Browsing by Author "Li, Zheng"

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    Accelerating Catalyst Discovery via Ab Initio Machine Learning
    Li, Zheng (Virginia Tech, 2019-12-03)
    In recent decades, machine learning techniques have received an explosion of interest in the domain of high-throughput materials discovery, which is largely attributed to the fastgrowing development of quantum-chemical methods and learning algorithms. Nevertheless, machine learning for catalysis is still at its initial stage due to our insufficient knowledge of the structure-property relationships. In this regard, we demonstrate a holistic machine-learning framework as surrogate models for the expensive density functional theory to facilitate the discovery of high-performance catalysts. The framework, which integrates the descriptor-based kinetic analysis, material fingerprinting and machine learning algorithms, can rapidly explore a broad range of materials space with enormous compositional and configurational degrees of freedom prior to the expensive quantum-chemical calculations and/or experimental testing. Importantly, advanced machine learning approaches (e.g., global sensitivity analysis, principal component analysis, and exploratory analysis) can be utilized to shed light on the underlying physical factors governing the catalytic activity on a diverse type of catalytic materials with different applications. Chapter 1 introduces some basic concepts and knowledge relating to the computational catalyst design. Chapter 2 and Chapter 3 demonstrate the methodology to construct the machine-learning models for bimetallic catalysts. In Chapter 4, the multi-functionality of the machine-learning models is illustrated to understand the metalloporphyrin's underlying structure-property relationships. In Chapter 5, an uncertainty-guided machine learning strategy is introduced to tackle the challenge of data deficiency for perovskite electrode materials design in the electrochemical water splitting cell.
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    Assessing Structure–Property Relationships of Crystal Materials using Deep Learning
    Li, Zheng (Virginia Tech, 2020-08-05)
    In recent years, deep learning technologies have received huge attention and interest in the field of high-performance material design. This is primarily because deep learning algorithms in nature have huge advantages over the conventional machine learning models in processing massive amounts of unstructured data with high performance. Besides, deep learning models are capable of recognizing the hidden patterns among unstructured data in an automatic fashion without relying on excessive human domain knowledge. Nevertheless, constructing a robust deep learning model for assessing materials' structure-property relationships remains a non-trivial task due to highly flexible model architecture and the challenge of selecting appropriate material representation methods. In this regard, we develop advanced deep-learning models and implement them for predicting the quantum-chemical calculated properties (i.e., formation energy) for an enormous number of crystal systems. Chapter 1 briefly introduces some fundamental theory of deep learning models (i.e., CNN, GNN) and advanced analysis methods (i.e., saliency map). In Chapter 2, the convolutional neural network (CNN) model is established to find the correlation between the physically intuitive partial electronic density of state (PDOS) and the formation energies of crystals. Importantly, advanced machine learning analysis methods (i.e., salience mapping analysis) are utilized to shed light on underlying physical factors governing the energy properties. In Chapter 3, we introduce the methodology of implementing the cutting-edge graph neural networks (GNN) models for learning an enormous number of crystal structures for the desired properties.
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    Design and Electrochemical Performance of Sodium-Based Batteries
    Zhang, Qipeng (Virginia Tech, 2024-12-06)
    Low-cost, high-performance energy storage solutions are in great demand for applications such as vehicle electrification and electricity generation from renewable sources. Lithium-based batteries have emerged as strong contenders due to their high energy density and stability. However, their reliance on scarce lithium reserves and high production costs makes them impractical for many applications. Sodium-based batteries (SBBs) are gaining traction as a more affordable option, with costs of $50 to $100 per kWh and an abundant resource base. Despite these advantages, SBBs still face many obstacles, primarily due to limited research on sodium-based chemistries. Additionally, sodium-based batteries have inherent limitations, including lower energy capacity and reduced cycle life, which restrict their viability for long-term use. This thesis addresses several critical challenges faced by SBBs and explores new strategies for enhancing their performance and viability for large-scale applications. First, a low-concentration, non-flammable electrolyte consisting of 0.3 M NaPF6 in a mixed solvent was formulated and tested in SBBs. This electrolyte significantly improves the cyclability and performance of SBBs across a wide temperature range, with high-capacity retention at both elevated and sub-zero temperatures. Molecular simulations reveal that the improved ion-pairing underpins the exceptional performance. This development addresses major challenges in SBBs by offering a safer, more cost-effective solution for large-scale applications. Second, sodium-sulfur (Na-S) batteries were explored to achieve high energy densities. An external acoustic field was implemented to enhance Na-S battery performance by inhibiting the shuttle effect and reducing dendrite growth, two key challenges in Na-S systems. This method offers a scalable, non-chemical solution to improve cycle life and efficiency, making Na-S batteries a more viable candidate for large-scale energy storage. This progress, along with the high theoretical capacity of Na-S batteries, helps address the limitations not resolved by the electrolyte engineering work of SBBs. Third, the mechanisms of Na2Sx (x≤2) precipitation in sodium-sulfur (Na-S) and sodium-oxygen-sulfur (Na/O2-S) systems were investigated. The results reveal that higher-order sodium polysulfides display the lowest current density, indicating a stronger driving force is needed to initiate their reaction. In Na/(O2)-S systems, the transition from high-order to low-order oxy-sulfur intermediates demands less energy compared to Na-S systems. The insights gained here help further optimize Na-S/Na/(O2)-S batteries to enhance their performance and cycle life. Together, the work in this dissertation addressed several critical needs in the development of SBBs and helped advance their commercialization.
