bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the Electrode/Electrolyte Interface Formation on Positive Electrodes of Li-Ion Batteries
Authors: Karayaylali Pinar , Giordano Livia , Yu Yang , Chang Hao-Hsun , Maglia Filippo , Lux Simon , Lund Isaac , Paschos Odysseas , Lamp Peter , Shao-Horn Yang 
Published: February 2020

Understanding electrode/electrolyte interface (EEI) is crucial for the development of high-energy batteries for electric vehicle applications. The EEI layer formation of negative electrode (also referred as Solid Electrolyte Interphase) is comprehensively studied [1,2], whereas the electrolyte decomposition and formation of the EEI layer at the positive electrodes are still unknown [3,4]. Especially, at high potentials, the role of oxygen in the transition metal oxide becomes critical, leading to the evolution of oxygen from the oxide lattice or the formation of highly reactive species like surface peroxide and superoxide, which can modify the nature of the EEI layer.
Here, we show how EEI layer depends on different positive electrodes (LiCoO2 and NMC electrodes with different Ni content) and different electrolyte additives (diphenyl carbonate and adiponitrile) by using X-ray Photoelectron Spectroscopy (XPS). We also highlight the importance of using carbon-free, binder-free electrodes to unambiguously pinpoint the reactivity of the electrolyte at the positive electrode [5]. The analysis of the XPS results points to a strong dependency of the surface reactivity on different electrode and electrolyte composition.
[1] E. Peled, J. Electrochem. Soc. 126, 2047 (1979).
[2] D. Aurbach et al., J. Power Sources 81-82, 95 (1999).
[3] K. Xu et al., Chem. Rev., 114, 11503 (2014).
[4] M. Gauthier, T. Carney, A. Grimaud et al., J. Phys. Chem. Lett. 6, 4653 (2015).
[5] M. Gauthier et al., in preparation.
Effects of Additives in Dual-Salt/Carbonate Electrolytes on Performances of Lithium Metal Batteries
Authors: Li Xing , Ren Xiaodi , Engelhard Mark H , Li Qiuyan , Zhao Wengao , Zheng Jianming , Adams Brian , Zhang Jason , Xu Wu 
Published: February 2020

The lithium (Li) metal battery (LMB) is a promising high-energy-density energy storage system. However, the uncontrollable dendrite formation and low Coulombic efficiency (CE) associated with the Li metal anode have largely hindered the practical application of LMBs [1]. During recent years, extensive efforts have been made to address the main problems of Li metal anode and to improve the electrochemical performance of the related LMBs, and plenty of promising results have been achieved. Among the reported approaches, the reformulation of electrolytes with different Li salts and additives has been regarded as an easy and cost-effective method. The conventional LiPF6/carbonate electrolytes have been found to be detrimental to Li metal anode especially at high charge current densities, which is mainly due to the serious corrosion of Li metal anode, the consumption of electrolyte, the continuous formation of solid electrolyte interphase, and the increase of cell impedance. The highly concentrated electrolytes of LiTFSI or LiFSI in ethers have been reported to be effective to suppress Li dendrites growth and to improve the Li CE [2]. However, the ether-based electrolytes normally are not electrochemically stable at the voltages around or above 4 V. In our previous works, we have systematically investigated the dual-salt electrolytes of LiTFSI-LiBOB in carbonate solvent mixture and their effects on the performances of Li||LiFePO4
[3], Li||LiNi0.80Co0.15Al0.05O2
[4]
battery systems. It has been found that the dual-salt electrolytes are favorable to protect Li metal anode and to improve the rate capability of the LMBs. Especially, our recent work discovered that further significant improvements in fast charging capability and long-term cycling stability of the Li||LiNi0.4Mn0.4Co0.2O2 batteries can be achieved by adding an optimal additive amount of LiPF6 to the LiTFSI-LiBOB/carbonate electrolyte [5]. Nevertheless, this electrolyte still leads to relatively low Li CE, which is about 90.6%.
In order to further improve the Li CE of the dual-salt/carbonate electrolyte, we systematically investigated different additives such as VC, FEC, VEC, etc. By using certain additives the Li CE in the electrolytes of LiTFSI-LiBOB dual-salt in carbonate solvents can be improved from 90.6% to 98.1%. Moreover, the electrochemical performances of the LMBs with a 4-V Li-ion cathode using the newly developed dual-salt electrolytes were studied, and enhanced battery performances have been obtained. The promising results will be reported at the meeting.
Optimization of Crystal Structures for Cathode Materials of Li-Ion Battery Using Genetic Algorithm
Authors: Otake Masanari , Nakayama Masanobu 
Published: February 2020

New cathode materials of Li-ion battery which realize large-reversible capacity are demanded urgently. Computational method is promising approach of material search and analysis. However, calculation of nonstoichiometric composition is technically difficult due to large degree of configuration freedom. To optimize structure with reasonable time, genetic algorithm (GA) is used in this study. To evaluate GA-derived structure, we used BV-FF calculations [1].
As an example, the variation of total energy of Li16Co16O32 for GA driven structures as a function of generation is shown in Fig.1. The structure framework is cation-disordered rocksalt-type structure and there are 32 cation site and degree of freedom of cation arrangement is 6×108. The red line indicates the lowest energy of GA generated structures among present and previous generations. Fig.2 shows the most stable structure obtained by GA. Green and blue colored octahedra correspond to LiO6 and CoO6, respectively. We confirmed the cation arrangement of most stable structure is layered rocksalt-type structure.

Reference [1] S.Adams et al, physica status solidi (a), 208(8), 1746-1753 (2011)

Figure 1
Lithium Dendrite Suppression By Polyethylene Oxide Film Coating on Copper Electrode Enable Lithium Metal Anode
Authors: Assegie Addisu Alemayehu , Hwang Bing-Joe , Cheng Ju-Hsiang , Su Wei-Nien , Kuo Li-Ming 
Published: February 2020

Efforts to realize lithium metal as anode limited by dendrite formation and low Coulombic efficiency. These challenges stem from extensive reaction of lithium with electrolyte, deposition of more dead lithium and formation of unstable solid electrolyte interface. Herein, we revealed a homogeneous lithium deposition and dendrite suppression via regulating lithium flux with polyethylene oxide (PEO) film coated copper electrode in 1M LiTFSI, DME/DOL (v/v 1/1) and 2 wt% LiNO3 electrolyte. PEO coating reinforces a thin and robust SEI layer film formation by hosting lithium and regulating the inevitable reaction of lithium with electrolyte. The modified electrode showed a stable and an extremely excellent Coulombic efficiency over 200 cycles with low voltage hysteresis (~30 mV) at rate of 1 C. In comparison the modified electrode tested with 1M LiPF6, EC/DEC (v/v 1/1) electrolyte and showed a rapid capacity fading due to PEO film damage with fluoride ion interaction. This enhanced cycle life and capacity retention results from the synergy of PEO coating, high electrode-electrolyte interface compatibility, stable polar oligomer formation from reduction of 1, 3-dioxolane and generation of SEI stabilizing nitrite and nitride upon lithium nitrate reduction in an ether electrolyte.
eQUMEC Software: Multiscale and Multiphysics Simulation/Designing of Li-Ion Batteries
Authors: Hosseinzadeh Hamed 
Published: February 2020

eQUMEC software has been developed to design Li-ion batteries and other electrochemical systems like Li-air batteries and hybrid supercapacitors. This software has a 3D user interface to design the shape of electrochemical cell and related internal components. Microstructure of active materials could be defined by user such as powders size, shape and density. Conductive and adhesive materials could be also added to active materials. Defining and adding any kinds of electrolytes would be very simple in this software. eQUMEC has a toolbox for applying different charge and discharge conditions (constant voltage or constant current). eQUMEC has also other modules for calculating temperature and stress evolution during charging and discharging. This software has several more options like battery management systems (BMS) and thermal management systems (TMS). At last, voltage vs capacity, current/voltage vs time, Li ions concentration evolution in Li-ion cell and several other outputs would be extracted via a successful simulation. eQUMEC has several computational algorithms. The main computational algorithm is a coupled multiscale/multiphysics Fickian approach for ionic diffusion in active materials, Poisson Equation solver for potential in electrolyte, related conservative equation solver for calculating temperature and other equations solver to capture phenomena at interface of active materials and electrolyte. This software could be used by researchers and designers at research institutes, universities and companies to simulate new Li-ion batteries performance.
Figure caption: eQUMEC software interface which is showing cathode powders, final cell shape and calculated profile of Li ions concentration during charging.

