Thermal Management Materials for AI and Power Electronics: Global Market 2027-2037

Table of Contents

1 EXECUTIVE SUMMARY

• 1.1 Scope of this report
• 1.2 Market size and growth
• 1.3 Key findings
• 1.4 The heat-removal pathway in numbers
• 1.5 AI hardware versus power electronics
• 1.6 Research priorities
• 1.7 Competitive landscape summary

2 INTRODUCTION AND METHODOLOGY

• 2.1 Report scope and definitions
  • 2.1.1 What the report covers
  • 2.1.2 What the report excludes
  • 2.1.3 Device and system boundaries
• 2.2 The heat-removal pathway framework
  • 2.2.1 Four positions in the heat path
  • 2.2.2 Mapping the eight subcategories to the pathway
  • 2.2.3 Market structure by pathway position
• 2.3 Thermal resistance fundamentals
  • 2.3.1 The series resistance stack
  • 2.3.2 Worked example: datasheet conductivity versus package-level performance
  • 2.3.3 Heat flux versus total power
  • 2.3.4 Spreading resistance
  • 2.3.5 Thermal boundary resistance
  • 2.3.6 Why datasheet bulk conductivity misleads
• 2.4 Measurement and characterisation methods
• 2.5 AI and power-electronics thermal paths compared
  • 2.5.1 The lidded flip-chip accelerator package
  • 2.5.2 The power-module stack
  • 2.5.3 Double-sided cooling
• 2.6 Research methodology
  • 2.6.1 Primary and secondary research
  • 2.6.2 Bottom-up forecasting approach
  • 2.6.3 Base year, forecast period and currency
  • 2.6.4 Segment definitions: applications
  • 2.6.5 Segment definitions: regions and countries
  • 2.6.6 Limitations
• 2.7 Relationship to other Future Markets reports

3 MARKET DRIVERS AND APPLICATION REQUIREMENTS

• 3.1 The AI accelerator power roadmap
  • 3.1.1 Package power by generation
  • 3.1.2 Heat flux, hotspots and thermal headroom
  • 3.1.3 HBM stacks
  • 3.1.4 2.5D/3D packaging and CoWoS-L growth
• 3.2 Rack power density and the shift to liquid cooling
  • 3.2.1 From 40 kW to 600 kW per rack
  • 3.2.2 The cooling ladder
  • 3.2.3 What liquid cooling changes for materials
• 3.3 Data-centre power infrastructure
  • 3.3.1 800 V DC distribution
  • 3.3.2 Solid-state transformers, SiC/GaN power supplies and battery backup
• 3.4 EV and transport power electronics
  • 3.4.1 SiC traction inverters and 800 V platforms
  • 3.4.2 Power cycling and lifetime
  • 3.4.3 Beyond the traction inverter
• 3.5 Renewable, grid and industrial power electronics
• 3.6 Telecom, RF and defence power devices
• 3.7 Wide-bandgap semiconductor adoption and why it shifts materials
  • 3.7.1 Higher junction temperatures and stiffer dies
  • 3.7.2 CTE mismatch
  • 3.7.3 GaN in power conversion
  • 3.7.4 Wide-bandgap adoption outlook
• 3.8 Requirement matrices by application
• 3.9 Sustainability and regulatory drivers
  • 3.9.1 PFAS restrictions
  • 3.9.2 Silicone contamination and siloxane regulation
  • 3.9.3 Lead and hazardous-substance rules
  • 3.9.4 Energy efficiency and data-centre rules
  • 3.9.5 Critical-material supply and export controls
• 3.10 Restraints and challenges
• 3.11 From device demand to materials content
  • 3.11.1 Thermal-material content per device
  • 3.11.2 Materials-to-application mapping
• 3.12 Market by application, 2027–2037
  • 3.12.1 Forecast
  • 3.12.2 Interpretation

4 POLYMER-BASED THERMAL-INTERFACE MATERIALS

• 4.1 Scope and position in the heat-removal pathway
• 4.2 Product forms
  • 4.2.1 Thermal greases
  • 4.2.2 Thermal gels: one-part, two-part and cure-in-place
  • 4.2.3 Dispensable gap fillers
  • 4.2.4 Gap pads
  • 4.2.5 Thermally conductive adhesives and tapes
• 4.3 Matrix chemistries: silicone and silicone-free
• 4.4 Fillers and filler packing
• 4.5 Key research questions
  • 4.5.1 Bond-line thickness
  • 4.5.2 Contact resistance
  • 4.5.3 Pump-out
  • 4.5.4 Dry-out, oil bleed and siloxane volatiles
  • 4.5.5 Lifetime stability and qualification
• 4.6 Applications
  • 4.6.1 AI accelerators and advanced packaging
  • 4.6.2 AI servers and data-centre IT equipment
  • 4.6.3 Data-centre power infrastructure
  • 4.6.4 EV and transport power electronics
  • 4.6.5 Renewable, grid, industrial, telecom, RF and defence
  • 4.6.6 Dispensing automation
• 4.7 Commercial product benchmarks
• 4.8 Prices
• 4.9 Supply chain, raw materials and regulation
• 4.10 Recent developments, 2024–2026
• 4.11 Supplier landscape and market shares
• 4.12 Market forecast
• 4.13 SWOT analysis
• 4.14 Outlook and research priorities

5 PHASE-CHANGE INTERFACE MATERIALS

• 5.1 Scope, definitions and working principle
• 5.2 Formulation and transition-temperature design
• 5.3 Material classes
  • 5.3.1 Polymer phase-change films and pads
  • 5.3.2 Reinforced PCMs on foil or carrier
  • 5.3.3 Screen- and stencil-printable PCMs
  • 5.3.4 Low-melting metal-alloy PCMs versus organic PCMs
  • 5.3.5 Pre-applied PCM on power modules
• 5.4 Key research questions
  • 5.4.1 Conformability and first-melt conditioning
  • 5.4.2 Repeated cycling and thixotropic behaviour
  • 5.4.3 Leakage and pump-out compared with grease
  • 5.4.4 Stable contact pressure
  • 5.4.5 Reworkability
  • 5.4.6 Bond-line thickness after reflow-like conditioning
• 5.5 AI server adoption
• 5.6 Power modules and power electronics
• 5.7 Commercial product benchmarks
• 5.8 Recent developments, 2024–2026
• 5.9 Suppliers and market shares
• 5.10 Market forecast
• 5.11 SWOT analysis
• 5.12 Outlook