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    The Design and Optimization of a Lithium-ion Battery Direct Recycling Process
    Zheng, Panni (Virginia Tech, 2019-08-21)
    Nowadays, Lithium-ion batteries (LIBs) have dominated the power source market in a variety of applications. Lithium cobalt oxide (LiCoO2) is one of the most common cathode materials for LIBs in consumer electronics. The recycling of LIBs is important because cobalt is an expensive element that is dependent on foreign sources for production. Lithium-ion batteries need to be recycled and disposed properly when they reach the end of life (EOL) to avoid negative environmental impact. This project focuses on recycling cathode material (LiCoO2) by direct method. Two automation stages, tape peeling stage and unrolling stage, are designed for disassembling prismatic winding cores. Different sintering conditions (e.g., temperature, sintering atmosphere, the amount of lithium addition) are investigated to recycle EOL cathode materials. The results show that the capacity of the recycled cathode materials increases with increasing temperature. The extra Li addition leads to worse cycling performance. In addition, the sintering atmosphere has little influence on small- scale sintering. Also, most of directly recycled cathode materials have better electrochemical (EC) performance than commercial LiCoO2 (LCO) from Sigma, especially when cycling with 4.45V cutoff voltage.
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    Direct Lithium-ion Battery Recycling to Yield Battery Grade Cathode Materials
    Ge, Dayang (Virginia Tech, 2019-08-05)
    The demand for Lithium-ion batteries (LIBs) has been growing exponentially in recent years due to the proliferation of electric vehicles (EV). A large amount of lithium-ion batteries are expected to reach their end-of-life (EOL) within five to seven years. The improper disposal of EOL lithium-ion batteries generates enormous amounts of flammable and explosive hazardous waste. Therefore, cost-effectively recycling LIBs becomes urgent needs. Lithium nickel cobalt manganese oxides (NCM) are one of the most essential cathode materials for EV applications due to their long cycle life, high capacity, and low cost. In 2008, 18.9% of Lithium-ion batteries used NCM cathode material worldwide while this number increased to 31% six years later. An environment–friendly and low-cost direct recycling process for NCM has been developed in this project. The goal of this project is to recycle the EOL NCM and yield battery-grade NCM with equivalent electrochemical performance compared to virgin materials. In order to achieve this goal, four different heat treatment conditions are investigated during the direct recycling process. From the experimental results, the charge and discharge capacities of the recycled material are stable (between 151-155 mAh/g) which is similar to that of the commercial MTI NCM when sintered at 850 °C for 12 hours in the air. In addition, the cycling performance of recycled NCM is better than the commercial MTI NCM up to 100 cycles.
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    Electrochemical Flow System for Li-Ion Battery Recycling and Energy Storage
    Yang, Tairan (Virginia Tech, 2021-11-09)
    The wide applications of energy storage systems in consumer electronics, electric vehicles, and grid storage in the recent decade has created an enormous market globally. The electrochemical flow system has many applications in Li-ion battery recycling and energy storage system design. First, research work on a scalable electrochemical flow system is presented to effectively restore the lithium concentration in end-of-life Li-ion cathode materials. An effective recycling process for end-of-life lithium-ion batteries could relieve the environmental burden and retrieve valuable cathode battery materials. The design is validated in a static configuration with both cathode loose powder and cathode electrode sheet. Materials with comparable electrochemical performance to virgin cathode materials are produced after post heat treatment. Second, research contributions in sulfur-based flow battery systems for long-duration energy storage are presented. Sulfur-based redox flow batteries are promising due to their high theoretical capacity, low cost, and high abundance. The speciation of aqueous sulfur solutions with different nominal concentrations, sulfur concentrations, and pH are studied by Raman spectroscopy. Next, a promising aqueous manganese catholyte to couple with the sulfur anolyte for a full flow battery is investigated. Test protocols and quantification metrics for the catholyte are developed. The stability of the catholyte, including self-discharge rate and precipitation rate, is measured via ex-situ characterizations. The electrochemical performance of the catholyte is investigated and optimized via in-situ experiments. The reaction pathway for the precipitation of catholyte is discussed and several mitigation strategies are proposed. Finally, a semi-solid sodium-sulfur flow battery is developed. The electrochemical performance of the sodium-sulfur battery is studied first in a static configuration at an intermediate temperature (150°C). Then a Na-S semi-solid flow cell is assembled and cycled under the two-aliquots and three-aliquots intermittent flow.
