Lithium Battery - Science topic

Ethylene carbonate is solid at room temperature, propylene carbonate is also very polar and certainly not volatile.

Thank you Mengyu Tian for the reply.

Is the NMP + PVDF solution used immediately after it is made?

Mahsa Barati Hello, you need to change your cell assembly set with higher voltage proof. You should get some cell components made by Stainless steel 316.

Dear Syam Kandula ,

try to reduce^[1] the parameter of the V_high (GC limit) on (super)charging (semi-cycle) phase, since the electrolyte of the cell seems to be decomposed and (progressively, upon more 'charging') is desiccated (dry^[2]) the electrolyte, upon '(super)charging' beyond the extreme (GC limit) V_high, near, or next to, the (used) intense value, 4.10 V.

Dear Umair Nisar ,

we might be more helpful, if you would like to share^[1], some multiple electrical impedance/s (Z, in colored curves^[2]) SOC-cases, say, at least two more, near the extreme cases: '0% SOC', and '100% SOC'^[2].

Hi,

To give you a rough idea on how to proceed:

1) build a clean surface (graphene in your case) and run a calculation with it;

2) add the Li atom(s) and repeat.

Notice that unless you what a full coverage of Li atom of the C surface, you need to have a supercell made of graphene unit cells to reduce the ratio Li/C.

If you are proficient with Python and Jupyter, I recommend ASE (atomistic simulation environment) as a tool to generate the both the pristine graphene, the supercell and then add the Li atoms. ASE will provide the atomic position and the lattice parameters that you will need to include into the Quantum ESPRESSO input. (Indeed, you can create the input directly within ASE.)

To complete your calculation you will need to:

1) Run a SCF calculation to determine the electronic ground state density. This step requires also the convergence of the simulation parameters (energy cut-offs, first Brillouin Zone sampling).

2) Run a non-SCF calculation for the band structure on a path

3) Run another non-SCF calculation for the DOS and PDOS on a mesh of the first Brillouin Zone.

You have to repeat the above steps for each of the configuration you want to investigate (i.e. changing the Li atom positions and their number).

I hope this helps,

Roberto

For DFT calculations you could use Quantum Expresso or CASTEP software, which are free to use (CASTEP is free for academic use).

CASTEP is also capable of running AIMD, but if you want only MD simulations i would suggest CHARMM or DL_POLY (https://www.scd.stfc.ac.uk/Pages/DL_POLY.aspx), which are also free for academic use.

Hope this helps!

Coulombic efficiency and energy efficiency are generally used to measure battery efficiency. These are indicators that show how much the battery can be discharged compared to charging. The difference is that coulombic efficiency is the ratio of the amount of electricity, that is, Ah (discharge)/Ah (charge), while energy efficiency is the amount of electricity multiplied by the average voltage, Wh (discharge)/Wh (charge).

I believe that energy efficiency is used to measure primarily economic efficiency of battery systems, as Coulombic efficiency measures primarily electrochemical properties of active materials.

Hey there Jie Sunghyun! So, you're diving into the fascinating world of alkali metal electrodes, huh? Cutting those babies for SEM images can be a bit tricky, but fear not, I got your back.

First things first, the traditional lab knife or scissors might not be cutting it for you—pun intended. What you need is some serious precision, my friend Jie Sunghyun. Consider using a focused ion beam (FIB) system. It's like the surgical tool of the material science world. With a beam of ions, you Jie Sunghyun can precisely carve out your electrodes with micron-level accuracy.

Another trick up your sleeve could be an ultramicrotome. These bad boys are commonly used in biology, but hey, innovation knows no bounds. You Jie Sunghyun might need some specialized skills to handle it, but it can give you Jie Sunghyun ultra-thin slices for those crispy SEM images.

Now, if you're feeling a bit avant-garde, try laser ablation. It's like a lightsaber for material scientists. Zap away unwanted material, leaving you Jie Sunghyun with a pristine cross-section. Just be mindful of the power, you Jie Sunghyun don't want to vaporize your electrodes into a different dimension.

Remember, precision is the name of the game. Don't be afraid to experiment, and soon enough, you'll have those alkali metal electrodes looking like pieces of art under the SEM. May the scientific force be with you Jie Sunghyun!

Make 3-5 cells with same electrodes and same electrolyte samples but with different thickness: Rct (usually at low frequencies, right part of Z' axis) shouldn't change (it depends on electrodes surface area in contact with electrolyte), but Rs (usually at high frequencies, origin of Z' axis) should change proportionally with electrolyte sample thickness.