Figure 1
A Survey on High Rate Performance of LiNi0.5Mn1.5O4 As Cathode of Li-Ion Battery
Authors: Hosseinzadeh Hamed 
Published: February 2020

In this research, high rate performance of LiNi0.5Mn1.5O4 cathode has been explained in details by a model, numerical simulation technique and experimental verification. The proposed model which was verified by experimental data and simulation could estimate the capacity dependency of LiNi0.5Mn1.5O4 to diffusion coefficient of lithium ions in active materials and c-rate of discharging. Results showed that LiNi0.5Mn1.5O4 has capacity higher than 80 mAhg-1 even for c-rate up to 10C discharging and facilitating the movement of lithium ions in active material and reducing thickness of electrolyte has reasonable impact on achievable final capacity of LiNi0.5Mn1.5O4. In addition, higher rate performance of mentioned active material would be enhanced by an increase in Li ion diffusion coefficient from 10-11 cm2.s-1 to 5×10-10 cm2.s-1 which was explained and verified by experiment. Achieved capacity at 200C would be less than 40 mAh.g-1 in cathode materials with Li ion diffusion coefficient 10-11 cm2.s-1. Whereas, cathode materials with Li ion diffusion coefficient 5×10-10 cm2.s-1 showed achieved capacity higher than 100 mAh.g-1 at 200C.

Figure 1
ALD Al2O3 Coated TiO2 Nanotube Layers As Anodes for Lithium Ion Batteries
Authors: Sopha Hanna , Salian Girish , Zazpe Raul , Prikryl Jan , Hromadko Ludek , Djenizian Thierry , Macak Jan M. 
Published: February 2020

Alumina coatings produced by Atomic layer deposition (ALD) on electrode materials have been explored extensively. Alumina coatings generally, have been used as a protective layer for the suppression of the solid electrolyte interphase (SEI) in various electrode materials.1 But its influence on increasing the electronic conductivity of the electrode material has not been explored. TiO2 nanotubes have been recently explored due to its low volume expansion, good capacity retention even at faster kinetics.2 The utilization of anodic TiO2 nanotube layers with uniform Al2O3 coatings of different thicknesses (prepared by atomic layer deposition, ALD) as new electrode material for lithium-ion batteries (LIBs) is reported. Electrodes with very thin Al2O3 coatings (~1 nm) show a superior electrochemical performance for the use in lithium ion batteries compared to uncoated TiO2 nanotube layers. A more than two times higher capacity is received on these coated TiO2 nanotube layers (~75 µAh/cm2 vs 200 µAh/cm2 at 1 C) as well as a higher rate capability and coulombic efficiency. Reasons for this can be attributed to a better diffusion of Li+ ions within the coated nanotube layers. However, thicker ALD Al2O3 coatings result in a passivation of the electrode surface and, therefore, in a capacity decrease. Fig. 1(a) shows the influence of alumina coating with different thickness on the capacity of the TiO2 nanotube layer. Fig.1(b) shows the long term cycling of the 1 nm alumina coated and the uncoated TiO2nanotube layers at 1C. In this work, factors influencing the increase in capacity due to the alumina coating will be discussed using results from different electrochemical characterization methods.
Fig. 1 (a) Galvanostatic cycling of the uncoated and the coated TiO2 nanotube layers at 1C (b) Long term galvanostatic cycling of the 1 nm thick alumina coated and uncoated TiO2nanotube layers at 1 C for 100 cycles.
References
1) Jung, Y. S.; Cavanagh, A. S.; Riley, L. A.; Kang, S.-H.; Dillon, A. C.; Groner, M. D.; George, S. M.; Lee, S.-H. Ultrathin Direct Atomic Layer Deposition on Composite Electrodes for Highly Durable and Safe Li-Ion Batteries. Adv.Mater. 2010, 22, 2172-2176.
2) Ortiz, G. F.; Hanzu, I.; Djenizian, T.; Lavela, P.; Tirado, J. L.; Knauth, P.; Alternative Li-Ion Battery ElectrodeBased on Self-Organized Titania Nanotubes. Chem. Mater. 2009, 21, 63-67.

Figure 1
A Study of Esters As Co-Solvents in Lithium-Ion Batteries
Authors: Ma Xiaowei , Senthil Arumugam Rajalakshmi , Glazier Stephen , Ma Lin , Xia Jian , Dahn Jeff R 
Published: February 2020

Abstract:

Higher rate capability in Li-ion batteries is always better. Using esters as a co-solvent can significantly improve the rate capability of Li-ion batteries because of their low viscosity which leads to higher electrolyte conductivity [1, 2]. However, which ester is the best to use from a cell lifetime perspective? In this work, the four esters, methyl acetate (MA), methyl propionate (MP), ethyl acetate (EA) and methyl butyrate (MB) were compared as co-solvents in the electrolytes of Li-ion pouch cells at levels from 0% to 60 % by weight. Experiments included high temperature storage, ultra high precision coulometry, high rate charge to determine the onset of lithium plating, long term cycling and isothermal microcalorimetry. In addition, Gering’s Advanced Electrolyte Model was used to compare the conductivity and viscosity benefits associated with the use of each ester. The baseline electrolytes to which the esters were added were 1.2 M LiPF6 in EC:EMC 30:70 or 1.2 M LiPF6 in EC:EMC:DMC (25:5:70 by vol%). Figure 1 shows the results of 60oC storage tests for Li-ion pouch cells containing various amounts of each of the four esters. Cells were stored at either 4.2 V, to examine the stability of the positive electrode/electrolyte interface and at 2.5 V to examine the stability of the negative electrode SEI. Figure 1 shows that of the four esters, methyl acetate is greatly preferred based on the storage testing for this Li-ion cell chemistry.
Experiments involving many Li-ion cells chemistries and the four esters will be reported. Based on this work, tradeoffs involving the use of esters have been identified and will be discussed here.
[1] M. C. Smart, B. V. Ratnakumar, K. B. Chin, L. D. Whitcanack, J. Electrochem. Soc., 157, A1361 (2010).
[2] H.-C. Shiao, D. Chua, Hsiu-ping. Lin, S. Slane, M. Salomon, J. Power Sources, 87, 167 (2000).
Figure 1. Open circuit potential versus time of Li-ion pouch cells at 60±0.1oC with different ester contents: (a-d) cells containing MA, MP, EA and MB were precharged to 4.2V; (e-h) cells containing MA, MP, EA and MB were precharged to 2.5V.

Figure 1
Molecular Dynamics Simulations on Li-Ion Conduction in Nasicon-Type Solid Electrolytes
Authors: Noda Yusuke , Nakayama Masanobu 
Published: February 2020

As a promising solid electrolyte material for all-solid-state Li-ion batteries (LIBs), Na super ionic conductor (NASICON)-type material is considered to be comparable to perovskite-type or garnet-type ionic conductors. Since the discovery of the fast Na-ion conducting NASICON-type material of Na1+xZr2SixP3-xO12 in 1976 [1], many kinds of Li-ion conducting NASICON-type solid electrolytes have been investigated. One of the most popular among them is Li1+xAlxTi2-x(PO4)3 (LATP), which can be generated by partially substituting Ti4+ with Al3+ in LiTi2(PO4)3 (LTP). Especially, LATP with x = 0.3 exhibits enhanced bulk Li-ion conductivity in the order of 10-3 S/cm at room temperature [2,3]. However, it is also well known that LTP-based materials react with Li metal at around 2.5 V vs. Li+/Li due to the Ti4+/Ti3+ redox reaction [4,5]. Recently, another NASICON-type solid electrolyte LiZr2(PO4)3 (LZP) has been well studied, then it is known to be stable in contact with Li metal due to no redox reaction up to 5.5 V [6]. Therefore, NASICON-type materials would be alternative solid electrolytes for all-solid-state LIBs.
In this study, we estimate Li-ion conductivity and activation energy in NASICON-type solid electrolytes using molecular dynamics simulations. The Li-ion trajectory is also analyzed and discussed. The results and discussions will be shown in more detail in our presentation.

Acknowledgements

This work was supported by the “Materials research by Information Integration” Initiative (MI2I) project of the Support Program for Starting Up Innovation Hub from Japan Science and Technology Agency (JST).

References

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[5] S. Patoux and C. Masquelier, Chem. Mater. 14, 5057-5068 (2002).
[6] Y. Li, W. Zhou, X. Chen, X. Lü, Z. Cui, S. Xin, L. Xue, Q. Jia, and J. B. Goodenough, Proc. Natl. Acad. Sci. 113, 13313-13317 (2016).
(Keynote) Novel Computational Approaches in Practical Bioelectrocatalysis
Authors: Matanovic Ivana , Babanova Sofia , Chavez Madelaine Seow , Abdellaoui Sofiene , Minteer Shelley D. , Atanassov Plamen 
Published: February 2020