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    Electrochemical Stability and Reversibility of Aqueous Polysulfide Electrodes Cycled Beyond the Solubility Limit
    Pan, Menghsuan Sam; Su, Liang; Eiler, Stephanie L.; Jing, Linda W.; Badel, Andres F.; Li, Zheng; Brushett, Fikile R.; Chiang, Yet-Ming (Electrochemical Society, 2022-06)
    Batteries which use dissolved redox-active species, such as redox flow batteries (RFBs), are often considered to be constrained in their operation and energy density by the solubility limit of the redox species. Here, we show that soluble redox active electrolytes can be reversibly cycled deeply into the precipitation regime, permitting higher effective concentrations, energy densities, and lower costs. Using aqueous sodium polysulfide negative electrolytes cycled in the nominal Na2S2 to Na2S4 capacity range as an example, we show that the effective solubility can be increased from 5 M in the fully-dissolved state to as much as 10 M using the precipitation strategy. Stable cycling was observed at 8 M concentration over more than 1600h at room temperature. We also analyze the range of polysulfide electrochemical stability, and characterize the precipitate composition. This enhanced effective concentration approach may be generalized to other redox chemistries that utilize solubilized reactants, and may be especially useful for long-duration storage applications where slow charge-discharge rates allow equilibration of precipitated species with the redox-active solution.
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    Enabling Intelligent Recovery of Critical Materials from Li-ion Battery through Direct Recycling Process with Internet-of-Things
    Lu, Yingqi; Han, Xu; Li, Zheng (MDPI, 2021-11-24)
    The rapid market expansion of Li-ion batteries (LIBs) leads to concerns over the appropriate disposal of hazardous battery waste and the sustainability in the supply of critical materials for LIB production. Technologies and strategies to extend the life of LIBs and reuse the materials have long been sought. Direct recycling is a more effective recycling approach than existing ones with respect to cost, energy consumption, and emissions. This approach has become increasingly more feasible due to digitalization and the adoption of the Internet-of-Things (IoT). To address the question of how IoT could enhance direct recycling of LIBs, we first highlight the importance of direct recycling in tackling the challenges in the supply chain of LIB and discuss the characteristics and application of IoT technologies, which could enhance direct recycling. Finally, we share our perspective on a paradigm where IoT could be integrated into the direct recycling process of LIBs to enhance the efficiency, intelligence, and effectiveness of the recycling process.
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    Frequency Response Modeling of Additive Friction Stir Deposition Parts with Print Defects
    Pennington, Brett Kenneth (Virginia Tech, 2024-06-03)
    A change in a part's response to vibrations can be measured and utilized as a non-destructive testing method to detect deviations in the part's materials or geometry through processes such as laser acoustic resonance spectroscopy. This work focuses on leveraging vibration resonance to detect flaws in prints produced through additive friction stir deposition that arise through environmental contamination. More specifically, the use case considered is the printing of AA7075 in an iron oxide rich environment, where iron oxide dust or powder could accidentally be stirred into the printed material creating a print flaw. The modeling of printed parts contaminated with iron oxide to predict their natural frequencies is examined. Two different finite element models are discussed, which were created to represent contamination flaws with and without voids. The first model considers the case where a part is void-free. In this case, the model assumes a solid, homogeneous material condition in the stir region. The second model considers the case where voids are present in the part. This model leverages x-ray computed tomography data to build a representative mesh. These models show that with a well-understood part and corresponding flaw, it is possible to predict the natural frequencies of a flawed part. By leveraging the part vibration measurements and model predictions of known defects, it may be possible to gain insights into and characterize unknown print flaws.