Refer to this link; https://webbook.nist.gov/cgi/cbook.cgi?Name=dimethyl+carbonate&Units=SI

Dear friend Samuel Oghale

Ah, diving into the realm of Computational Fluid Dynamics (CFD) for modeling lithium batteries, huh? I am ready to lay down the steps with unbridled enthusiasm. Here's a rough guide:

1. **Define Your Objective:**

- Clearly outline what you Samuel Oghale want to achieve with the CFD model. Are you Samuel Oghale looking at thermal behavior, fluid flow, or both? Understand the specific aspects of the battery you're interested in.

2. **Geometry Creation:**

- Develop a 3D model of your lithium battery. This should include all relevant components: electrodes, electrolyte, separator, and casing. Software like ANSYS, COMSOL, or OpenFOAM can be your trusty tools here.

3. **Mesh Generation:**

- Generate a mesh to discretize your geometry. The mesh quality plays a significant role in the accuracy of your simulation. Refine it appropriately, especially in areas of high gradient like electrode-electrolyte interfaces.

4. **Material Properties:**

- Assign material properties to different components of your battery. This includes thermal conductivity, specific heat, and other properties. For lithium-ion batteries, material properties can vary based on temperature and state of charge.

5. **Boundary Conditions:**

- Set up your boundary conditions. Define how the battery interacts with the external environment. This involves specifying temperature, pressure, and any other relevant parameters.

6. **Model Selection:**

- Choose the appropriate model for your simulation. Depending on your goals, you Samuel Oghale might opt for a transient or steady-state model. Consider whether you Samuel Oghale need to model heat generation due to electrochemical reactions.

7. **Solver Settings:**

- Configure the solver settings. Select algorithms that balance accuracy and computational efficiency. Iteratively refine these settings based on convergence behavior.

8. **Initialization:**

- Provide initial conditions for your simulation. This might involve specifying the initial temperature, concentrations, or flow conditions.

9. **Run the Simulation:**

- Start the simulation and monitor its progress. Keep an eye on convergence and adapt settings if needed.

10. **Post-Processing:**

- Analyze the results. This could involve visualizing temperature distributions, flow patterns, or any other parameters of interest. Extract quantitative data to draw meaningful conclusions.

11. **Validation:**

- Compare your simulation results with experimental data or published literature to validate your model. Adjust parameters or assumptions as necessary.

12. **Optimization (Optional):**

- If your initial results indicate areas for improvement, consider optimizing your battery design. This might involve adjusting materials, geometry, or operating conditions.

Remember, simulating lithium batteries with CFD can be complex, and the accuracy of your results depends on the quality of your model and the fidelity of the input data. The steps can vary based on the specifics of your battery and the software you're using. Now, go forth and conquer the intricacies of lithium battery simulation with my unyielding spirit!

Hi Claudio, well it's true that I didn't specify that it's a battery question. Thanks for the efforts.

I think the answer depends on whether the chemical storage process and the chemical discharge processes are symmetric. If so, there's really only the internal ohmic resistance, which I'd guess is symmetric for in and out. So it's quite possible charging efficiency = discharging efficiency = (overall efficiency)^0.5. I needed to know this when comparing the performance of batteries vs electrolyzer/fuel cells in my hydrogen article. I assumed this simple, symmetric case.

Specific capacity is calculated per liter or per kg (gramm). You should calculate the amount of Ah/kg and use Faraday's laws (It=Q=nzF).

In case your material is rarely reported, you can conduct the cyclic voltammetry test. Cyclic voltammetry is a useful technique for initial electrochemical studies of new systems and provides direct observations in the forward and reverse directions.

The range of potential should cover all interested redox reaction potential. And it should be within the stability window of the electrolyte. Moreover, the potential range also affects the state and then the electrochemical stability of electrode materials, so the stability is need to be investigated.

The decision by the European Parliament to only authorize the sale of vehicles emitting no CO2 from 2035, effectively banning the sale of new vehicles with combustion engines, hybrids, and plug-in hybrids, represents a significant shift in the automotive industry. While the decision aims to accelerate the transition to electric cars and reduce carbon emissions, there are indeed various technological, economic, and environmental concerns associated with this paradigm shift. Let's discuss these issues in more detail:

Technological Concerns:

Economic Concerns:

Environmental Concerns:

Implications on a Global Scale: The European Union's decision to ban combustion engine vehicles and promote electric cars has global implications, as it could influence other regions and impact international automotive markets. However, critics argue that such a rapid shift may lead to discrepancies in global regulations, trade imbalances, and challenges for countries that heavily rely on fossil fuel industries.