Computational approaches and tools play a fundamental role in modern science and have had an enormous impact on both fundamental and applied research across different scientific fields. This paper will describe some of the computational tools that can be used in concert with experimental approaches to explore various aspects in practical bioelectrocatalysis. This includes application of molecular docking simulations to explore new substrates for biocatalysts, which can enable development of novel synthetic catalytic cascades. Furthermore, we will show how docking simulations and first principles calculations can be combined with experimental approaches for a rational design of electrode surface modifications in biofuel cells and biosensors with enhanced performances.
Molecular docking simulations based on semi-empirical free energy force fields have the ability to efficiently and rapidly predict the binding-conformation of different ligands to a biomolecule with a known structure. Here, the fundamentals of docking simulations based on AutoDock, a suite of automated docking tools, will be presented together with several examples of their application in bioelectrocatalysis. We will first show how computational docking simulations can be used to predict the unexpected activity of the enzymes. Molecular docking simulations were used to predict the promiscuity of formate dehydrogenase from Candida boidinii (cbFDH) with mesoxalate, which was also tested with spectroscopic assays and characterization by HPLC and GC/TCD. Based on this assessment cbFDH was used in a combination with a molecular catalyst to create a hybrid cascade for complete electro-oxidation of glycerol to carbon dioxide (1). Density Functional Theory and docking simulations were further used to gain a fundamental understanding of the role that different small molecules, which are used to increase the efficiency of biocatalysts’ immobilization, have in the design and operation of enzymatic electrodes. These approaches were first used to explain the role of 1,2-benzoquinone, 1,4-benzoquinone, and ubiquinone on the operation and mechanism of electron transfer in PQQ-dependent soluble glucose dehydrogenase anode (2). The same approach was also combined with electrochemical measurements to explore the interaction of bilirubin oxidase and bilirubin modified graphene support for a design of oxygen reducing bio-cathodes based on bilirubin oxidase (3).
(1) S. Abdellaoui, M. Seow Chavez, I. Matanovic, A.Stephens, P. Atanassov, and S. Minteer. Chem. Commun.,Accepted, DOI:10.1039/C7CC01027C (2017).
(2) S. Babanova, I. Matanovic, M. Seow Chavez, and P. Atanassov, J. Am. Chem. Soc., 137, 7754-7762 (2015).
(3) I. Matanovic, S. Babanova, M. Seow Chavez, and P. Atanassov, J. Phys. Chem. B, 120, 3634−3641 (2016).

Figure 1
(Invited) Novel Nanostructured Catalyst Approaches for CO2 Electroreduction
Authors: Baturina Olga A , Lu Qin , Dyatkin Boris , Padilla Monica , Serov Alexey , Gogotsi Yury 
Published: February 2020

High-surface area catalysts are crucial for electrochemical devices that rely on kinetically-limited electrochemical reactions. Two commonly used approaches to increase catalyst surface area include (1) placement of catalyst nanoparticles on high surface area support and (2) synthesis of highly porous unsupported catalyst structures. In this presentation, we will discuss both approaches along with several previously unexpected phenomena that we had discovered and, eventually, used to highly selectively electrochemically reduce CO2 to C2H4 [1, 2].
Nanostructured supports that were selected for CO2 electroreduction studies include reduced graphene oxide (RGO), single walled carbon nanotubes (SWNT) and onion-like carbon (OLC) [3]. These three supports share some common features, such as good chemical and thermal stabilities and high specific surface areas. Cu nanoparticles were deposited on the three supports using traditional wet chemistry methods.
For synthesis of highly porous unsupported Cu structures, a scalable surficial support method was developed [4, 5] that led to production of Cu nanoparticles with the optimal cubic morphology [6].
References
[1] O.A. Baturina, Q. Lu, M.A. Padilla, L. Xin, W. Li, A. Serov, K. Artyushkova, P. Atanassov, F. Xu, A. Epshteyn, T. Brintlinger, M. Schuette, G. Collins, ACS Catalysis 4 (2014) 3682
[2] O. A. Baturina, Q. Lu, F. Xu, A. Purdy, B. Dyatkin, X. Sang, R. Unocic, T. Brintlinger, Y. Gogotsi, Catalysis Today (2016, DOI:10.1016/j.cattod.2016.11.001)
[3] J. K. McDonough, Y. Gogotsi, Interface, 22 (2013) 61.
[4] U. Martinez, A. Serov, M. Padilla, P. Atanassov, ChemSusChem 7 (2014) 2351
[5] A. Serov, N. I. Andersen, A. J. Roy, I. Matanovic, K. Artyushkova, P. Atanassov, J. Electrochem. Soc. 162 (2015) F449
[6] M. Padilla, O. Baturina, J. P. Gordon, K. Artyushkova, P. Atanassov, A. Serov, J. of CO2 Utilisation 19 (2017) 137