Bioplastic derived from corn stover: Life cycle assessment and artificial intelligence-based analysis of uncertainty and variability.

Exploring feasible and renewable alternatives to reduce dependency on traditional fossil-based plastics is critical for sustainable development. These alternatives can be produced from biomass, which may have large uncertainties and variabilities in the feedstock composition and system parameters. This study develops a modeling framework that integrates cradle-to-grave life cycle assessment (LCA) with a rigorous process model and artificial intelligence (AI) models to conduct uncertainty and variability analyses, which are highly time-consuming to conduct using only the process model. This modeling framework examines polylactic acid (PLA) produced from corn stover in the U.S. An analysis of uncertainty and variability was conducted by performing a Monte Carlo simulation to show the detailed result distributions. Our Monte Carlo simulation results show that the mean life-cycle Global Warming Potential (GWP) of 1 kg PLA is 4.3 kgCO2eq (P5-P95 4.1-4.4) for composting PLA with natural gas combusted for the biorefinery, 3.7 kgCO2eq (P5-P95 3.4-3.9) for incinerating PLA for electricity with natural gas combusted for the biorefinery, and 1.9 kgCO2eq (P5-P95 1.6-2.1) for incinerating PLA for electricity with wood pellets combusted for the biorefinery. Tradeoffs for different environmental impact categories were identified. Based on feedstock composition variations, two AI models were trained: random forest and artificial neural networks. Both AI models demonstrated high prediction accuracy; however, the random forest performed slightly better.

A Scalable Microstructure Photonic Coating Fabricated by Roll-to-Roll "Defects" for Daytime Subambient Passive Radiative Cooling.

The deep space's coldness (∼4 K) provides a ubiquitous and inexhaustible thermodynamic resource to suppress the cooling energy consumption. However, it is nontrivial to achieve subambient radiative cooling during daytime under strong direct sunlight, which requires rational and delicate photonic design for simultaneous high solar reflectivity (>94%) and thermal emissivity. A great challenge arises when trying to meet such strict photonic microstructure requirements while maintaining manufacturing scalability. Herein, we demonstrate a rapid, low-cost, template-free roll-to-roll method to fabricate spike microstructured photonic nanocomposite coatings with Al2O3 and TiO2 nanoparticles embedded that possess 96.0% of solar reflectivity and 97.0% of thermal emissivity. When facing direct sunlight in the spring of Chicago (average 699 W/m2 solar intensity), the coatings show a radiative cooling power of 39.1 W/m2. Combined with the coatings' superhydrophobic and contamination resistance merits, the potential 14.4% cooling energy-saving capability is numerically demonstrated across the United States.