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    Green Manufacturing and Direct Recycling of Lithium-Ion Batteries
    Lu, Yingqi (Virginia Tech, 2020-09-03)
    According to the International Energy Agency, the global Electric Vehicle (EV) sales are experiencing approximately 24% annual growth and the total market could reach 4 million in 2020 and 21.5 million by 2030. However, the mass production of lithium-ion batteries (LIBs) to power EV creates concerns over environmental impacts and the long-term sustainability of critical elements for producing the major battery components. Although much investment has been made, it is still imperative to develop an effective LIB production and recycling process. This dissertation demonstrates a green and sustainable paradigm for LIBs where the batteries are manufactured and direct recycled to form a closed loop. The water-based cathode electrode delivers comparable cycle life and rate performance to the ones from the conventional organic solvent-based process. The direct recycling process has the advantages to regenerate the cathode material from electrode instead of decomposing into elements. Utilization of a water-soluble binder enables separating the cathode compound from spent electrodes using water, which is then successfully regenerated to deliver comparable electrochemical performance to the pristine one. When scaled up, the degraded cathode material can be directly regenerated by an optimized relithiation thermal synthesis (RTS) method to resynthesize the homogeneous cathode powder of high quality. The key factors and sintering procedures are studied to ensure the performance of the product. The pilot scale test successfully scales up to Kg-level with recycled output materials delivering good electrochemical performance. To automate the direct recycling process and improve the efficiency, machine learning and sensors are utilized in a novel battery disassembly platform. It can classify different batteries based on their types and sizes. The processing temperature is instantly monitored using thermal imager, and the prediction model is trained to give the prediction for measures taken by a closed loop control system. Furthermore, the image recognition is employed for quality control after the cutting process and the defect can be mitigated to ensure effective dismantling of End-of-life (EOL) batteries. The integration of machine learning techniques makes the elaborate dismantling process safer and more efficient.
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    Impacts of Energy Development on Texas Roads
    Li, Zheng; Mikhail, Magdy (2015-06-04)
    The production and exploration of oil and gas in Texas has been ongoing for many years. Recently, Texas has seen a tremendous increase in the exploration and production of energy resources. The number of completed oil and gas wells has almost tripled since 2011. The increase in energy-related activity has greatly benefited the state economy, however, the production of oil and gas generates large numbers of heavy trucks traveling on roads which were not originally designed to handle high-intensity truck traffic. Over time, the large volumes of heavy truck traffic have damaged the roads and significantly reduced their service life. The problem is particularly acute in the counties that have experienced the oil and gas drilling boom. These counties have experienced a more than ten percentage point drop in their percentage of lane miles in "Good" or better condition in just one year. Due to the lack of adequate funding, it is a challenge to maintain existing infrastructure and ensure the transportation system can serve the energy sector in the future. This paper illustrates the impacts of the energy development activities on the state maintained roads, and compares the differences between proactive and reactive maintenance approaches using a case study on a typical Farm-to-Market road. In addition, some of the mitigation strategies implemented in Texas were documented in this paper. The analysis methodology, findings, and strategies documented in this paper can be used by other transportation agencies to mitigate damages caused by the energy sector.
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    Intermittent Water Supply Management, Household Adaptation, and Drinking Water Quality: A Comparative Study in Two Chinese Provinces
    Li, Hongxing; Cohen, Alasdair; Li, Zheng; Lv, Shibo; He, Zuan; Wang, Li; Zhang, Xinyi (MDPI, 2020-05-12)
    Intermittent water supply (IWS) is a relatively common phenomenon across the world as well as in rural and peri-urban areas across China, though there has been little IWS-focused research from China published to date. IWS consumers typically adopt a range of strategies to cope with insufficient water supply, poor drinking water quality, and associated inconveniences. In this study, we collected a range of data from small-scale utilities and households in two IWS systems and two continuous water supply (CWS) systems, as well as from comparison groups, in Shandong and Hubei provinces. Data collection included water quality testing, interviews, and surveys on behavioral adaptations, coping strategies, water-related health perceptions, and other metrics of consumer satisfaction. Overall, we found that the IWS coping strategies employed in northern China (Shandong) were associated with generally safe, but inconvenient, water access, whereas adaptation strategies observed in southern China (Hubei) appeared to improve convenience, but not water quality. Compared to the CWS comparison groups, we did not observe significant differences in water- and sanitation-related behaviors in the IWS groups, suggesting interventions to increase adaptive and protective behaviors at the household level might further improve safe water access for households living with IWS. Overall, although the water supply infrastructure in these study areas appeared to be in relatively good condition, in contrast to reported data on IWS systems in other countries, we observed multiple risk factors associated with the water treatment and distribution processes in these IWS systems. Among policy recommendations, our results suggest that the implementation of Water Safety Plans in China would likely improve the management of drinking water treatment and, by extension, safe drinking water supply under conditions of IWS.