6 METALLIC INTERFACE AND ATTACHMENT MATERIALS

• 6.1 Scope and position in the heat-removal pathway
• 6.2 Indium and indium-alloy solder TIM1
  • 6.2.1 Metallisation stacks
  • 6.2.2 Reflow, voiding and assembly sequencing
• 6.3 Liquid metals
  • 6.3.1 Reactions, oxidation and confinement
  • 6.3.2 Liquid metal at TIM1.5 in AI accelerators
• 6.4 Low-melting alloys and phase-change metals
• 6.5 Conventional solders for die, substrate and lid attach
• 6.6 Silver sintering
  • 6.6.1 Pressure versus pressureless
  • 6.6.2 Silver sinter in AI packages
• 6.7 Copper sintering and active copper
• 6.8 Transient liquid phase bonding
• 6.9 Large-area sintering of substrate to baseplate and cooler
• 6.10 Silver-filled hybrid materials
• 6.11 Key research questions
  • 6.11.1 Low thermal resistance: interfaces, voids and intermetallics
  • 6.11.2 Joining temperature: reflow profiles versus die and HBM limits
  • 6.11.3 Fatigue: power cycling, CTE mismatch and creep
  • 6.11.4 Compatibility with adjoining surfaces
• 6.12 AI versus power-electronics requirements
• 6.13 Raw materials: indium, gallium and silver
• 6.14 Products and suppliers
• 6.15 Recent developments, 2024–2026
• 6.16 Market forecast, 2027–2037
  • 6.16.1 Technology sub-split
• 6.17 SWOT analysis
• 6.18 Outlook and research priorities

7 CARBON-BASED HEAT SPREADERS

• 7.1 Role in the heat-removal pathway
• 7.2 Material families
  • 7.2.1 Natural graphite sheets and foils
  • 7.2.2 Synthetic graphite sheets from polyimide
  • 7.2.3 Graphene films and graphene-containing structures
  • 7.2.4 Vertically aligned graphite and graphene interface materials
  • 7.2.5 Carbon nanotube arrays
  • 7.2.6 Pitch-based carbon fibre
  • 7.2.7 Carbon–metal composites and encapsulated annealed pyrolytic graphite
• 7.3 Property benchmarks
• 7.4 Key research questions
  • 7.4.1 In-plane versus through-plane conductivity
  • 7.4.2 Integration: lamination, adhesives, thickness and encapsulation
  • 7.4.3 Electrical insulation requirements
• 7.5 Applications
  • 7.5.1 AI accelerators and advanced packaging
  • 7.5.2 AI servers and data-centre IT equipment
  • 7.5.3 Data-centre power infrastructure
  • 7.5.4 EV and transport power electronics
  • 7.5.5 Renewable, grid and industrial power electronics
  • 7.5.6 Telecom, RF and defence power devices
• 7.6 Products and suppliers
• 7.7 Costs and pricing
• 7.8 Recent developments, 2024–2026
• 7.9 Supplier landscape
• 7.10 Market forecast, 2027–2037
• 7.11 SWOT analysis
• 7.12 Outlook

8 DIAMOND-BASED THERMAL MATERIALS

• 8.1 Role in the heat-removal pathway
• 8.2 Material families and grades
  • 8.2.1 Polycrystalline CVD diamond heat spreaders
  • 8.2.2 Single-crystal diamond
  • 8.2.3 Diamond thin films and coatings on silicon and GaN
  • 8.2.4 GaN-on-diamond and diamond-on-silicon wafers
  • 8.2.5 Diamond interposers and substrates
  • 8.2.6 Metal–diamond composites
  • 8.2.7 Diamond particle fillers in TIMs and nanodiamond
  • 8.2.8 Measuring diamond thermal performance
• 8.3 Production methods and scalability
• 8.4 Key research questions
  • 8.4.1 Cost
  • 8.4.2 Scalable production
  • 8.4.3 Bonding quality
  • 8.4.4 Thermal resistance at the diamond–device interface
• 8.5 Applications
  • 8.5.1 AI accelerators and advanced packaging
  • 8.5.2 AI servers and data-centre IT equipment
  • 8.5.3 Data-centre power infrastructure and EV power electronics
  • 8.5.4 Telecom, RF and defence power devices
• 8.6 Recent developments, 2024–2026
• 8.7 Supplier landscape
• 8.8 Market forecast, 2027–2037
• 8.9 SWOT analysis
• 8.10 Outlook

9 THERMALLY CONDUCTIVE INSULATING CERAMICS

• 9.1 Scope and position in the heat path
• 9.2 Property benchmark
• 9.3 Aluminium nitride
  • 9.3.1 Conductivity, oxygen and grain-boundary phases
  • 9.3.2 Powder routes: carbothermal reduction versus direct nitridation
  • 9.3.3 Substrates and other aluminium nitride forms
• 9.4 Silicon nitride
  • 9.4.1 Why β-silicon nitride can conduct heat
  • 9.4.2 Fracture toughness: the property that sells silicon nitride
  • 9.4.3 Supplier base and Chinese expansion
• 9.5 Alumina and zirconia-toughened alumina
• 9.6 Beryllium oxide: a legacy material
• 9.7 Boron nitride systems
  • 9.7.1 Hexagonal boron nitride platelets and agglomerates
  • 9.7.2 Boron nitride ceramics, nanotubes and cubic BN
• 9.8 Metallised substrate technologies
  • 9.8.1 Direct bonded copper and direct bonded aluminium
  • 9.8.2 Active metal brazing
  • 9.8.3 Thick-film, co-fired and insulated metal substrates
  • 9.8.4 Ceramic-based integrated substrates and pin-fin structures
  • 9.8.5 Worked example: why thinner silicon nitride can beat thicker aluminium nitride
• 9.9 Key research questions
  • 9.9.1 Thermal conductivity: impurities, oxygen and grain boundaries
  • 9.9.2 Dielectric strength and partial discharge at 800 V to 3.3 kV
  • 9.9.3 Fracture resistance and thermal cycling
  • 9.9.4 Manufacturability: tape casting to finished substrate
• 9.10 Ceramics in AI infrastructure
  • 9.10.1 800 V DC rack power and solid-state transformers
  • 9.10.2 GaN power stages, vertical power delivery and co-packaged power
  • 9.10.3 Optical modules, RF and ceramic heat sinks
  • 9.10.4 Comparing AI and conventional power-electronics requirements
• 9.11 Supply chain and suppliers
  • 9.11.1 Powder producers
  • 9.11.2 Substrate and metallised-substrate producers
  • 9.11.3 Prices
  • 9.11.4 Supplier market shares
• 9.12 Recent developments, 2024–2026
• 9.13 Market forecast
  • 9.13.1 Forecast by application
  • 9.13.2 Forecast by material and product group
• 9.14 SWOT analysis
• 9.15 Outlook

10 THERMALLY CONDUCTIVE POLYMER COMPOSITES

• 10.1 Scope and position in the heat-removal pathway
• 10.2 Polymer matrices
• 10.3 Fillers
  • 10.3.1 Particle morphology and hybrid filler systems
• 10.4 Key research questions
  • 10.4.1 Filler loading and percolation
  • 10.4.2 Viscosity, rheology and processability
  • 10.4.3 Anisotropy
  • 10.4.4 Electrical properties
  • 10.4.5 Long-term reliability
  • 10.4.6 Measurement and specification pitfalls
• 10.5 Products and technologies
  • 10.5.1 Epoxy mould compounds for power modules and advanced packages
  • 10.5.2 Potting compounds and silicone gels
  • 10.5.3 Insulated metal substrate dielectrics and thermally conductive laminates
  • 10.5.4 Thermally conductive plastics
  • 10.5.5 Polymer insulating sheets replacing ceramics
  • 10.5.6 Thermally conductive underfills
• 10.6 AI versus power-electronics requirements
• 10.7 Application map
• 10.8 Recent developments, 2024–2026
• 10.9 Supplier landscape
• 10.10 Market forecast
  • 10.10.1 Forecast by application
  • 10.10.2 Forecast by product
• 10.11 SWOT analysis
• 10.12 Outlook: high-conductivity insulating composites as a research priority