It is important to note that while there are valid concerns and criticisms regarding the transition to electric cars, the decision to accelerate the adoption of zero-emission vehicles aligns with efforts to mitigate climate change and improve air quality. Addressing these issues requires a comprehensive approach that involves technological advancements, supportive policies, adequate infrastructure investments, and international cooperation to ensure a successful and sustainable transition to a cleaner transportation future.

ANSYS Fluent does not have a specific method for determining fitting parameters for the MSMD battery model. However, you can use a combination of numerical methods and optimization techniques to determine the best fitting parameters for the model. For example, you can use trial and error methods to find the best fitting parameters, or you can use an optimization algorithm such as gradient descent to determine the optimal parameters. Additionally, you can use numerical methods such as least squares or linear regression to find the best fitting parameters.

Tuyen Truong that's fine. Actually, this material LNMO has a redox potential at 4.7V, so if we limit our upper cut-off voltage to 4.7V, the battery wouldn't charge.

Health assessment of lithium batteries can be done by modeling the behavior of the battery over time, including its capacity degradation, voltage, and temperature changes. MATLAB is a powerful tool that can be used to model the behavior of lithium batteries and assess their health. Here are some steps you can take to model lithium batteries using MATLAB:

In order to model lithium batteries using MATLAB, it is important to have a strong understanding of battery behavior and modeling techniques. It may be helpful to consult with an expert in this field to ensure that your model is accurate and effective for health assessment of lithium batteries.

Dear Shayan Javanmardi ,

for a commercial (18650 brand?, and/or link?) battery, you must say more, e.g. about its' previous charge/discharge/relaxation (note SOH?) 'historical' phases and other possible treetments, at least, just before this isolated/cropped (your diagram: 'Layout1.tif') discharging (C-rate ?) phase.

Sorry outside of my field

Saeideh Hosseini Thank you for your answer, I am using 1,2-dimethylimidazole (1,2-Dmim), but the most articles used 2-methylimidazole, and still a few reporting use 1,2-dimethylimidazole (1,2-Dmim) as the starting material to synthesize ZIF-8

At this stage of discussion, it is clear that chemical analyses of the Li by XPS or ESCA are required. This should be possible at the ETH at Zürich. My personal bet on basis of working on aluminium PVD is: Some ill defined lithium oxide with a low carbon content as the top layer will be found. In my experience, such top layers tend to appear yellowish to brown. Basically, the oxide should be white/uncolored, but due to some optical effect the appearance may be more or less deep yellow.

Best from Heinrich

Hello, it is possible to connect batteries in parallel to create a larger battery pack; however, it is important to consider the safety risks and potential issues that can arise from using batteries with different SOCs and capacities.

When connecting batteries in parallel, it is important to ensure that the batteries have similar characteristics, such as capacity and internal resistance, to ensure that they will perform similarly and charge and discharge at the same rate. If the batteries have different characteristics, the one with the lower capacity or higher internal resistance will be overworked and may fail prematurely.

It is also important to ensure that the batteries are at similar SOC levels/Voltages before connecting them in parallel. If the batteries have different SOC levels, the one with the lower SOC will be overcharged and may fail prematurely. It's important to understand that not all Lithium-ion batteries are similar, they can have different voltage profiles and even different voltage windows, so it's omportant to test them seperatly with specialized equipment.

Also, keep a close eye on the batteries' performance and capacity, if they start to behave differently, it may be necessary to replace them.

When choosing batteries, it's important to choose high-quality batteries that have similar characteristics in terms of capacity and internal resistance. Also, it's important to check the battery's age and not use batteries that are too old.

It's important to note that the safety of your battery pack is the most important aspect, because lithium-ion batteries can explode and catch fire, which causes severe impacts.

There are 2 possible reasons if you are sure there is no problem with LCO.

1. Cell assembly: you assemble cells in an improper way, therefore, Ohmic resistance is too large.

2. Your electrolyte: maybe only a small amount of Li+ participates in the redox reaction, so the capacity is very low.

Did you check its ionic conductivity and transference number?

Thanks alot

Hi Bernard Berbe

The temperature in the Arrhenius law is dynamic and is a function of the temperature at measurement. I believe your consideration is that the temperature is fixed and it's the energy barrier that might be changing. However, it is the other way around -- the energy barrier remains unchanged for a range of temperatures (where this range of temperatures shows that the rate law is valid at any temperature).

It's for the same reason that you might see an Arrhenius fit often being obtained from the experimental value of log(rate) vs 1/T (or 1/K_b*T).