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    The Material Separation Process for Recycling End-of-life Li-ion Batteries
    Li, Liurui (Virginia Tech, 2020-10-27)
    End-of-life lithium-ion batteries retired from portable electronics, electric vehicles (EVs), and power grids need to be properly recycled to save rare earth metals and avoid any hazardous threats to the environment. The recycling process of a Lithium-ion Battery Cell/Module includes storage, transportation, deactivation, disassembly, and material recovery. This study focused on the disassembly step and proposed a systematic method to recover cathode active coating, which is considered the most valuable component of a LIB, from end-of-life LIB pouch cells. A semi-destructive disassembly sequence is developed according to the internal structure of the LIB cell. A fully automated disassembly line aiming at extracting cathode electrodes is designed, modeled, prototyped, and demonstrated based on the disassembly sequence. In order to further obtain the coating material, the extracted cathode electrodes are treated with the organic solvent method and the relationship between process parameters and cathode coating separation yield is numerically studied with the help of Design of Experiment (DOE). Regression models are then fitted from the DOE result to predict the cathode coating separation yield according to combinations of the process parameters. The single cell material separation methodology developed in this study plays an important role in the industrial application of the direct recycling method that may dominate the battery recycling market due to its environmental friendly technology and high recovery rate regardless of element type in the short future.
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    Multiscale chemistry and design principles of stable cathode materials for Na-ion and Li-ion batteries
    Rahman, Muhammad Mominur (Virginia Tech, 2021-06-03)
    Alkali-ion batteries have revolutionized modern life through enabling the widespread application of portable electronic devices. The call for adapting renewable energy in many applications will also see an increase in the demand of alkali-ion batteries, specially to account for the intermittent nature of the renewable energy sources. However, the advancement of such technologies will require innovation on the forefront of materials development as well as fundamental understanding on the physical and chemical processes from atomic to device length scales. Herein, we focus on advancing energy storage devices such as alkali-ion batteries through cathode materials development and discovery as well as fundamental understanding through multiscale advanced synchrotron spectroscopic and microscopic characterizations. Multiscale electrochemical properties of cathode materials are unraveled through complementary characterizations and design principles are developed for stable cathode materials for alkali-ion batteries. In Chapter 1, we provide a comprehensive background on alkali-ion batteries and cathode materials. The future prospect of Li-ion and beyond Li-ion batteries are summarized. Surface to bulk chemistry of alkali-ion cathode materials is introduced. The prospect of combined cationic and anionic redox processes to enhance the energy density of cathode materials is discussed. Structural and chemical complexities in cathode materials during electrochemical cycling as well as due to anionic redox are summarized. In Chapter 2, we explain an inaugural effort on tuning the 3D nano/mesoscale elemental distribution of cathode materials to positively impact the electrochemical performance of cathode materials. We show that engineering the elemental distribution can take advantage of depth dependent redox reactions and curtail harmful side reactions at cathode-electrolyte interface which can stabilize the electrochemical performance. In Chapter 3, we show that the surface to bulk chemistry of cathode particles is distinct under applied electrochemical potential. We show that the severe surface degradation at the beginning stages of cycling can impact the long-term cycling performance of cathode materials in alkali-ion batteries. In Chapter 4, we utilize the structural and chemical complexities of sodium layered oxide materials to synthesize stable cathode materials for half cell and full cell sodium-ion batteries. Meanwhile, challenges with enabling long term cycling (more than 1000 cycles) are deciphered to be transition metal dissolution and local and global structural transformations. In Chapter 5, we utilize anionic redox in conjunction with conventional cationic redox of cathode materials for alkali-ion batteries to enhance the energy density. We show that the stability of anionic redox is closely related to the local transition metal environment. We also show that a reversible evolution of local transition metal environment during cycling can lead to stable anionic redox. In Chapter 6, we provide design principles for cathode materials for advanced alkali-ion batteries for application under extreme environments (e.g., outer space and nuclear power industries). For the first time, we systematically study the microstructural evolution of cathode materials under extreme irradiation and temperature to unravel the key factors affecting the stability of battery cathodes. Our experimental and computational studies show that a cathode material with smaller cationic antisite defect formation energy than another is more resilient under extreme environments.
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    One thousand plant transcriptomes and the phylogenomics of green plants
    Leebens-Mack, James H.; Barker, Michael S.; Carpenter, Eric J.; Deyholos, Michael K.; Gitzendanner, Matthew A.; Graham, Sean W.; Grosse, Ivo; Li, Zheng; Melkonian, Michael; Mirarab, Siavash; Porsch, Martin; Quint, Marcel; Rensing, Stefan A.; Soltis, Douglas E.; Soltis, Pamela S.; Stevenson, Dennis W.; Ullrich, Kristian K.; Wickett, Norman J.; DeGironimo, Lisa; Edger, Patrick P.; Jordon-Thaden, Ingrid E.; Joya, Steve; Liu, Tao; Melkonian, Barbara; Miles, Nicholas W.; Pokorny, Lisa; Quigley, Charlotte; Thomas, Philip; Villarreal, Juan Carlos; Augustin, Megan M.; Barrett, Matthew D.; Baucom, Regina S.; Beerling, David J.; Benstein, Ruben Maximilian; Biffin, Ed; Brockington, Samuel F.; Burge, Dylan O.; Burris, Jason N.; Burris, Kellie P.; Burtet-Sarramegna, Valerie; Caicedo, Ana L.; Cannon, Steven B.; Cebi, Zehra; Chang, Ying; Chater, Caspar; Cheeseman, John M.; Chen, Tao; Clarke, Neil D.; Clayton, Harmony; Covshoff, Sarah; Crandall-Stotler, Barbara J.; Cross, Hugh; dePamphilis, Claude W.; Der, Joshua P.; Determann, Ron; Dickson, Rowan C.; Di Stilio, Veronica S.; Ellis, Shona; Fast, Eva; Feja, Nicole; Field, Katie J.; Filatov, Dmitry A.; Finnegan, Patrick M.; Floyd, Sandra K.; Fogliani, Bruno; Garcia, Nicolas; Gateble, Gildas; Godden, Grant T.; Goh, Falicia (Qi Yun); Greiner, Stephan; Harkess, Alex; Heaney, James Mike; Helliwell, Katherine E.; Heyduk, Karolina; Hibberd, Julian M.; Hodel, Richard G. J.; Hollingsworth, Peter M.; Johnson, Marc T. J.; Jost, Ricarda; Joyce, Blake; Kapralov, Maxim V.; Kazamia, Elena; Kellogg, Elizabeth A.; Koch, Marcus A.; Von Konrat, Matt; Konyves, Kalman; Kutchan, Toni M.; Lam, Vivienne; Larsson, Anders; Leitch, Andrew R.; Lentz, Roswitha; Li, Fay-Wei; Lowe, Andrew J.; Ludwig, Martha; Manos, Paul S.; Mavrodiev, Evgeny; McCormick, Melissa K.; McKain, Michael; McLellan, Tracy; McNeal, Joel R.; Miller, Richard E.; Nelson, Matthew N.; Peng, Yanhui; Ralph, Paula E.; Real, Daniel; Riggins, Chance W.; Ruhsam, Markus; Sage, Rowan F.; Sakai, Ann K.; Scascitella, Moira; Schilling, Edward E.; Schlosser, Eva-Marie; Sederoff, Heike; Servick, Stein; Sessa, Emily B.; Shaw, A. Jonathan; Shaw, Shane W.; Sigel, Erin M.; Skema, Cynthia; Smith, Alison G.; Smithson, Ann; Stewart, C. Neal, Jr.; Stinchcombe, John R.; Szovenyi, Peter; Tate, Jennifer A.; Tiebel, Helga; Trapnell, Dorset; Villegente, Matthieu; Wang, Chun-Neng; Weller, Stephen G.; Wenzel, Michael; Weststrand, Stina; Westwood, James H.; Whigham, Dennis F.; Wu, Shuangxiu; Wulff, Adrien S.; Yang, Yu; Zhu, Dan; Zhuang, Cuili; Zuidof, Jennifer; Chase, Mark W.; Pires, J. Chris; Rothfels, Carl J.; Yu, Jun; Chen, Cui; Chen, Li; Cheng, Shifeng; Li, Juanjuan; Li, Ran; Li, Xia; Lu, Haorong; Ou, Yanxiang; Sun, Xiao; Tan, Xuemei; Tang, Jingbo; Tian, Zhijian; Wang, Feng; Wang, Jun; Wei, Xiaofeng; Xu, Xun; Yan, Zhixiang; Yang, Fan; Zhong, Xiaoni; Zhou, Feiyu; Zhu, Ying; Zhang, Yong; Ayyampalayam, Saravanaraj; Barkman, Todd J.; Nam-Phuong Nguyen; Matasci, Naim; Nelson, David R.; Sayyari, Erfan; Wafula, Eric K.; Walls, Ramona L.; Warnow, Tandy; An, Hong; Arrigo, Nils; Baniaga, Anthony E.; Galuska, Sally; Jorgensen, Stacy A.; Kidder, Thomas I.; Kong, Hanghui; Lu-Irving, Patricia; Marx, Hannah E.; Qi, Xinshuai; Reardon, Chris R.; Sutherland, Brittany L.; Tiley, George P.; Welles, Shana R.; Yu, Rongpei; Zhan, Shing; Gramzow, Lydia; Theissen, Gunter; Wong, Gane Ka-Shu (2019-10-31)
    Green plants (Viridiplantae) include around 450,000-500,000 species(1,2) of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life.