11 MATERIALS FOR INTEGRATED LIQUID COOLING

• 11.1 Scope and market definition
• 11.2 Cooling architectures and their material demands
• 11.3 Cold plates and microchannel structures
  • 11.3.1 Material selection for cold plates
  • 11.3.2 Microchannel manufacturing methods
  • 11.3.3 Microchannel lids and package-integrated cooling
• 11.4 Bonded cooling structures
  • 11.4.1 Brazing, diffusion bonding and welding
  • 11.4.2 Attachment of coolers to substrates and EV pin-fin baseplates
• 11.5 Seals, hoses and quick disconnects
• 11.6 Protective and functional coatings
• 11.7 Coolants, dielectric fluids and fluid-contact materials
• 11.8 Key research questions
  • 11.8.1 Corrosion
  • 11.8.2 Leakage
  • 11.8.3 Fouling
  • 11.8.4 Joining reliability
  • 11.8.5 Long-term fluid compatibility
• 11.9 Material content, cost structure and supply chain
• 11.10 AI versus power-electronics requirements
• 11.11 Recent developments, 2024–2026
• 11.12 Supplier landscape
• 11.13 Market forecast
  • 11.13.1 Forecast by application
  • 11.13.2 Forecast by material and structure type
• 11.14 SWOT analysis
• 11.15 Outlook: package-integrated cooling as a research priority

12 PACKAGE ARCHITECTURE, INTERFACE QUALITY AND SYSTEM-LEVEL THERMAL PERFORMANCE

• 12.1 Why bulk conductivity is a poor proxy for package-level cooling
• 12.2 Lidded and lidless architectures in AI packages
• 12.3 TIM1, TIM1.5 and TIM2: naming, roles and consolidation
• 12.4 Worked thermal resistance budget: AI accelerator package
• 12.5 Bond-line thickness sensitivity
• 12.6 Bringing the coolant closer: cold plates, micro-channel lids and direct-to-silicon cooling
• 12.7 2.5D and 3D stacks and the HBM thermal path
• 12.8 Backside power delivery and its thermal implications
• 12.9 Warpage of large packages and its effect on bond-line thickness
• 12.10 Co-packaged optics and vertical power delivery
• 12.11 Power modules: cooling architectures and the disappearing interface
• 12.12 Worked thermal resistance budget: SiC traction module
• 12.13 Case studies
  • 12.13.1 Bare-die accelerator on a liquid cold plate
  • 12.13.2 HBM in-stack thermal paths
  • 12.13.3 Pin-fin direct-cooled SiC traction module
  • 12.13.4 Double-sided cooling in hybrid and EV inverters
  • 12.13.5 Composite case: indium TIM1 adoption in a custom AI ASIC
• 12.14 Simulation, digital twins and system-technology co-optimisation
• 12.15 Metrology: measuring what matters
• 12.16 Reliability qualification
• 12.17 What to specify beyond thermal conductivity
• 12.18 Implications for the market

13 SUPPLY CHAIN, RAW MATERIALS, PRICING AND GEOPOLITICS

• 13.1 The value chain from raw materials to OEMs
• 13.2 Raw materials and their exposure by subcategory
• 13.3 Concentration by country
• 13.4 Export controls
  • 13.4.1 Responses by the United States and its allies
• 13.5 Tariffs, 2025–2026
• 13.6 PFAS restrictions and fluorinated materials
• 13.7 Prices and price trends
• 13.8 Qualification cycles and switching costs
• 13.9 M&A and consolidation, 2023–2026
• 13.10 Regional manufacturing capacity
• 13.11 Risk matrix

14 GLOBAL MARKET FORECASTS 2027–2037

• 14.1 Forecast basis and assumptions
• 14.2 Total market
• 14.3 Market by material subcategory
• 14.4 Market by position in the heat-removal pathway
• 14.5 Market by application
  • 14.5.1 AI accelerators and advanced packaging
  • 14.5.2 AI servers and data-centre IT equipment
  • 14.5.3 Data-centre power infrastructure
  • 14.5.4 EV and transport power electronics
  • 14.5.5 Renewable, grid and industrial power electronics
  • 14.5.6 Telecom, RF and defence power devices
• 14.6 Material by application matrix
• 14.7 AI hardware versus power electronics
• 14.8 Market by region
• 14.9 Scenario analysis

15 TECHNOLOGY ROADMAP, RESEARCH PRIORITIES AND COMPETITIVE LANDSCAPE

• 15.1 Technology roadmap 2027–2037
• 15.2 Research priorities
  • 15.2.1 Thin-bond-line interfaces
  • 15.2.2 Diamond integration
  • 15.2.3 High-conductivity insulating composites
  • 15.2.4 Materials for package-integrated cooling
• 15.3 Emerging materials watchlist
• 15.4 Competitive landscape
  • 15.4.1 Strategic groups
  • 15.4.2 Supplier positioning across the eight subcategories
• 15.5 Recommendations
  • 15.5.1 For materials suppliers
  • 15.5.2 For device makers and system integrators
  • 15.5.3 For investors
• 15.6 Outlook

16 COMPANY PROFILES 279 (156 company profiles)

17 APPENDIX

• 17.1 Glossary of terms and abbreviations
• 17.2 Unit conversions and conventions

