A Conceptual Architecture Integrating High-Efficiency Power Conversion, Thermal Transport, Radiative Cooling, and Heat Reuse
Author: Kinuyo Matsushima
Contributing AI Systems:
KIMI AI, Genspark, Gemini, Grok, Meta AI, Mistral, Perplexity, ChatGPT, Copilot, pi.ai, Claude
Abstract
The rapid expansion of artificial intelligence is creating two closely related infrastructure challenges for data centers: rapidly increasing electricity demand and increasing thermal-management requirements associated with high-density computing.
This paper proposes a conceptual architecture for future AI data centers designed to minimize operational water consumption by integrating high-efficiency power conversion and distribution, closed-loop thermal management, phase-change thermal storage, radiative heat rejection, geothermal or other long-duration thermal sinks, and heat reuse within a unified building system.
A central principle of the proposed architecture is that electrical losses ultimately become heat. Therefore, improving the efficiency of transformers, power converters, distribution systems, and point-of-load conversion can reduce the amount of heat that must subsequently be removed by the cooling system.
The proposed facility uses a cylindrical, vertically organized architecture inspired by the compact and highly integrated appearance of spacecraft and other advanced industrial systems. A central Thermal Spine provides a conceptual pathway for transporting heat from high-density GPU areas toward upper-level heat-rejection systems, thermal-storage systems, and heat-reuse interfaces.
Radiative cooling is proposed as one component of the overall heat-rejection system rather than as the sole cooling mechanism. On Earth, radiative panels can emit thermal radiation toward the sky, particularly through the atmospheric infrared window around approximately 8–13 μm, although their performance is affected by atmospheric conditions, cloud cover, humidity, surface temperature, and available radiative area.
The concept was discussed and evaluated collaboratively by eleven AI systems. Their discussions converged on the importance of reducing electrical conversion losses and treating power infrastructure and thermal management as interconnected engineering problems.
This paper presents the architecture as a conceptual research proposal, not as a validated commercial design. Detailed engineering simulations, thermal measurements, economic analysis, reliability studies, and field demonstrations would be required before practical deployment.
1. Introduction
Artificial intelligence is driving a rapid increase in computational demand. Modern AI systems require increasingly powerful GPU and accelerator clusters, which in turn require substantial electrical infrastructure and increasingly sophisticated thermal-management systems.
Two infrastructure challenges are particularly important:
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The rapid growth of electrical demand and the limitations of power-conversion and distribution infrastructure
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The increasing heat density of AI computing and the associated cooling requirements
These challenges are often considered separately.
Power engineers focus on transformers, converters, distribution systems, and grid interfaces, while thermal engineers focus on cooling loops, heat exchangers, chillers, heat rejection, and thermal storage.
However, these systems are physically connected.
Every watt of electrical power that is lost through resistance, switching losses, transformer losses, semiconductor losses, or other inefficiencies ultimately appears largely as heat.
Therefore, reducing electrical losses can reduce the thermal load that must subsequently be removed.
The central concept of this paper is consequently:
AI data-center power infrastructure and thermal infrastructure should be designed as one integrated energy system rather than as independent subsystems.
The proposed architecture combines high-efficiency power conversion with water-minimizing thermal management and heat reuse.
2. Design Philosophy
The proposed system is based on five principles.
2.1 Reduce heat generation at the source
The first objective is not simply to remove heat more efficiently.
It is to prevent unnecessary heat from being generated.
Potential approaches include:
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High-efficiency solid-state transformers
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Silicon-carbide (SiC) power semiconductors
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Gallium-nitride (GaN) devices where appropriate
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High-efficiency power converters
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High-voltage DC distribution
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Optimized power-distribution architecture
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Point-of-load conversion
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Efficient switching strategies
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Low-loss magnetic materials
The precise technology selection would depend on voltage, power level, frequency, cost, reliability, and safety requirements.
3. Integrated Power and Thermal Architecture
The proposed data center is organized around the relationship:
Electrical Power → Computing → Heat → Thermal Transport → Heat Rejection / Heat Reuse
Instead of viewing cooling as an independent mechanical system, the building treats the movement and destination of heat as a fundamental part of the architectural design.
The conceptual architecture consists of:
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Grid or renewable-energy input
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High-efficiency transformer and power-conversion systems
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High-voltage DC distribution
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Point-of-load conversion
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High-density GPU computing decks
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Closed-loop thermal transport
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Central Thermal Spine
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Phase-change thermal storage
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Radiative heat-rejection surfaces
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Geothermal or other long-duration thermal sinks
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Heat-reuse systems
4. Transformer and Power-Distribution Efficiency
4.1 Solid-State Transformers
Solid-state transformers (SSTs) are considered as a potential component of the proposed architecture.
Compared with conventional transformer architectures, SST-based systems can provide advanced power-conversion and control functions, depending on the specific implementation.
Potential advantages include:
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Power-flow control
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Voltage conversion
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Power-quality management
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Integration with DC distribution
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Potential reduction of conversion stages
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Compact integration with advanced semiconductor devices
However, SSTs also introduce their own switching and conversion losses, thermal-management requirements, cost, and reliability considerations.
Therefore, the objective is not simply to replace every conventional transformer with an SST.
Rather:
The optimal power-conversion architecture should minimize total system losses while maintaining reliability, maintainability, safety, and economic feasibility.
4.2 SiC and GaN Power Electronics
Silicon-carbide and gallium-nitride semiconductor technologies may enable high-efficiency power conversion in appropriate voltage and power ranges.
Potential applications include:
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AC/DC conversion
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DC/DC conversion
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High-frequency switching
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Point-of-load power conversion
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Power supplies for accelerator systems
The actual benefit would need to be evaluated at the system level rather than assumed solely from semiconductor efficiency.
4.3 High-Voltage DC Distribution
High-voltage DC distribution is another potential component.
A conceptual architecture could distribute electrical power at a suitable DC voltage and perform final conversion close to the computing equipment.
An 800 V-class DC architecture is one possible design direction, although the appropriate voltage would depend on safety requirements, equipment standards, insulation, protection systems, and overall system design.
Potential benefits include reducing unnecessary conversion stages and simplifying some power-distribution architectures.
4.4 Amorphous-Metal Transformer Cores
Amorphous-metal magnetic cores may reduce certain transformer losses compared with conventional magnetic materials.
They could therefore be considered where their electrical, thermal, mechanical, manufacturing, and economic characteristics are appropriate.
4.5 High-Temperature Superconducting Cables
High-temperature superconducting cables are considered a future technology option rather than a required component of the proposed architecture.
Their very low electrical resistance under appropriate operating conditions is attractive.
However, superconducting systems require cryogenic infrastructure, which itself consumes energy and introduces additional complexity.
Consequently, the total system efficiency must be evaluated before such technology can be justified for a particular data center.
5. The Relationship Between Electrical Loss and Cooling Load
One of the most important principles of this proposal is straightforward:
Electrical losses ultimately become heat.
For example, consider a hypothetical AI computing facility consuming 100 MW of electrical power.
If the relevant power-conversion and distribution losses were approximately 2%, the associated electrical loss would be:
100 MW × 0.02 = 2 MW
That 2 MW ultimately appears predominantly as heat.
If improvements reduced the corresponding losses to 1%, the loss would become:
100 MW × 0.01 = 1 MW
The difference would be approximately:
1 MW of heat
that no longer needs to be removed from the facility as a result of those avoided electrical losses.
This example is illustrative rather than a prediction of any particular data center.
It demonstrates the central design principle:
Improving power-conversion efficiency can reduce thermal-management requirements before the cooling system even begins removing heat.
Therefore, future AI data centers should evaluate electrical efficiency and thermal efficiency together.
6. Water-Minimizing Thermal Management
The proposed architecture does not assume that one cooling technology will solve the entire thermal problem.
Instead, several thermal-management mechanisms are combined.
These may include:
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Closed-loop liquid cooling
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Two-phase cooling where technically and environmentally appropriate
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Dielectric-fluid cooling
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Heat pipes
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Vapor chambers
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Phase-change materials
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Radiative heat rejection
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Natural or mechanically assisted convection
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Geothermal heat rejection
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Thermal energy storage
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Heat reuse
The goal is to eliminate or greatly reduce dependence on evaporative cooling towers and other systems that continuously consume significant quantities of water.
For this reason, the more technically cautious description of the architecture is:
Near-Zero-Operational-Water AI Data Center
rather than an absolute claim that every form of water use can be eliminated.
7. Radiative Cooling
7.1 Terrestrial Radiative Cooling
Radiative cooling is a key component of the proposed architecture.
Certain surfaces can emit thermal radiation toward the sky, particularly within portions of the atmospheric infrared window around approximately 8–13 μm.
Under favorable atmospheric conditions, a suitably designed radiative surface can reject heat without consuming water.
However, terrestrial radiative cooling is fundamentally different from radiative cooling in outer space.
On Earth, performance depends on:
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Ambient air temperature
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Humidity
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Cloud cover
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Atmospheric transparency
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Surface emissivity
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Solar radiation
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Available panel area
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Temperature difference
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Local weather conditions
Therefore, radiative cooling should be considered a supplementary or integrated heat-rejection mechanism, rather than assumed to be sufficient by itself for the entire thermal load of a large AI data center.
7.2 Radiative Panels and Solar Panels Are Different Systems
The proposed building may include both:
Solar photovoltaic panels
Their purpose is:
Sunlight → Electricity
Radiative cooling panels
Their purpose is:
Thermal energy → Infrared radiation → Sky
These two functions should be represented separately in engineering drawings.
A roof could potentially contain both systems, but their orientation, surface properties, thermal behavior, and operating objectives are different.
8. Cylindrical “Spaceship-Style” Data Center Architecture
The proposed building uses a cylindrical geometry inspired by the compact and vertically integrated appearance of spacecraft and advanced industrial facilities.
This geometry is not claimed to be universally superior to rectangular data-center architecture.