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    Parameter optimization and yield prediction of cathode coating separation process for direct recycling of end-of-life lithium-ion batteries
    Li, Liurui; Yang, Tairan; Li, Zheng (2021-07-21)
    Fast adoption of lithium-ion batteries (LIBs) for electric vehicles requires an effective LIB recycling process to recover the valuable battery components and alleviate the concerns over the disposal of hazardous waste. The retrieval efficiency of cathode materials in direct recycling of end-of-life (EOL) lithium-ion batteries is systematically studied using the Taguchi Design of Experiment (DoE) method for the first time. A mathematical regression model is also developed to predict the yield and guide the parameter selection.
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    Scalable Fabrication of High Efficiency Hybrid Perovskite Solar Cells by Electrospray
    Jiang, Yuanyuan (Virginia Tech, 2019-06-18)
    Perovskite solar cells have attracted much attention both in research and industrial domains. An unprecedented progress in development of hybrid perovskite solar cells (HPSCs) has been seen in past few years. The power conversion efficiencies of HPSCs has been improved from 3.8% to 24.2% in less than a decade, rivaling that of silicon solar cells which currently dominate the solar cell market. Hybrid perovskite materials have exceptional opto-electrical properties and can be processed using cost-effective solution-based methods. In contrast, fabrication of silicon solar cells requires high-vacuum, high-temperature, and energy intensive processes. The combination of excellent opto-electrical properties and cost-effective manufacturing makes hybrid perovskite a winning candidate for solar cells. As power conversion efficiencies of HPSCs improves beyond that of the established solar cell technology and their long-term stability increases, one of the crucial hurdles in the path to commercialization remaining to be adequately addressed is the cost-effective scalable fabrication. Spin-coating is the prevailing method for fabrication of HPSCs in laboratories. However, this technique is limited to small areas and results in excessive material waste. Two types of scalable manufacturing methods have been successfully demonstrated to fabricate HPSCs: (i) meniscus-assisted coating such as doctor-blade coating and slot-die coating; and (ii) dispersed deposition based on the coalescence of individual droplets, such as inkjet printing and spray coating. Electrospray printing belongs to the second category with advantages of high material utilization rate and patterning capability along with the scalability and roll-to-roll compatibility. In Chapter 3 of this dissertation, electrospray printing process is described for manufacturing of HPSCs in ambient conditions below 150 C. All three functional layers were printed using electrospray printing including perovskite layer, electron transport layer, and hole transport layer. Strategies for successful electrospray printing of HPSCs include formulation of the precursor inks with solvents of low vapor pressures, judicial choice of droplet flight time, and tailoring the wetting property of the substrate to suppress coffee ring effects. Implementation of these strategies leads to pin-hole free, low surface roughness, and uniform perovskite layer, hole transport layer and electron transport layer. The power conversion efficiency of the all electrospray printed device reached up to 15.0%, which is among the highest to date for fully printed HPSCs. The most efficient HPSCs rely on gold and organic hole-transport materials (HTMs) for achieving high performance. Gold is also chosen for its high stability. Unfortunately, the high price of gold and high-vacuum along with high-temperature processing requirements for gold film is not suitable for the large-scale fabrication of HPSCs. Carbon is a cheap alternative electrode material which is inert to hybrid perovskite layer. Due to the ambipolar transport property of hybrid perovskite, perovskite itself can act as a hole conductor, and the extra hole transport layer can be left out. Carbon films prepared by doctor-blade coating method have been reported as the top electrode in HPSCs. The efficiencies of these devices suffer from the poor interface between the doctor-blade coated carbon and the underlying perovskite layer. In Chapter 4, electrospray printing was applied for the fabrication of carbon films and by optimizing the working distance during electrospray printing, the interface between carbon and the underlying perovskite layer was greatly improved compared to the doctor-blade coated carbon film. The resulting HPSCs based on the electrospray printed carbon electrode achieved higher efficiency than that based on doctor-blade method and remarkably, this performance is close to that of gold based devices. In Chapter 5, preliminary results are provided on the laser annealing of hybrid perovskite films to further advance their scalable manufacturing. All layers of HPSCs require thermal annealing at temperature over 150 C for about half an hour or longer. The time-consuming conventional thermal annealing complicates the fabrication process and is not suitable for continuous production. High temperature over150 C is also not compatible with flexible substrates such as PET. Laser annealing is a promising method for overcoming these issues. It has several other advantages including compatibility with continuous roll-to-roll printing, minimal influence on non-radiated surrounding area, and rapid processing. Laser annealing can be integrated with the electrospray process to realize the continuous fabrication of hybrid perovskite film. Rapid laser annealing process with optimized power density and scanning pattern is demonstrated here for annealing perovskite films. The resulting hybrid perovskite film is highly-crystalline and pin-hole free, similar to that obtained from conventional thermal annealing.
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    The synthesis and characterization of sodium polysulfides for Na-S battery application
    Zhang, Qiaoyi (Virginia Tech, 2019-06-26)
    The limited understanding of the electrochemical mechanism of Na-S battery systems is a barrier to further improve the performance of the Na-S energy storage. The characterization of sodium polysulfides in the Na-S battery systems can offer insightful information to understand the electrochemical reaction mechanism of the Na-S batteries and overcome the "inert" nature of short-chain polysulfides (Na2Sn, 1
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    Understanding and Controlling the Degradation of Nickel-rich Lithium-ion Layered Cathodes
    Steiner, James David (Virginia Tech, 2018-10-08)
    Consumers use batteries daily, and the lithium-ion battery has undergone a lot of engineering advances in the last few decades. There is a need to understand and improve the cathode chemistry to adapt to the rapidly growing electronics and electric vehicle market that is continually demanding more energy from batteries. Nickel-rich layered LiNi1-x-yMnxCoyO₂ (1-x-y ≥ 0.6, NMC) cathodes could potentially provide the necessary energy to meet the demand of the high energy applications. Overcoming the stability issues from oxygen activation in nickel-rich materials is one of the largest challenges facing the commercial incorporation of NMCs. This thesis focuses on, LiNi0.8Mn0.1Co0.1 (NMC811). Using surface sensitive techniques, such as Xray Absorption (XAS), our research reveals that degradation of NMC811 occurs during cycling, regardless of temperature, and that oxygen activation plays a role in the overall surface changes and degradation observed in NMC811. The thesis then explores the role of substituting a transition metal in the NMC811. Then we used a gradient addition of titanium to the NMC811 material to stabilize the battery performance. Theoretical techniques, such as Finite Difference Method Near Edge Structure, and experimental techniques, such as XAS, revealed how transition metal substitution, specifically titanium, stabilized the lattice. The results indicated that titanium deactivates oxygen by limiting the nickel and oxygen covalency that typically leads to oxygen activation upon charging. We observed that the titanium substitution increases cycling reversibility after hundreds of cycles. Overall, the work indicates that a more stable nickel-rich material is possible. It identifies the reasons why substitution can work in cathode materials. Additionally, the methods described can provide a guideline to further studies of stabilization of the cathode.
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    Unified Net Willans Line Model for Estimating the Energy Consumption of Battery Electric Vehicles
    Li, Candy Yuan (Virginia Tech, 2022-09-09)
    Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired for providing quick, high-level estimations for a BEV without requiring extensive vehicle and computational resources. Therefore, the goal of this paper is to create a simple, yet reliable vehicle model, that can estimate the energy consumption of most, if not all, electric vehicles on the market by using parameter normalization techniques. These vehicle parameters include the vehicle test weight and performance to obtain a unified net Willans line to describe the input/output power through a linear relationship. A base model and three normalized models are developed by fitting the UDDS and HWFET energy consumption test data published by the EPA for all BEVs in the U.S. market. Out of the models analyzed, the normalization with weight performs best with the lowest RMSE values at 0.384 kW, 0.747 kW, and 0.988 kW for predicting the UDDS, HWY, and US06 data points, respectively, and 0.653 kW for all three data sets combined. Consideration of accessory loads at 0.5 kW improves the model normalized by weight and performance by a reduction of over 20% in RMSE for predictions with all data sets combined. Removing outliers in addition to consideration of accessory loads improves the model normalized by weight and performance by a reduction of over 36% in RMSE for predictions with all data sets combined. Overall, results suggest that a unified net Willans line is largely achievable with accessible energy consumption data on U.S. regulatory cycles.