List of Tables

• Table 1. The eight material subcategories, by position in the heat-removal pathway.
• Table 2. Global market for thermal management materials for AI and power electronics by subcategory, 2027–2037 (US$ million).
• Table 3. Global market by application, 2027–2037 (US$ million).
• Table 4. Market by position in the heat-removal pathway, 2027 and 2037.
• Table 5. Thermal-management requirements: AI hardware versus power electronics.
• Table 6. Research priorities for thermal management materials, 2027–2037.
• Table 7. Scope boundaries: what is included and excluded from the market sizing.
• Table 8. The eight material subcategories mapped to position in the heat-removal pathway.
• Table 9. Worked example: area-specific resistance and temperature rise across TIM1 at 1,400 W over 1,600 mm².
• Table 10. Total power and heat flux for representative devices, 2026.
• Table 11. Principal measurement and characterisation methods for thermal-management materials.
• Table 12. AI accelerator and power-module heat paths compared.
• Table 13. Key forecasting conventions and assumptions.
• Table 14. Application segment definitions.
• Table 15. Regional segmentation and 2026–2037 market values (US$ million).
• Table 16. Related Future Markets reports and their relationship to this study.
• Table 17. AI accelerator package power by vendor and generation.
• Table 18. Packaging architecture trends and their thermal-materials implications.
• Table 19. Rack density bands, cooling methods and the thermal materials they pull through.
• Table 20. Data-centre power infrastructure: devices, thermal challenges and materials.
• Table 21. Evolution of the traction-inverter module material stack.
• Table 22. Renewable, grid and industrial power electronics: thermal profiles.
• Table 23. Telecom, RF and defence thermal requirements.
• Table 24. Thermal and mechanical properties of semiconductor and packaging materials.
• Table 25. Wide-bandgap penetration by application and material consequences, 2026–2035.
• Table 26. Requirement matrix by application.
• Table 27. Relative importance of material subcategories by application, 2026–2037 (H = high, M = medium, L = low).
• Table 28. Sustainability, regulatory and trade drivers affecting thermal-management materials.
• Table 29. Restraints and challenges for thermal-management materials.
• Table 30. Future Markets estimates of thermal-material content per device (constant 2025 US$).
• Table 31. Thermal-management materials market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 32. Application shares, growth and incremental value, 2026–2037.
• Table 33. Polymer TIM product forms in scope and their typical operating envelope.
• Table 34. Strengths, weaknesses and dominant failure modes of polymer TIM forms.
• Table 35. Comparison of polymer TIM matrix chemistries.
• Table 36. Properties and indicative prices of the principal TIM fillers.
• Table 37. Temperature drop across an interface (K) as a function of applied thermal resistance and heat flux.
• Table 38. Typical reliability tests applied to polymer TIMs and the failure modes they probe.
• Table 39. Key research questions for polymer TIMs: mechanisms, metrics and current status.
• Table 40. Requirement comparison: polymer TIMs in AI hardware versus power electronics.
• Table 41. Benchmark of selected thermal greases and thin-bond-line materials.
• Table 42. Benchmark of selected gels, dispensable gap fillers, pads and adhesives.
• Table 43. Indicative 2026 prices for polymer TIMs, volume industrial purchases.
• Table 44. Selected developments in polymer TIMs, 2024–2026.
• Table 45. Leading suppliers of polymer TIMs and estimated 2026 market shares (applications covered by this report).
• Table 46. Polymer-based thermal-interface materials market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 47. Polymer-based TIM market by product form, 2027–2037 (US$ million; Future Markets estimates).
• Table 48. SWOT analysis: polymer-based thermal-interface materials.
• Table 49. Classes of phase-change interface materials.
• Table 50. Organic (polymer) PCMs compared with low-melting metal-alloy PCMs.
• Table 51. Pre-applied TIM programmes at selected power module makers.
• Table 52. Phase-change materials compared with thermal greases at the same interfaces.
• Table 53. Key research questions for phase-change interface materials.
• Table 54. Requirement comparison: phase-change materials in AI hardware versus power electronics.
• Table 55. Benchmark of selected commercial phase-change interface materials.
• Table 56. Selected developments in phase-change interface materials, 2024–2026.
• Table 57. Leading suppliers of phase-change interface materials and estimated 2026 market shares.
• Table 58. Phase-change interface materials market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 59. Phase-change interface materials market by form, 2027–2037 (US$ million; Future Markets estimates).
• Table 60. SWOT analysis: phase-change interface materials.
• Table 61. Scope of metallic interface and attachment materials by position in the stack.
• Table 62. Typical metallisation stack for indium solder TIM1.
• Table 63. Confinement approaches for gallium-based liquid metal interfaces.
• Table 64. Property benchmark: metallic interface and attachment materials.
• Table 65. Indicative thermal resistance budget for TIM1 options on a 700 mm² AI accelerator die.
• Table 66. Joining temperature windows against component limits.
• Table 67. Indicative power-cycling lifetime of die-attach technologies.
• Table 68. Compatibility of metallic interface materials with common adjoining surfaces.
• Table 69. Requirements for metallic interface and attachment materials: AI packaging versus power electronics.
• Table 70. Raw-material price and supply indicators for metallic interface and attachment materials, 2024–2026.
• Table 71. Selected products and suppliers of metallic interface and attachment materials.
• Table 72. Supplier landscape by technology segment.
• Table 73. Recent developments in metallic interface and attachment materials.
• Table 74. Metallic interface and attachment materials market by application, 2027–2037 (US$ million).
• Table 75. Application shares and growth, metallic interface and attachment materials.
• Table 76. Metallic interface and attachment materials by technology, 2026–2037 (US$ million, Future Markets estimates).
• Table 77. SWOT analysis: metallic interface and attachment materials.
• Table 78. Research priorities for metallic interface and attachment materials.
• Table 79. Carbon-based heat spreader families: form, conductivity and role.
• Table 80. Synthetic graphite sheet: representative conductivity by thickness (Panasonic PGS reference grades).
• Table 81. Graphene oxide and reduced graphene oxide routes for thermal films.
• Table 82. Pitch-based carbon fibres used in thermal management.
• Table 83. Carbon–metal composites and encapsulated graphite: representative properties.
• Table 84. Property benchmark: carbon spreaders versus metal and diamond alternatives.
• Table 85. Lateral spreading capacity and vertical penalty of candidate spreaders.
• Table 86. Integration formats for carbon spreaders.
• Table 87. Electrical insulation options for graphite spreaders.
• Table 88. Requirements comparison: AI hardware versus power electronics for carbon spreaders.
• Table 89. Representative carbon spreader and interface products.
• Table 90. Indicative cost ranges for carbon spreaders, 2026.
• Table 91. Recent developments in carbon spreaders and interface structures, 2024–2026.
• Table 92. Supplier landscape for carbon-based heat spreaders.
