ترغب بنشر مسار تعليمي؟ اضغط هنا

Computational Screening of Current Collectors for Enabling Anode-free Lithium Metal Batteries

218   0   0.0 ( 0 )
 نشر من قبل Venkatasubramanian Viswanathan
 تاريخ النشر 2019
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

Lithium metal cells are key towards achieving high specific energy and energy density for electrification of transportation and aviation. Anode-free cells are the limiting case of lithium metal cells involving no excess lithium and the highest possible specific energy. In addition, anode-free cells are easier, cheaper and safer as they avoid handling and manufacturing of lithium metal foils. Issues related to dendrite growth and poor cycling are magnified in anode-free cells due to lack of excess lithium. Electrolyte and current collector surface play a crucial role in affecting the cycling performance of anode-free cells. In this work, we have computationally screened for candidate current collectors that can nucleate lithium effectively and allow uniform growth. These are determined by the free energy of lithium adsorption and lithium surface diffusion barrier on candidate current collectors. Using density functional theory calculations, we show that Li-alloys possess ideal characteristics for Li nucleation and growth. These can lead to vastly improved specific energy compared to current transition metal current collectors.

قيم البحث

اقرأ أيضاً

Lithium metal has been an attractive candidate as a next generation anode material. Despite its popularity, stability issues of lithium in the liquid electrolyte and the formation of lithium whiskers have kept it from practical use. Three-dimensional (3D) current collectors have been proposed as an effective method to mitigate whiskers growth. Although extensive research efforts have been done, the effects of three key parameters of the 3D current collectors, namely the surface area, the tortuosity factor, and the surface chemistry, on the performance of lithium metal batteries remain elusive. Herein, we quantitatively studied the role of these three parameters by synthesizing four types of porous copper networks with different sizes of well-structured micro-channels. X-ray microscale computed tomography (micro-CT) allowed us to assess the surface area, the pore size and the tortuosity factor of the porous copper materials. A metallic Zn coating was also applied to study the influence of surface chemistry on the performance of the 3D current collectors. The effects of these parameters on the performance were studied in detail through Scanning Electron Microscopy (SEM) and Titration Gas Chromatography (TGC). Stochastic simulations further allowed us to interpret the role of the tortuosity factor in lithiation. By understanding these effects, the optimal range of the key parameters is found for the porous copper anodes and their performance is predicted. Using these parameters to inform the design of porous copper anodes for Li deposition, Coulombic efficiencies (CE) of up to 99.56% are achieved, thus paving the way for the design of effective 3D current collector systems.
Next generation batteries based on lithium (Li) metal anodes have been plagued by the dendritic electrodeposition of Li metal on the anode during cycling, resulting in short circuit and capacity loss. Suppression of dendritic growth through the use o f solid electrolytes has emerged as one of the most promising strategies for enabling the use of Li metal anodes. We perform a computational screening of over 12,000 inorganic solids based on their ability to suppress dendrite initiation in contact with Li metal anode. Properties for mechanically isotropic and anisotropic interfaces that can be used in stability criteria for determining the propensity of dendrite initiation are usually obtained from computationally expensive first-principles methods. In order to obtain a large dataset for screening, we use machine learning models to predict the mechanical properties of several new solid electrolytes. We train a convolutional neural network on the shear and bulk moduli purely on structural features of the material. We use AdaBoost, Lasso and Bayesian ridge regression to train the elastic constants, where the choice of the model depended on the size of the training data and the noise that it can handle. Our models give us direct interpretability by revealing the dominant structural features affecting the elastic constants. The stiffness is found to increase with a decrease in volume per atom, increase in minimum anion-anion separation, and increase in sublattice (all but Li) packing fraction. Cross-validation/test performance suggests our models generalize well. We predict over 20 mechanically anisotropic interfaces between Li metal and 6 solid electrolytes which can be used to suppress dendrite growth. Our screened candidates are generally soft and highly anisotropic, and present opportunities for simultaneously obtaining dendrite suppression and high ionic conductivity in solid electrolytes.
A thick electrode with high areal capacity has been developed as a strategy for high-energy-density lithium-ion batteries, but thick electrodes have difficulties in manufacturing and limitations in ion transport. Here, we reported a new manufacturing approach for ultra-thick electrode with aligned structure, called structure electrode additive manufacturing or SEAM, which aligns active materials to the through-thicknesses direction of electrodes using shear flow and a designed printing path. The ultra-thick electrodes with high loading of active materials, low tortuous structure, and good structure stability resulting from a simple and scalable SEAM lead to rapid ion transport and fast electrolyte infusion, delivering a higher areal capacity than slurry-casted thick electrodes. SEAM shows strengths in design flexibility and scalability, which allows the production of practical high energy/power density structure electrodes.
Using first principles structure searching with density-functional theory (DFT) we identify a novel $Fmbar{3}m$ phase of Cu$_2$P and two low-lying metastable structures, an $Ibar{4}3d$--Cu$_3$P phase, and a $Cm$--Cu$_3$P$_{11}$ phase. The computed pa ir distribution function of the novel $Cm$--Cu$_3$P$_{11}$ phase shows its structural similarity to the experimentally identified $Cm$--Cu$_2$P$_7$ phase. The relative stability of all Cu--P phases at finite temperatures is determined by calculating the Gibbs free energy using vibrational effects from phonon modes at 0 K. From this, a finite-temperature convex hull is created, on which $Fmbar{3}m$--Cu$_2$P is dynamically stable and the Cu$_{3-x}$P ($x < 1$) defect phase $Cmc2_1$--Cu$_8$P$_3$ remains metastable (within 20 meV/atom of the convex hull) across a temperature range from 0 K to 600 K. Both CuP$_2$ and Cu$_3$P exhibit theoretical gravimetric capacities higher than contemporary graphite anodes for Li-ion batteries; the predicted Cu$_2$P phase has a theoretical gravimetric capacity of 508 mAh/g as a Li-ion battery electrode, greater than both Cu$_3$P (363 mAh/g) and graphite (372 mAh/g). Cu$_2$P is also predicted to be both non-magnetic and metallic, which should promote efficient electron transfer in the anode. Cu$_2$Ps favorable properties as a metallic, high-capacity material suggest its use as a future conversion anode for Li-ion batteries; with a volume expansion of 99% during complete cycling, Cu$_2$P anodes could be more durable than other conversion anodes in the Cu--P system with volume expansions greater than 150%.
The metal-organic framework (MOF) MFU-4l containing Co(II) centers and Cl- ligands has recently shown promising redox activity. Aiming for further improved MOF catalysts for oxidation processes employing molecular oxygen we present a density-function al theory (DFT) based computational screening approach to identify promising metal center and ligand combinations within the MFU-4l structural family. Using the O2 binding energy as a descriptor for the redox property, we show that relative energetic trends in this descriptor can reliably be obtained at the hybrid functional DFT level and using small cluster (scorpionate-type complex) models. Within this efficient computational protocol we screen a range of metal center / ligand combinations and identify several candidate systems that offer more exothermic O2 binding than the original Co/Cl-based MFU-4l framework.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا