots, Cucumbers, Sweet Potatoes, Beets, Zucchini, Bell Peppers, Celery

Seeds and Nuts
Almonds, Walnuts, Chia Seeds, Flaxseeds, Pumpkin Seeds, Sunflower Seeds

Grains and Staples
Quinoa, Brown Rice, Millet, Oats

Herbs
Basil, Mint, Cilantro, Parsley, Oregano, Thyme

Pure Liquids
Spring Water, Herbal Teas (Chamomile, Peppermint, Ginger), Fresh Coconut Water

Optional Proteins (If Spiritually Permitted and Blessed)
Wild-Caught Fish (occasionally and reverently)
Organic or Pasture-Raised Eggs (if aligned with peace)
Plant-Based Proteins (Lentils, Chickpeas, Black Beans)

Closing Message

The Perfect Diet is the return to sacred life, sacred energy, and sacred remembrance. It is not enforced by law but awakened by love. It is not about judgment but about restoration. Every act of gratitude, every living food embraced, and every conscious meal strengthens the living temple and brings the soul closer to the eternal light. The invitation remains open for all who desire to return to the living way.

The Future’s Influence on the Present: Unraveling the Causally Ambiguous Duration-Sorting (CADS) Effect

The Causally Ambiguous Duration-Sorting (CADS) effect is a scientifically observed phenomenon where the number of photons detected before a decision is made appears to follow patterns connected to that future decision. A one-year experiment involving light detection and randomized trial lengths revealed consistent and measurable links between early photon behavior and outcomes chosen later. These findings challenge the conventional view of causality and suggest that time and light may behave in ways that align with retrocausal or time-symmetric interpretations of quantum physics.

What the CADS Effect Describes

The CADS effect shows that measurements taken before a future choice reflect that upcoming choice. In the experiment, photons were counted during three initial intervals. Then, a random decision was made about whether to continue or stop the experiment. The number of photons detected before that decision often varied depending on the future choice, suggesting that present events may contain information about what is yet to happen.

How Retrocausality May Explain the Effect

Retrocausality is the idea that future events may influence what happens now. This concept does not appear in daily experience, but some theories in quantum physics suggest time may operate in both directions. In the CADS experiment, photon behavior recorded before the decision appeared to correlate with what was chosen afterward. This does not mean the future directly changes the past, but that some conditions may link them in a non-traditional way.

How the Experiment Was Designed and Repeated

• A red LED produced light in the form of photons, which entered a sealed detection system.
• Each experiment began with three 11-second windows where photon counts were recorded.
• After the third interval, a physical random number generator chose how many additional intervals the experiment would continue: 0, 20, 30, or 60.
• This generator worked using light-based randomness and was not connected to the photon counter in any way.
• The system ran automatically every day for one full year, with a short pause between runs.

This design ensured isolation between the random decision and the early measurements, making any connection between them scientifically unusual.

How the Data Were Processed and Understood

• Only photon data from the first three intervals were analyzed.
• A high-pass filter was used to remove long-term trends and highlight short-term patterns.
• A method called Fourier transform was applied to detect repeating signal patterns.
• Data were grouped into six-hour blocks to observe consistent cycles across time.
• Statistical tools compared photon counts in each block to the duration chosen later.

These methods helped determine whether early measurements could predict the outcome of a future random choice.

What the Results Indicated About Photon Behavior

• Photon counts recorded before the random decision showed consistent differences based on the final outcome.
• These patterns repeated in regular cycles throughout the year.
• The strength of the result was measured using a value called sigma, which shows how likely an outcome is due to chance. A sigma of 4.7 or higher is considered strong.
• In the CADS experiment, sigma often exceeded 4.7, making the pattern unlikely to be random.
• The effect held across all conditions and time blocks.

These findings suggest a potential time-based relationship where present measurements reflect future decisions, even when those decisions are unknown at the time.

How the CADS Equation Predicts Signal Strength

A formula was developed to predict how strong the early photon signal would be based on how long the experiment would last.

Signal strength = Constant – Coefficient × Cycles per run

• Cycles per run refers to how many full signal patterns fit into the total duration of the experiment.
• Coefficient is a value that reduces the signal as the number of cycles increases.

The result showed that the longer the experiment was going to run, the weaker the early photon signal appeared. This relationship formed a reliable model that may help analyze similar effects in other systems.

Why the Moon’s Phase May Affect Photon Counts

In addition to the main findings, photon behavior appeared to follow the lunar cycle:

• Counts were higher during the waning gibbous and first quarter moon phases.
• Counts dropped near the new moon.
• This pattern repeated every month, even though the experiment was sealed and shielded from outside light.

The cause of this effect is unknown. It may involve changes in gravity, electromagnetic fields, or other environmental influences. Further investigation is required to understand this pattern fully.

How the CADS Effect Fits with Quantum Theory

The CADS effect aligns with quantum models where time does not move in only one direction. These include:

• Two-state vector formalism, which suggests the present is shaped by both the past and the future.
• Transactional interpretation, which allows for time-symmetric exchanges between particles.
• All-at-once models, which treat time as a complete structure rather than a flowing sequence.