• Table 93. Carbon-based heat spreaders market by application, 2027–2037 (US$ million).
• Table 94. Carbon-based heat spreaders market by product type, 2027–2037 (US$ million, Future Markets estimates).
• Table 95. SWOT analysis: carbon-based heat spreaders.
• Table 96. Diamond grades and properties for thermal management.
• Table 97. Metal–diamond composites and incumbent package materials.
• Table 98. Production methods for diamond thermal materials.
• Table 99. Diamond thermal material cost trajectory (indicative, US$ per cm²).
• Table 100. Bonding and attachment routes for diamond spreaders.
• Table 101. Thermal boundary resistance at diamond interfaces (representative reported ranges).
• Table 102. Worked example 1: vertical temperature rise contributed by spreader and attach layers (one-dimensional).
• Table 103. Worked example 2: GaN HEMT junction temperature rise versus effective TBR (illustrative).
• Table 104. Application readiness of diamond thermal technologies.
• Table 105. Requirements comparison: diamond in AI hardware versus power electronics.
• Table 106. Recent developments in diamond-based thermal materials, 2024–2026.
• Table 107. Supplier landscape for diamond-based thermal materials.
• Table 108. Diamond-based thermal materials market by application, 2027–2037 (US$ million).
• Table 109. Diamond-based thermal materials market by product type, 2027–2037 (US$ million, Future Markets estimates).
• Table 110. SWOT analysis: diamond-based thermal materials.
• Table 111. Ceramic forms covered in this chapter and their position in the heat-removal pathway.
• Table 112. Property benchmark for thermally conductive insulating ceramics (typical production values).
• Table 113. Aluminium nitride powder production routes compared.
• Table 114. Silicon nitride substrate grades and the variables that control them.
• Table 115. Boron nitride forms for thermal management.
• Table 116. Metallised ceramic substrate technologies compared.
• Table 117. Junction-to-coolant-surface thermal resistance of substrate stacks: worked example (10 × 10 mm die, 45° spreading).
• Table 118. Insulation requirements by voltage class and typical substrate choices.
• Table 119. Thermal-shock and mechanical performance of metallised substrates (typical).
• Table 120. Manufacturing steps, yield risks and cost levers for ceramic substrates.
• Table 121. AI-related applications for insulating ceramics.
• Table 122. Requirement comparison: AI data-centre power versus automotive and industrial power electronics.
• Table 123. Selected thermal-grade ceramic powder producers.
• Table 124. Selected insulating ceramic substrate and metallised substrate producers.
• Table 125. Indicative 2026 prices for insulating ceramics and substrates.
• Table 126. Estimated supplier shares of metallised AMB substrate value (Si3N4 and AlN), 2026.
• Table 127. Selected developments in insulating ceramics and substrates, 2024–2026.
• Table 128. Thermally conductive insulating ceramics market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 129. Thermally conductive insulating ceramics market by product group, 2027–2037 (US$ million; Future Markets estimates within model totals).
• Table 130. SWOT analysis: thermally conductive insulating ceramics.
• Table 131. Product classes in scope and their role in the heat path.
• Table 132. Polymer matrices for thermally conductive composites: representative properties.
• Table 133. Filler comparison for thermally conductive polymer composites.
• Table 134. Thermal conductivity versus filler loading: representative through-plane values for common systems.
• Table 135. Processing windows and constraints by product class.
• Table 136. Anisotropy in platelet-filled composites and alignment routes.
• Table 137. Electrical requirements for thermally conductive composites by application.
• Table 138. Product benchmark: representative thermally conductive composite products.
• Table 139. Requirements for thermally conductive composites: AI hardware versus power electronics.
• Table 140. Application map: where each composite product class is used, 2027.
• Table 141. Selected developments in thermally conductive polymer composites, 2024–2026.
• Table 142. Supplier landscape: thermally conductive polymer composites.
• Table 143. Thermally conductive polymer composites market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 144. Thermally conductive polymer composites market by product, 2027–2037 (US$ million; Future Markets estimates).
• Table 145. SWOT analysis: thermally conductive polymer composites.
• Table 146. Scope of the materials for integrated liquid cooling subcategory.
• Table 147. Direct-to-chip, immersion and in-package liquid cooling compared.
• Table 148. Cold-plate and cooler material comparison.
• Table 149. Microchannel and cold-plate manufacturing methods.
• Table 150. Joining methods for liquid-cooled structures.
• Table 151. Elastomer and polymer compatibility matrix for coolants and dielectric fluids.
• Table 152. Protective and functional coatings for liquid-cooled structures.
• Table 153. Coolant and dielectric fluid comparison.
• Table 154. Failure modes in integrated liquid cooling and material mitigations.
• Table 155. Integrated liquid cooling material requirements: AI hardware versus power electronics.
• Table 156. Selected developments in materials for integrated liquid cooling, 2024–2026.
• Table 157. Supplier landscape: materials and structures for integrated liquid cooling.
• Table 158. Materials for integrated liquid cooling market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Table 159. Materials for integrated liquid cooling market by material and structure type, 2027–2037 (US$ million; Future Markets estimates).
• Table 160. SWOT analysis: materials for integrated liquid cooling.
• Table 161. Contributions to the thermal resistance of a single interface layer, and the variables that control them.
• Table 162. Lidded versus lidless (bare-die) AI accelerator packages: thermal and integration trade-offs.
• Table 163. Interface positions in AI and HPC packages and the materials used at each, 2026.
• Table 164. Illustrative thermal resistance budget for a 1,200 W lidded AI accelerator on a liquid cold plate (Architecture A: polymer TIM1, copper lid, grease TIM2).
• Table 165. Cooling architectures for AI accelerators: thermal performance and materials implications, 2026–2033.
• Table 166. Thermal implications of advanced package architectures and the materials responses, 2026.
• Table 167. Effect of package coplanarity on achieved TIM bond line and interface temperature drop (illustrative, 1,200 W over 1,600 mm²).
• Table 168. Power module cooling architectures: structure, thermal performance and materials, 2026.
• Table 169. Illustrative thermal resistance budget for one switch position of a 1,200 V SiC module (Architecture: conventional baseplate with grease TIM).
• Table 170. Summary of case studies: what determined the thermal outcome.
• Table 171. Simulation and co-design tools relevant to thermal materials selection, 2026.
• Table 172. Thermal metrology methods and what they reveal about interface quality.
• Table 173. Reliability tests relevant to thermal interface and attachment materials.
• Table 174. Recommended specification parameters beyond bulk thermal conductivity, with indicative 2027 targets.
• Table 175. Thermal management materials value chain: stages, inputs and representative participants.
• Table 176. Critical raw materials for thermal management materials: use, supply concentration and principal risk.
• Table 177. Country positions by subcategory, 2026.
