Engineering topics

Advincula, Paul A.

Publications and source records attributed to Advincula, Paul A..

6 records

DOE OSTI2023

Automated Laboratory Kilogram-Scale Graphene Production from Coal

The flash Joule heating (FJH) method converts many carbon feedstocks into graphene in milliseconds to seconds using an electrical pulse. This opens an opportunity for processing low or negative value resources, such as coal and plastic waste, into high value graphene. Here, in this work, a lab-scale automation FJH system that allows the synthesis of 1.1 kg of turbostratic flash graphene from coal-based metallurgical coke (MC) in 1.5 h is demonstrated. The process is based on the automated conversion of 5.7 g of MC per batch using an electrical pulse width modulation system to conduct the bottom-up upcycle of MC into flash graphene. This study then compare this method to two other scalable graphene synthesis techniques by both a life cycle assessment and a technoeconomic assessment.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Waste plastic- and coke-derived flash graphene as lubricant additives

Lubricants play an essential role in reducing wear in mechanical systems. Carbon nanomaterial additives, such as graphene, have been found to significantly improve tribological performance when used as lubricant additives. Here, in this study, post-consumer plastic and metallurgical coke are converted into turbostratic flash graphene (FG) through flash Joule heating (FJH). The FG is then added to either poly(alpha olefin) 6 or 9 (PAO 6 or PAO 9). Adding waste plastic-derived FG (WPFG) and metallurgical coke-derived FG (MCFG) to lubricants resulted in a significant decrease in the coefficient of friction (CoF), wear scar diameter (WSD), and roughness during four-ball testing. WPFG and MCFG decrease the CoF in PAO 9 by 6% and 9% at 0.1 mg mL -1 , respectively, and in PAO 6 by 23% and 6% at 0.5 mg mL -1 , respectively. WPFG and MCFG decrease the WSD of steel balls in PAO 9 by 14% and 8% at 0.5 mg mL -1 , respectively, and in PAO 6 by 12% and 14% at 0.5 mg mL -1 , respectively, by forming a coating-like layer between the metal surfaces. Roughness decreased by 38% and 32% for WPFG and MCFG in PAO 6, respectively, and by 35% and 29% for WPFG and MCFG in PAO 9, respectively. Finally, preliminary life cycle analyses demonstrate that production of FG produces up to 99% less greenhouse gas emissions, requires 98% less energy, and consumes 99.9% less water when compared to conventional production techniques of graphene. Hence, metallurgical coke and waste plastic are shown to be ready feedstocks for high-quality FG lubricant additives.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Flash Recycling of Graphite Anodes

The ever-increasing production of commercial lithium-ion batteries (LIBs) will result in a staggering accumulation of waste when they reach their end of life. A closed-loop solution, with effective recycling of spent LIBs, will lessen both the environmental impacts and economic cost of their use. Presently, <5% of spent LIBs are recycled and the regeneration of graphite anodes has, unfortunately, been mostly overlooked despite the considerable cost of battery-grade graphite. Here, in this work, an ultrafast flash recycling method to regenerate the graphite anode is developed and valuable battery metal resources are recovered. Selective Joule heating is applied for only seconds to efficiently decompose the resistive impurities. The generated inorganic salts, including lithium, cobalt, nickel, and manganese, can be easily recollected from the flashed anode waste using diluted acid, specifically 0.1 M HCl. The flash-recycled anode preserves the graphite structure and is coated with a solid-electrolyte-interphase-derived carbon shell, contributing to high initial specific capacity, superior rate performance, and cycling stability, when compared to anode materials recycled using a high-temperature-calcination method. Life-cycle-analysis relative to current graphite production and recycling methods indicate that flash recycling can significantly reduce the total energy consumption and greenhouse gas emission while turning anode recycling into an economically advantageous process.

36 MATERIALS SCIENCE↗

DOE OSTI2022

High-surface-area corundum nanoparticles by resistive hotspot-induced phase transformation

Abstract High-surface-area α-Al 2 O 3 nanoparticles are used in high-strength ceramics and stable catalyst supports. The production of α-Al 2 O 3 by phase transformation from γ-Al 2 O 3 is hampered by a high activation energy barrier, which usually requires extended high-temperature annealing (~1500 K, > 10 h) and suffers from aggregation. Here, we report the synthesis of dehydrated α-Al 2 O 3 nanoparticles (phase purity ~100%, particle size ~23 nm, surface area ~65 m 2 g −1 ) by a pulsed direct current Joule heating of γ-Al 2 O 3 . The phase transformation is completed at a reduced bulk temperature and duration (~573 K, < 1 s) via an intermediate δʹ-Al 2 O 3 phase. Numerical simulations reveal the resistive hotspot-induced local heating in the pulsed current process enables the rapid transformation. Theoretical calculations show the topotactic transition (from γ- to δʹ- to α-Al 2 O 3 ) is driven by their surface energy differences. The α-Al 2 O 3 nanoparticles are sintered to nanograined ceramics with hardness superior to commercial alumina and approaching that of sapphire.

Deng, Bing (ORCID:0000000305308410)↗

DOE OSTI2022

Heteroatom-Doped Flash Graphene

Heteroatom doping can effectively tailor the local structures and electronic states of intrinsic two-dimensional materials, and endow them with modified optical, electrical, and mechanical properties. Recent studies have shown the feasibility of preparing doped graphene from graphene oxide and its derivatives via some post-treatments, including solid-state and solvothermal methods, but they require reactive and harsh reagents. However, direct synthesis of various heteroatom-doped graphene in larger quantities and high purity through bottom-up methods remains challenging. Here, we report catalyst-free and solvent-free direct synthesis of graphene doped with various heteroatoms in bulk via flash Joule heating (FJH). Seven types of heteroatom-doped flash graphene (FG) are synthesized through millisecond flashing, including single-element-doped FG (boron, nitrogen, oxygen, phosphorus, sulfur), two-element-co-doped FG (boron and nitrogen), as well as three-element-co-doped FG (boron, nitrogen, and sulfur). Here, a variety of low-cost dopants, such as elements, oxides, and organic compounds are used. The graphene quality of heteroatom-doped FG is high, and similar to intrinsic FG, the material exhibits turbostraticity, increased interlayer spacing, and superior dispersibility. Electrochemical oxygen reduction reaction of different heteroatom-doped FG is tested, and sulfur-doped FG shows the best performance. Lithium metal battery tests demonstrate that nitrogen-doped FG exhibits a smaller nucleation overpotential compared to Cu or undoped FG. The electrical energy cost for the synthesis of heteroatom-doped FG synthesis is only 1.2 to 10.7 kJ g –1 , which could render the FJH method suitable for low-cost mass production of heteroatom-doped graphene.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Machine Learning Guided Synthesis of Flash Graphene

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low-value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves an r 2 score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction-limited to diffusion-limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta-learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. Furthermore, these results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.

01 COAL, LIGNITE, AND PEAT↗