The periodic table for the AI infrastructure age
The AI future is built from elements.
Periodic Engine maps the elements powering critical industries, and the supply-chain risk hiding inside them.
Ranked by strategic importance. Scored for supply-chain risk. Mapped to the industries that depend on them.
Selected Element
Gallium
Atomic Number 31
Primary industry exposure
Modeled intelligence score
Status
CriticalConfidence
Last reviewed
May 12, 2025
Supply context (static modeled)
Key use cases
- - RF amplifiers & power electronics
- - Semiconductor fabrication (GaAs, GaN)
- - Optoelectronics & LEDs
- - Advanced defense systems
Top supply regions
Static modeled supply context
Why it matters
Gallium
Semiconductors
RF systems
CriticalHelium
MRI machines
Cryogenics
HighNeodymium
Motors
Drones, defense
CriticalCobalt
Batteries
Superalloys
HighCopper
Grid
AI data centers
CoreSilicon
Chips
Solar, electronics
CoreGermanium
Fiber optics
Infrared, space
HighMost teams building with these technologies have never mapped the element-level dependencies behind them.
Periodic Engine shows what you are depending on before it becomes a problem.
How do you want to start?
Start with an element
Investigate Gallium, Lithium, Copper, Helium, Germanium, and the rest of Genesis 12.
Explore elements ->
Start with an industry
See the materials behind AI, defense, telecom, energy, semiconductors, and more.
Explore industries ->
Start with a question
Ask what powers a system, where the risk is, and which elements deserve attention.
Explore example questions ->
Question-first intelligence flow, preview version.
Genesis 12 Elements
The first materials mapped across risk, dependency, and strategic importance.
High strategic and supply-chain exposure
Important with elevated risk
Foundational infrastructure element
Monitor closely
Visible, not modeled yet
What Periodic Engine does
Ranks strategic elements
By civilization importance, exposure, and supply-chain risk.
Maps industry dependency
Across AI, defense, telecom, energy, health, and more.
Explains supply-chain risk
With sources, confidence levels, and last-reviewed dates.
Shows substitution risk
Replacement difficulty by use case and tradeoff.
Connects sources
USGS, DOE, IEA, EU, RSC, and peer-reviewed data.
Explore by industry
AI / Data Centers
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Defense / Aerospace
Explore ->
Telecom
Explore ->
Semiconductors
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Energy / Grid
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More industries coming soon.
Who we serve
Government / Public Sector
Understand strategic materials, defense exposure, industrial policy, and supply-chain dependency.
Review methodology ->
Commercial / Industry Teams
Map the materials behind products, suppliers, factories, and critical infrastructure.
Explore industries ->
Investors / Diligence
Find hidden material risk before it shows up in a pitch deck or diligence call.
Assess risk early ->
Analysts / Researchers
Move from scattered sources to ranked, explainable element intelligence.
Build informed briefs ->
Founders / Operators
Understand what your product depends on before it becomes a constraint.
Investigate dependencies ->
Modeled intelligence scores
Not government ratings
Source registry
Linked to original data
Confidence levels
High / Medium / Low
Last-reviewed dates
Every element
Methodology published
How scores are calculated