• Table 178. Export control measures affecting thermal management materials, 2023–2026.
• Table 179. Tariff measures affecting thermal management materials and components, 2025–2026.
• Table 180. PFAS exposure in thermal management materials and likely outcomes.
• Table 181. Indicative annual average prices for key metals used in thermal management materials, 2020–2026.
• Table 182. Indicative prices of key engineered thermal materials and components, 2026.
• Table 183. Qualification cycles and switching costs by application and material position.
• Table 184. Selected M&A, separations and strategic transactions affecting thermal management materials, 2023–2026.
• Table 185. Regional production capacity by subcategory and direction of investment, 2024–2026.
• Table 186. Supply-chain risk matrix for thermal management materials, 2027–2030.
• Table 187. Key assumptions underpinning the base-case forecast.
• Table 188. Global market for thermal management materials for AI and power electronics, 2023–2037 (US$ million, constant 2025 dollars).
• Table 189. Global market by material subcategory, 2027–2037 (US$ million).
• Table 190. Share of market by material subcategory, 2027, 2032 and 2037 (%).
• Table 191. Market by position in the heat-removal pathway, 2027–2037 (US$ million).
• Table 192. Global market by application, 2027–2037 (US$ million).
• Table 193. AI accelerators and advanced packaging: market by material subcategory, 2027–2037 (US$ million).
• Table 194. AI servers and data-centre IT equipment: market by material subcategory, 2027–2037 (US$ million).
• Table 195. Data-centre power infrastructure: market by material subcategory, 2027–2037 (US$ million).
• Table 196. EV and transport power electronics: market by material subcategory, 2027–2037 (US$ million).
• Table 197. Renewable, grid and industrial power electronics: market by material subcategory, 2027–2037 (US$ million).
• Table 198. Telecom, RF and defence power devices: market by material subcategory, 2027–2037 (US$ million).
• Table 199. Market by material subcategory and application, 2027 (US$ million).
• Table 200. Market by material subcategory and application, 2037 (US$ million).
• Table 201. CAGR 2027–2037 by material subcategory and application (%).
• Table 202. AI hardware versus power electronics demand, 2027–2037 (US$ million).
• Table 203. Global market by region, 2027–2037 (US$ million).
• Table 204. Scenario forecasts, 2027–2037 (US$ million).
• Table 205. Scenario sensitivities by subcategory: principal swing factors.
• Table 206. Market trajectory by subcategory, 2027–2037 (US$ million, constant 2025 dollars).
• Table 207. Technology roadmap by subcategory, 2027–2037.
• Table 208. Four research priorities: state of the art, targets, gaps and leading developers.
• Table 209. Emerging materials watchlist: properties, technology readiness and commercial horizon.
• Table 210. Strategic groups: characteristics, strengths and strategic risks.
• Table 211. Supplier positioning matrix, part A: interface and spreader pathways (● major position · ○ presence).
• Table 212. Supplier positioning matrix, part B: insulating substrate and cooling-fluid pathways (● major position · ○ presence).
• Table 213. Summary recommendations by stakeholder, priority and timing.
• Table 214. Companies profiled by primary position in the heat-removal pathway.
• Table 215. 3M thermal-management product portfolio for AI and power electronics.
• Table 216. 5N Plus products relevant to metallic interface and attachment materials.
• Table 217. Accelsius two-phase cooling portfolio for AI and HPC.
• Table 218. Adamas Nanotechnologies products relevant to the diamond thermal pathway.
• Table 219. Admatechs spherical filler portfolio relevant to AI and power-electronics thermal management.
• Table 220. Advent Diamond technology and product focus.
• Table 221. AIM Solder product families relevant to thermal attachment in power electronics and servers.
• Table 222. Aismalibar thermal-management product portfolio for power electronics.
• Table 223. Akash Systems Diamond Cooling product portfolio.
• Table 224. Akhan Semiconductor technology portfolio.
• Table 225. Alloy Enterprises Stack Forging thermal components.
• Table 226. Almatis alumina portfolio relevant to thermal management.
• Table 227. Ames Goldsmith materials relevant to thermal attachment and interfaces.
• Table 228. Amkor packaging platforms and the thermal-material decisions they embed.
• Table 229. Amogreentech thermal-management product portfolio for AI and power electronics.
• Table 230. Amosense ceramic substrate activities relevant to thermal management.
• Table 231. Applied Diamond product and capability portfolio relevant to thermal management.
• Table 232. Arieca product portfolio for AI and power electronics.
• Table 233. ASE platforms and the thermal-material decisions they embed.
• Table 234. AVC thermal portfolio for AI and power electronics.
• Table 235. ASMPT equipment relevant to metallic attachment and thermal interfaces.
• Table 236. Auras Technology thermal portfolio for AI and power electronics.
• Table 237. Bando Chemical thermal-management materials.
• Table 238. BNNT Materials product forms and their relevance to thermal management.
• Table 239. Boschman Technologies equipment relevant to thermal attachment and packaging.
• Table 240. Boston Materials thermal-management product portfolio for AI and power electronics.
• Table 241. Boyd and former Boyd Thermal portfolio relevant to AI and power electronics.
• Table 242. Carbice thermal-management product portfolio for AI and power electronics.
• Table 243. Celanese thermal-management product portfolio for AI and power electronics.
• Table 244. CeramTec insulating substrate portfolio for power electronics.
• Table 245. CCTC ceramic products relevant to the heat-removal pathway.
• Table 246. Chemours data-centre cooling fluid programme.
• Table 247. CHT thermal-management silicone portfolio.
• Table 248. Coherent thermal-management materials and products for AI and power electronics.
• Table 249. Cooler Master thermal portfolio for AI and power electronics.
• Table 250. CoolIT Systems liquid-cooling portfolio for AI and HPC.
• Table 251. Coollaboratory liquid-metal product range.
• Table 252. CoolSem WaLTIS positioning against established heat-path options for III-V devices.
• Table 253. CoorsTek ceramics relevant to the heat-removal pathway.
• Table 254. Corintis product and technology portfolio.
• Table 255. CPC Everis liquid-cooling couplings for AI and data-centre equipment.
• Table 256. Danfoss products in the data-centre liquid-cooling loop.
• Table 257. Denka thermal-management portfolio for AI and power electronics.
• Table 258. Dexerials thermal conductive sheet portfolio for AI and power electronics.
• Table 259. Diamfab technology and product portfolio.
• Table 260. Diamond Foundry semiconductor diamond portfolio.
• Table 261. Diamond Materials product portfolio relevant to thermal management.
• Table 262. Diamond Quanta Adamantine platform.
• Table 263. Dow thermal-management product portfolio for AI and power electronics.
• Table 264. DOWA Group materials relevant to the thermal pathway in power electronics and AI hardware.
• Table 265. ELANTAS thermally conductive products for power electronics and e-mobility.
• Table 266. Electrolube thermal interface portfolio for power electronics and data-centre hardware.
• Table 267. Element Six thermal-management product portfolio for AI and power electronics.
• Table 268. Elkem Silicones thermal-management product portfolio.
• Table 269. Engineered Fluids product portfolio for immersion and direct fluid cooling.
• Table 270. Ensinger thermally conductive compound portfolio.
