Jamie Gomez, Ph.D.
Principal, Insight Quantix
Decision-Grade Techno-Economic Analysis (TEA) for Large-Scale Clean Energy
Hydrogen • SAF • Power-to-Liquids | Go / No-Go Decisions • Capital Risk
Insight Quantix is a founder-led analytical portfolio focused on hydrogen, SAF, and electrolyzer economics. This site archives public, decision-grade analyses with emphasis on delivered-cost assumptions, utilization sensitivities, and policy-tier risks.
Domains of Expertise
Areas of focus
Analytical depth across clean energy pathways where cost formation is complex and policy constraints shape economics.
Hydrogen Production
Green and low-carbon hydrogen economics under 45V, IRA credits, and evolving matching requirements.
- What electricity price is required to undercut grey hydrogen at the gate?
- How does hourly vs. annual matching affect credit tier eligibility?
- At what utilization does a project become uneconomic?
- Credit-tier cliff risk from matching strategy assumptions
- Delivered cost vs. nominal LCOH differences
Sustainable Aviation Fuel
Pathway-specific TEA for HEFA, Fischer-Tropsch, ATJ, and emerging PtL routes.
- Which feedstock and pathway combination minimizes delivered cost?
- What CI score is achievable under CORSIA vs. LCFS?
- How do credit stacking scenarios affect project returns?
- Energy-intensity sensitivities across conversion steps
- Feedstock price volatility impact on break-even
Power-to-Liquids (PtL)
E-fuels synthesis economics: electrolyzer capacity, DAC integration, and FT/methanol pathways.
- What electricity cost makes e-kerosene competitive with fossil jet?
- How does electrolyzer sizing affect system utilization?
- What are the cost implications of DAC vs. point-source CO2?
- System-level capacity factor vs. component utilization
- Heat integration opportunities and penalties
Electrolyzer Systems
PEM, alkaline, and SOEC technology selection, stack degradation modeling, and BOP cost drivers.
- Which technology fits a given load profile and grid constraints?
- How does stack replacement timing affect project NPV?
- What efficiency degradation assumptions are defensible?
- BOP costs at scale vs. published stack-only numbers
- Ramp rate constraints and cycling penalties
Manufacturing Scale-up
Learning curves, capacity expansion, and supply chain cost trajectories for clean energy equipment.
- What learning rate is defensible for cost projections?
- When does local manufacturing become cost-competitive?
- How do supply chain bottlenecks affect deployment timelines?
- Critical material constraints on learning curve assumptions
- Regional cost differentials beyond labor rates
Policy-Constrained Economics
IRA credits, 45V/45Z, LCFS, CORSIA, and EU regulatory frameworks for project economics.
- How should credit uncertainty be modeled in project finance?
- What compliance pathway optimizes credit value?
- How sensitive are projects to policy sunset provisions?
- Threshold effects and cliff risks at credit-tier boundaries
- Additionality and geographic constraints on credit eligibility
Analytical Notes
Public decision-grade analyses
Independent research on TEA/LCA methods and modeling decisions, published for transparency.
Hydrogen: 45V Cost Parity vs Grey
Under the finalized 45V framework, what electricity price and matching strategy are required for clean hydrogen to undercut grey at the gate? A techno-economic analysis of utilization, matching constraints, and credit-tier risk.
Read the AnalysisDynamics of Cost Formation in Early-Stage SAF Pathways
Forthcoming: A method-focused reflection on assumption clarity and energy-intensity drivers.
Architectures for Scalable Clean-Energy System Models
Forthcoming: Notes on TEA/LCA validation and modeling reproducibility.
Analytical Method
Analytical principles
Five principles that shape the analytical work published here.
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Published LCOH or LCOF numbers often exclude transport, storage, and conditioning costs. These models track full delivered cost to the point of use, revealing where projects break even versus where headlines claim they will.
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Capacity factor assumptions drive economics more than most realize. Models are stress-tested across realistic utilization ranges, especially for intermittent-coupled systems where 90% nameplate assumptions hide substantial risk.
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Policy credits often have hard thresholds (e.g., 45V emission intensity tiers). Analysis maps where projects sit relative to cliff edges and quantifies the economic impact of small changes in carbon intensity or matching strategy.
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Instead of single-point forecasts, results are framed as thresholds: "This project works if electricity stays below $X/MWh" or "Break-even requires >Y% utilization." Decision-makers can then apply their own views on key uncertainties.
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All published analysis includes documented assumptions, source citations, and sensitivity tables. Technical reviewers can trace any output back to its inputs and audit the methodology independently.
Background
About the analyst
Experience
- Ph.D. in engineering with focus on energy systems
- TEA/LCA modeling across hydrogen, SAF, and electrochemical systems
- Published analytical frameworks referenced in industry
Approach
The work archived here emphasizes decision-relevant analysis over comprehensive surveys. The goal is to provide clear views of key uncertainties and thresholds that matter for specific decisions.
Independence note: Insight Quantix is an independent analytical practice. Analysis and opinions expressed here are solely those of the author and do not represent the views of any employer or affiliated organization.
General correspondence: jamie@insightquantix.com