Rather, it is proposed as a conceptual architecture for investigating whether a cylindrical arrangement can facilitate:
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Vertical thermal transport
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Centralized heat routing
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Symmetrical equipment organization
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Compact mechanical infrastructure
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Distributed access around a central thermal pathway
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Integration of rooftop thermal systems
The cylindrical architecture therefore functions as a research hypothesis requiring comparison with conventional rectangular facilities.
9. Exterior Architecture
The proposed exterior consists of a cylindrical or approximately cylindrical building envelope.
The upper structure may contain:
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Radiative cooling surfaces
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Solar photovoltaic systems
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Heat-rejection equipment
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Heat-pipe interfaces
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Mechanical ventilation structures
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Maintenance walkways
The roof is designed as an energy and thermal-management platform rather than simply as a protective building surface.
10. Vertical Cross-Section
The vertical architecture can be conceptually divided into several zones.
10.1 Radiative Cooling Roof
The uppermost level contains radiative heat-rejection surfaces.
These surfaces are intended to reject part of the facility's thermal energy toward the sky through infrared radiation.
The design should account for:
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Atmospheric conditions
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Solar loading
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Panel emissivity
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Maintenance
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Weather protection
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Structural loading
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Available radiative area
The radiative roof therefore forms one layer of a hybrid thermal-management system.
10.2 GPU Computing Deck
The GPU decks contain high-density accelerator systems.
Because AI accelerators can produce very high heat fluxes, direct thermal transport from the GPU package to a liquid or other high-performance cooling medium may be required.
A conceptual arrangement could use:
GPU → cold plate / immersion or two-phase interface → closed-loop heat transport → Thermal Spine
The exact cooling fluid and architecture would depend on the selected equipment and engineering requirements.
The concept does not require the use of CO₂ or liquid metals as the default cooling medium.
Those technologies could instead be treated as specialized research options.
11. Thermal Spine
The Thermal Spine is the central conceptual element of the building.
It functions as a vertical thermal transport corridor connecting the high-density computing decks with:
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Thermal storage
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Heat exchangers
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Radiative heat-rejection systems
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Geothermal systems
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Heat-reuse systems
The basic concept is:
GPU Heat → Local Heat Collection → Thermal Spine → Thermal Buffer / Heat Rejection / Heat Reuse
The Thermal Spine should not be interpreted as a single physical pipe in a finished engineering design.
It represents an integrated thermal transport infrastructure that could contain multiple independent loops and safety zones.
12. Phase-Change Material Deck
Phase-change materials (PCMs) can absorb thermal energy while undergoing a phase transition.
They can therefore act as thermal buffers.
Potential uses include:
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Short-duration peak-load buffering
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Reducing instantaneous heat-rejection requirements
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Shifting thermal loads in time
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Supporting periods of unfavorable weather
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Supporting intermittent renewable electricity generation
However, PCM storage has finite energy capacity.
It therefore functions as a thermal buffer, not as an unlimited heat sink.
The PCM system would need to be sized according to:
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Thermal load
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Desired storage duration
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Phase-change temperature
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Material properties
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Charging/discharging rate
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Long-term stability
13. Geothermal and Long-Duration Thermal Sinks
Deep geothermal systems may provide another pathway for heat rejection or thermal storage.
Potential configurations include:
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Borehole thermal storage
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Ground-source heat exchange
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Seasonal thermal storage
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Deep geothermal heat rejection
However, the ground is not an unlimited heat sink.
Continuous heat injection can gradually increase surrounding ground temperature and reduce the effectiveness of the system.
Therefore, geothermal integration should be evaluated using:
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Geological conditions
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Thermal conductivity
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Groundwater movement
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Heat-storage capacity
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Seasonal thermal cycles
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Long-term temperature evolution
Geothermal systems are consequently presented as site-dependent technologies, not universal solutions.
14. Horizontal Cross-Section
The cylindrical building can also be analyzed through horizontal cross-sections.
14.1 Transformer and Power Room
The lower section may contain power-conversion equipment arranged around a central infrastructure zone.
Possible components include:
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SST modules
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Conventional transformers where appropriate
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DC conversion equipment
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Protection systems
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Switchgear
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Power-quality equipment
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Energy-storage interfaces
Radial arrangement may provide compact cable routing, although conventional linear arrangements may be more practical depending on equipment and maintenance requirements.
14.2 Thermal Storage Deck
The PCM systems can be arranged around the Thermal Spine.
This arrangement provides multiple thermal-storage modules rather than one single centralized tank.
Such modularity could potentially improve:
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Maintenance
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Redundancy
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Expansion
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Fault isolation
These advantages would require detailed engineering validation.
14.3 GPU Deck
GPU racks may be arranged in concentric or semi-concentric patterns around the Thermal Spine.
The purpose is to shorten thermal transport distances and provide multiple independent cooling loops.
However, equipment accessibility, airflow, fire protection, cable routing, structural loading, and maintenance must remain primary design constraints.
14.4 Roof Deck
The roof can integrate multiple energy and thermal functions.
Potential systems include:
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Radiative cooling surfaces
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Solar photovoltaic panels
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Heat exchangers
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Heat-pipe interfaces
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Mechanical equipment
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Maintenance infrastructure
Solar generation and radiative cooling should remain conceptually separate even if they coexist on the same roof.