AI in Carbon Capture Optimization Quiz

Answers and explanations appear as you take the quiz.

1. What is the main bottleneck AI tries to solve in carbon capture?
   • The high cost and energy use of capturing and releasing CO2
   • The color of the equipment
   • The lack of CO2 in the atmosphere
   • Too few power plants in the world
2. What solvent family did the cited machine-guided discovery study investigate?
   • Lithium salts for battery storage
   • Aqueous amines for acid-gas scrubbing carbon capture
   • Solid sorbents for water purification only
   • Hydrogen catalysts for fuel cells
3. What does 'solvent regeneration' refer to in carbon capture?
   • Painting the solvent tank
   • Cleaning the office
   • Releasing captured CO2 from the solvent so it can be reused, which takes a lot of energy
   • Adding more flue gas
4. What is the role of a surrogate model in capture-process optimization?
   • Certify that geological storage is secure
   • Replace all process measurements
   • Measure carbon emissions with satellite imagery
   • Approximate an expensive process simulation so candidate settings can be explored more quickly
5. What objectives did the cited 2026 amine-capture simulation study optimize together?
   • CO₂ recovery, product purity, and specific energy consumption
   • Worker safety, building daylight, and HVAC comfort
   • Only solvent color and viscosity
   • Reservoir pressure and earthquake risk
6. How did the cited solvent-discovery study verify promising model-selected candidates?
   • It launched an autonomous robotic lab for every candidate
   • It used a rapid laboratory assay for CO₂ absorption and then experimental checks
   • It used only a language-model rating
   • It inferred capture performance from satellite images
7. Which two solvent properties did the 2023 study use for molecular-fingerprint prediction?
   • Worker injury risk and building energy use
   • Reservoir pressure and seismic amplitude
   • Absorption capacity and observed initial absorption rate
   • CO₂ purity and stack temperature only
8. What did the 2023 solvent-discovery paper report on its external test set?
   • 100% accuracy on every outcome
   • 17% for all operating settings
   • No external test set
   • 60% accuracy for both material parameters and 80% for a single parameter