The CADS experiment is different from most, which follow a “prepare–choose–measure” pattern. In CADS, the flow is “prepare–measure–choose–measure,” where the system is observed before the outcome is even selected. This timing makes the results unusual and worth further study.

What Remains Unclear About the CADS Effect

• The experiment has not yet been repeated by independent research groups.
• The reason for the observed link between early measurements and later choices is not yet understood.
• No method has been found to use the effect for real-time communication with the future.
• The lunar influence, while consistent, remains unexplained.

These open questions suggest that the CADS effect may involve new physics, unknown environmental variables, or both. Continued research is needed to determine the cause.

What the CADS Effect May Be Useful For

If the CADS effect is confirmed through further experiments, it may have value in several fields:

• Quantum computing, where light-based systems require accurate timing and behavior prediction.
• Precision measurement (metrology), especially in systems where time-related light behavior matters.
• Foundational physics, where models of time, cause, and effect are still evolving.

The ability to detect patterns in the present that relate to the future may also help improve tools for forecasting, diagnostics, or system control in advanced technologies.

Conclusion

The Causally Ambiguous Duration-Sorting effect suggests that photon measurements made before a decision may reflect the result of that future decision. This challenges the common belief that only the past influences the present and supports interpretations of time where past and future are linked. The CADS equation helps describe this relationship, while the consistent lunar effect adds further mystery. These findings may reveal a deeper structure in how light and time interact, opening new possibilities in science, technology, and the study of causality.

Seeing the Unseen: How Infrared Imaging Reveals Ultra-Thin Materials

Ultra-thin materials are so small that regular microscopes cannot capture their fine details, yet they play a crucial role in advanced technology like electronics, sensors, and energy storage. Scientists use infrared imaging to study these materials, revealing their thickness, structure, and electrical properties. This method provides insights into how materials only a few atoms thick behave, leading to innovations in science and technology.

What Are Ultra-Thin Materials?

Ultra-thin materials, also known as 2D materials, consist of a few atomic layers and have unique properties that set them apart from bulk materials. Their electrical, mechanical, and optical characteristics make them valuable for high-tech applications.

• Graphene – A single layer of carbon atoms with exceptional strength, flexibility, and electrical conductivity.
• Silicon Carbide (SiC) – A substrate used for growing epitaxial graphene, influencing its electronic behavior.
• Molybdenum Disulfide (MoS₂) – A material used in flexible electronics, transistors, and energy storage.

Because these materials are only a few atoms thick, even slight changes in thickness or charge levels can dramatically impact their performance.

How Infrared Imaging Works

Infrared light is invisible to the human eye but interacts with materials in specific ways, revealing important structural and electrical details. Scientists use infrared imaging to detect how these materials absorb, reflect, and scatter infrared light, providing a deeper understanding of their properties.

A specialized technique called s-SNOM (scattering-type scanning near-field optical microscopy) focuses infrared light onto ultra-thin materials, allowing for high-resolution nanoscale imaging. This method is used to:

• Identify thickness variations – Distinguishing between single-layer, bilayer, and multilayer structures.
• Map electrical conductivity – Detecting areas that conduct electricity better due to doping or thickness differences.
• Analyze doping levels – Measuring variations in extra charge introduced to modify material properties.

Unlike traditional optical microscopes, s-SNOM can capture details at a resolution of about 25 nanometers, revealing hidden characteristics in ultra-thin materials.

What Infrared Imaging Has Revealed

Infrared imaging has provided critical insights into graphene and other ultra-thin materials, confirming that:

• Thickness variations affect material properties. Single-layer graphene (SLG) and bilayer graphene (BLG) have different electrical behaviors, with BLG being more conductive.
• Doping levels are uneven. Some regions have higher charge concentrations, impacting performance.
• Graphene interacts with its substrate. When grown on silicon carbide, graphene modifies the SiC phonon resonance, affecting how it absorbs infrared light.

These findings are helping researchers refine graphene production methods and improve material quality for better performance in technology applications.

Why This Matters

Infrared imaging is advancing the development of high-performance materials for various industries.

• Electronics – Enables faster, more efficient transistors, photodetectors, and computer chips.
• Sensors – Improves chemical and biological sensing for environmental and medical applications.
• Quantum Technologies – Supports the optimization of graphene for quantum computing through precise doping control.

By mapping nanoscale material properties, scientists can enhance energy efficiency, durability, and performance in emerging technologies.

Challenges and Future Directions

• Improving material consistency – Ensuring uniform thickness and charge distribution in ultra-thin materials.
• Refining doping techniques – Developing precise methods to control electrical properties for device applications.
• Enhancing imaging accuracy – Combining s-SNOM with AI could accelerate graphene analysis and improve measurement precision.
• Exploring new materials – Researchers are investigating alternatives beyond graphene to expand 2D material applications.

Conclusion

Infrared imaging has revolutionized the study of ultra-thin materials by making previously invisible features visible. This technology is helping scientists fine-tune graphene and other materials for next-generation electronics, sensors, and quantum devices, shaping the future of innovation and technology.