• Table 271. Envalior thermally relevant material families.
• Table 272. Fabric8Labs ECAM thermal portfolio.
• Table 273. Ferrotec substrate and thermal product portfolio.
• Table 274. Freudenberg Sealing Technologies data-centre sealing portfolio.
• Table 275. Fuji Electric module platforms and their thermal-material content.
• Table 276. Fujipoly SARCON portfolio for AI and power electronics.
• Table 277. Aluminium nitride product scope and application fit (Fujian Huaqing and Chinese AlN peers).
• Table 278. GMG thermal-management product portfolio relevant to AI and power electronics.
• Table 279. Graphmatech product platforms and relevance to thermal management.
• Table 280. GRC products for immersion and liquid cooling.
• Table 281. H.B. Fuller thermal-management product portfolio for power electronics and energy storage.
• Table 282. Henan Huanghe Whirlwind diamond products relevant to thermal management.
• Table 283. Henkel thermal-management product portfolio for AI and power electronics.
• Table 284. Heraeus Electronics thermal-management and attachment portfolio.
• Table 285. Huntsman thermal-management product portfolio for power electronics.
• Table 286. Iceotope technology, products and qualification milestones.
• Table 287. IIa Technologies CVD diamond portfolio.
• Table 288. Indium Corporation metallic thermal-interface and attachment portfolio.
• Table 289. Infineon thermal-material choices by product family.
• Table 290. Japan Fine Ceramics products relevant to the heat-removal pathway.
• Table 291. Jentech thermal portfolio for AI and power electronics.
• Table 292. JetCool liquid-cooling portfolio for AI and power electronics.
• Table 293. Jones Tech thermal-management product portfolio.
• Table 294. Kaneka graphite thermal products for AI and power electronics.
• Table 295. KCC–Momentive thermal-management portfolio for AI and power electronics.
• Table 296. Kitagawa thermal-management product portfolio.
• Table 297. Kuprion ActiveCopper application areas.
• Table 298. Kyocera thermal-management materials portfolio.
• Table 299. LiquidStack product portfolio for AI and data-centre cooling.
• Table 300. MacDermid Alpha thermal and attachment portfolio.
• Table 301. MARUWA insulating substrate portfolio.
• Table 302. Mikros Technologies thermal portfolio.
• Table 303. Mitsubishi Chemical Group thermal-management materials relevant to AI and power electronics.
• Table 304. Mitsubishi Electric thermal architectures by product family.
• Table 305. Mitsubishi Materials thermal-management products for power electronics.
• Table 306. Boron nitride filler characteristics and application fit (Mizushima Ferroalloy).
• Table 307. Momentive thermal-management product portfolio for AI and power electronics.
• Table 308. Momentive Technologies thermal-management products.
• Table 309. Motivair liquid-cooling portfolio for AI and HPC.
• Table 310. Nagase ChemteX and Nagase group packaging and thermal materials.
• Table 311. Namics product portfolio relevant to AI and power-electronics thermal paths.
• Table 312. NBE Tech nanosilver sinter technology.
• Table 313. NeoGraf thermal-management product portfolio for AI and power electronics.
• Table 314. NGK thermal and packaging ceramics relevant to AI and power electronics.
• Table 315. Nidec liquid-cooling products for AI data centres.
• Table 316. Nihon Superior materials relevant to thermal attachment.
• Table 317. Ningbo Crysdiam product portfolio.
• Table 318. Nippon Graphite Fiber product forms and thermal-management relevance.
• Table 319. Niterra Materials silicon nitride portfolio for power electronics.
• Table 320. Nitto Denko products relevant to thermal management in electronics.
• Table 321. Nolato thermal and EMC product portfolio.
• Table 322. onsemi thermal architectures by product family.
• Table 323. Orbray diamond portfolio for thermal and electronic applications.
• Table 324. Panasonic Industry graphite thermal product portfolio for AI and power electronics.
• Table 325. Parker Chomerics thermal-management product portfolio for AI and power electronics.
• Table 326. PINK GmbH Thermosysteme process equipment for power-electronics attachment.
• Table 327. Plansee thermal-management materials for power electronics and AI.
• Table 328. Polyplastics materials relevant to thermal management in power electronics and AI hardware.
• Table 329. Proterial products relevant to power-electronics thermal management.
• Table 330. Qnity (Laird) thermal-management product portfolio for AI and power electronics.
• Table 331. Resonac packaging and thermal products for AI accelerators and power devices.
• Table 332. RFHIC DiaFlux CVD diamond heat-spreader specifications (company data).
• Table 333. Rogers curamik and related products for power-electronics thermal management.
• Table 334. ROHM thermal-relevant product platforms.
• Table 335. SABIC thermal-management materials for AI and power electronics.
• Table 336. Saint-Gobain products in the thermal-management pathway.
• Table 337. Samsung thermal and packaging choices relevant to materials suppliers.
• Table 338. Sekisui Polymatech thermal-management product portfolio.
• Table 339. Semikron Danfoss packaging technologies and modules relevant to the thermal pathway.
• Table 340. Senju Metal Industry products relevant to thermal attachment in AI and power electronics.
• Table 341. Shell immersion cooling fluids and milestones.
• Table 342. Shenzhen FRD thermal-management portfolio relevant to AI and power electronics.
• Table 343. Shin-Etsu thermal-management product portfolio for AI and power electronics.
• Table 344. SHT Smart High Tech product portfolio.
• Table 345. Sinocera product lines in the thermal-management pathway.
• Table 346. The Sixth Element and Fuxi Technology thermal-management products.
• Table 347. SK hynix HBM thermal technologies.
• Table 348. Solstice thermal-management product portfolio for AI and power electronics.
• Table 349. STMicroelectronics thermal architectures by product family.
• Table 350. Staubli connection products for liquid-cooled AI and data-centre equipment.
• Table 351. Submer business lines and products.
• Table 352. Sumitomo Bakelite encapsulation materials for AI and power electronics.
• Table 353. Sumitomo Electric group heat-spreader materials.
• Table 354. T-Global thermal-management product portfolio for AI and power electronics.
• Table 355. TSMC 3DFabric roadmap and thermal implications.
• Table 356. TANAKA materials for thermal attachment in power and semiconductor packaging.
• Table 357. Tanyuan Technology thermal product portfolio.
• Table 358. Tekna technologies and their relevance to thermal-management materials.
• Table 359. Tokuyama heat-dissipation materials portfolio.
• Table 360. Toyo Aluminium TOYALNITE aluminium nitride portfolio.
• Table 361. Toyo Tanso products relevant to AI and power-electronics thermal management.
• Table 362. Umicore activities relevant to metallic interface and attachment materials.
• Table 363. Ventec tec-thermal product portfolio for power electronics and lighting.
• Table 364. Vertiv liquid-cooling and thermal-chain portfolio for AI.
• Table 365. Wacker thermally conductive silicone portfolio for AI and power electronics.
• Table 366. Wieland electronics-cooling portfolio.
• Table 367. Wolfspeed products and their position in the heat-removal pathway.
• Table 368. Zeon thermal and carbon-nanotube products.
• Table 369. Zhengzhou Sino-Crystal product categories relevant to thermal management.
• Table 370. ZutaCore HyperCool platform and ecosystem.
• Table 371. Glossary of terms and abbreviations used in this report.

List of Figures

• Figure 1. Global market by material subcategory, 2027–2037 (US$ million).
• Figure 2. CAGR 2027–2037 by material subcategory (%).
• Figure 3. Heat-removal pathway in a liquid-cooled, lidded AI accelerator package (heat flows upward from the die to the coolant).
• Figure 4. Thermal management materials market by heat-path position, 2026, 2030 and 2037 (US$ million, constant 2025 dollars).
• Figure 5. Total area-specific thermal resistance of TIM1 options in the worked example (mm²·K/W; lower is better).
• Figure 6. Heat-removal pathway in a liquid-cooled SiC traction-inverter power module (heat flows downward from the die to the coolant).
• Figure 7. Flagship NVIDIA accelerator package power by generation (W).
• Figure 8. Rack power of flagship NVIDIA AI platforms (kW per rack).
• Figure 9. Average new-build AI rack density, Future Markets base case (kW per rack).
• Figure 10. Thermal-management materials market by application, 2027–2037 (US$ million, constant 2025 dollars).
• Figure 11. CAGR 2027–2037 by application (%).
• Figure 12. Heat path through a lidded AI accelerator module to a direct-to-chip cold plate, showing where polymer TIMs act.
• Figure 13. Effective thermal conductivity of filled silicone versus filler volume fraction, Lewis–Nielsen model (matrix 0.16 W/m·K, spherical particles, maximum packing fraction 0.80).
• Figure 14. Applied thermal resistance of a polymer TIM layer versus bond-line thickness for three bulk conductivities (combined contact resistance 0.02 K·cm²/W).
• Figure 15. Supplier-quoted bulk thermal conductivity of selected polymer TIMs launched or promoted for AI and power electronics, 2021–2026.
• Figure 16. Estimated supplier shares of the polymer TIM market, 2026 (US$1,650 million).
• Figure 17. Polymer-based TIM market by application, 2027–2037 (US$ million).
• Figure 18. Polymer-based TIM market by product form, 2027–2037 (US$ million).
• Figure 19. Quoted bulk thermal conductivity across successive Honeywell/Solstice phase-change TIM generations, with a reference premium grease.
• Figure 20. Quoted thermal impedance of selected thin-bond-line interface materials.
• Figure 21. Estimated supplier shares of the phase-change interface materials market, 2026 (US$310 million).
• Figure 22. Phase-change interface materials market by application, 2027–2037 (US$ million).
• Figure 23. Phase-change interface materials market by form, 2027–2037 (US$ million).
• Figure 24. Metallic layers in a double-sided-cooled SiC power module heat path (one side shown).
• Figure 25. Bulk thermal conductivity versus peak joining temperature for metallic interface and attachment materials (mid-range values).
• Figure 26. Indicative temperature drop across TIM1 for a 1,000 W, 700 mm² accelerator die (mid-point estimates).
• Figure 27. Indicative power-cycling lifetime multiple relative to solder die attach with Al wire bonds (mid-point).
• Figure 28. Silver spot price at selected dates, 2025–2026.
• Figure 29. Metallic interface and attachment materials market by application, 2027–2037.
• Figure 30. Metallic interface and attachment materials by technology, 2027–2037 (Future Markets estimates).
• Figure 31. Technology mix of metallic interface and attachment materials, 2037 (Future Markets estimates).
• Figure 32. Synthetic graphite sheet in-plane conductivity and sheet conductance versus thickness.
• Figure 33. In-plane versus through-plane thermal conductivity of spreader materials (mid-range values).
• Figure 34. Carbon-based heat spreaders market by application, 2027–2037 (US$ million).
• Figure 35. Carbon-based heat spreaders market by product type, 2027–2037 (US$ million).
• Figure 36. Carbon-based heat spreaders market by application, 2037 (share of US$1,748 million).
• Figure 37. Indicative cost trajectory of diamond thermal materials (US$/cm², mid-points, log scale).
• Figure 38. Illustrative GaN HEMT junction temperature rise by component: GaN-on-SiC versus GaN-on-diamond at different effective TBRs (K).
• Figure 39. Near-junction diamond heat path in a GaN-on-diamond HEMT and the layers that add interface resistance.
• Figure 40. Diamond-based thermal materials market by application, 2027–2037 (US$ million).
• Figure 41. Diamond-based thermal materials market by product type, 2027–2037 (US$ million).
• Figure 42. Diamond-based thermal materials: AI accelerators and advanced packaging versus telecom, RF and defence (US$ million).
• Figure 43. Thermal conductivity versus fracture toughness of insulating substrate ceramics (typical production values).
• Figure 44. Worked example: thermal resistance contributions by layer for six substrate stacks (K/W).
• Figure 45. Heat path through a silicon nitride AMB power module stack (illustrative).
• Figure 46. Estimated supplier shares of AMB substrate value, 2026 (mid-points, %).
• Figure 47. Thermally conductive insulating ceramics market by application, 2027–2037 (US$ million).
• Figure 48. Thermally conductive insulating ceramics by product group, 2027–2037 (US$ million).
• Figure 49. Through-plane thermal conductivity versus filler loading, representative composite systems.
• Figure 50. Thermal conductivity versus temperature rating of composite product classes (mid-points of representative ranges).
• Figure 51. Thermally conductive polymer composites market by application, 2027–2037 (US$ million).
• Figure 52. Thermally conductive polymer composites by product, 2027 and 2037 (US$ million).
• Figure 53. Heat-flux capability versus indicative junction-to-fluid thermal resistance of cooling approaches (mid-points).
• Figure 54. Approximate volumetric heat capacity of coolants and dielectric fluids at 25 °C (MJ/m³·K).
• Figure 55. Materials for integrated liquid cooling market by application, 2027–2037 (US$ million).
• Figure 56. Materials for integrated liquid cooling by material and structure type, 2027–2037 (US$ million).
• Figure 57. Materials for integrated liquid cooling: value and share of total thermal management materials market, 2023–2037.
• Figure 58. Illustrative junction-to-coolant thermal resistance by layer for four AI accelerator architectures at 1,200 W (mK/W).
• Figure 59. Temperature drop across the die-level interface versus bond-line thickness, 1,200 W over 1,600 mm² (K).
• Figure 60. Illustrative junction-to-fluid thermal resistance per switch position for three SiC module architectures (mK/W).
• Figure 61. Share of junction-to-coolant thermal resistance attributable to interface layers, illustrative architectures (%).
• Figure 62. China's indicative share of global primary production or refining for selected inputs to thermal management materials, 2025 (%).
• Figure 63. Indicative price index for key thermal-materials metals, 2020 = 100.
• Figure 64. Silver metal content cost per kilogram of sinter paste (88% Ag by weight) at different silver prices (US$/kg).
• Figure 65. Thermal management materials market by region of consumption, 2027, 2030, 2033 and 2037 (US$ million).
• Figure 66. Global market for thermal management materials for AI and power electronics, 2023–2037 (US$ million).
• Figure 67. Global market by material subcategory, 2027–2037 (US$ million).
• Figure 68. Incremental annual revenue by subcategory, 2027 to 2037 (US$ million).
• Figure 69. Market by position in the heat-removal pathway, 2027, 2032 and 2037 (US$ million).
• Figure 70. Global market by application, 2027–2037 (US$ million).
• Figure 71. Market share by application, 2037.
• Figure 72. AI hardware versus power electronics demand, 2027–2037 (US$ million).
• Figure 73. Market by region, 2027 and 2037 (US$ million).
• Figure 74. Scenario forecasts, 2027–2037 (US$ million).
• Figure 75. Thermal management materials market by subcategory, 2027 and 2037 (US$ million).
• Figure 76. Future Markets targets for installed die-level interface resistance, 2024–2037 (mm²·K/W).
• Figure 77. Strategic groups: breadth across the heat-removal pathway versus exposure to AI and power electronics (Future Markets positioning estimates).