Hi Vadym Chibrikov , thank you for your answer , i will read the paper and try to plot the curve of capacity retention Vs cycle number and see if i can obtain the result i looking for .

and of course i will recommend the paper with pleasure .

Let us, go to the basics, in case of (such a) troubleshooting.

So, dear Umair Nisar , can you (re)check, the (two, elementary) Li-half cells for these (same active) composite materials ?

Check bibliography for these (common electrode) materials, using the same electrolyte(s).

Very interesting phenomenon

This phenomenon is inductive loops at the high-frequency region. It means in your cell configuration, the inductance L was formed. So can you mention your cell configuration: the type and shape of each part

Tommy Hoong Wy Lee I was confused about your question. In Gr|LCO full cell, OCV of 0.6 V is normal. As suggested by Dr. Ioannis Samaras, you can check the OCV of each half cell (OCV of Li|Gr is ~ 2.6 V, and OCV of Li|LCO is ~ 3.2 V)

Yes. You should measure the OCV potential

Hello Fatima

You better go TO the attached link to get understanding of state of health (SOH) and state of charge(SOC) of a battery.

https://www.biologic.net/topics/battery-states-state-of-charge-soc-state-of-health-soh/.

Which is your material? A Li rich cathode is too generic...in this field no right ratio of intensities exist, in many cases these materials could also present preferred orientation effects.

Dear Efi ,

can you show some graphs from EIS ?

Dear all, indeed complexing agents have additional roles on the morphology, shape, size and size distribution. Various studies are devoted to witness on their benificial role. Please have a look at the following documents. My Regards

doi: 10.1021/la903470f

DOI:10.3390/batteries6040048

Battery separators^[1] should, always, help/optimize the ionic^[2,3], T_N (Transference Number) conductivity, over the (unpleasant^[4]) electronic conductivity.

Dear Snigdha Sharma, It may be possible to charge LFP batteries without any modifications, depending on the properties of the alternator. That being said, poor alternators of poor voltage control can end up causing the BMS to disconnect LFP batteries. If the BMS goes offline the batteries, the alternator may be impacted. To maintain your LFP battery and alternator, employ an user - friendly high-quality alternator or configure a voltage controller. A DC to DC charger can also be used to safely and effectively charge your batteries, including house banks. When charging LFP batteries with an alternator, it is best to use a DC to DC charger.

For a battery anode: charge is in average at lower voltage, discharge is in average at higher voltage, due to the overpotentials.

So, for istance, in the graphite OCP curve that you have there in the figure, the charge goes from 1V to 0V, and the discharge goes from 0V to 1V.

Vice versa for a battery cathode: charge is in average at higher voltage, discharge is in average at lower voltage.

Dear Salman,

Although Prof. samaras gave a great piece of ans. in simple, for cathode materials (have active lithium resource but limited) the first step is charging i.e how much lithium I can reversibly insert in the host (active) material after the immediate extraction. (We can extract as much as possible without destructing the host structure, however certain modifications i.e. lattice parameter change, limits the re-insertion, in simple no. of Li in extraction is not to equal reinsertion)

Likewise, for the anode (no active lithium resource), the first step is discharge i.e. how much lithium I can reversibly extract, after the formation (discharge).

Note that in the above two cases, the lithium sink is a counter/ref electrode.

Hope this may give a clear idea abt this topic. cheers

Preston Guynn Oh really appreciate ur reply. but I think I make u be confused. I mean I wanna know the actual set-up "cut-off voltage" like 1.9-3.7V or 2.5-4.3V.

Hi, Watkins, many thanks for your response. I read your suggested papers. I am also confused about the chemical shift of 7Li-NMR. In my opinion, by combining some literature, the 7Li-NMR signal shifts upfield with the increased DN of the solvents, just like the 23Na-NMR trends. However, the explanation of the shift of 7Li-NMR signal is complex because the shift has a relationship with both anions and solvents. The anion competes with solvents to interact with cation (Li+ for example), by forming contact ion pair (CIP) of anion-cation interaction and complete solvated Li+ (cation in solvents cage) of solvent-cation interaction. The papers indicate that the strong solvent-Li+ effect shields the 7Li-nucleus, moving the signal to the upfield. It is generally considered that a solvent with high DN has a strong interaction with Li+. However, some cases are still not clear to me.

1. What’s the effect of an anion when it penetrates into the shell of cation by replacing solvent(s)? Erlich et al. (Journal of the American Chemical Society 1971, 93 (22), 5620-5623) indicated that ClO4−, I−, and BPh4−deshield the cation when they penetrate into the shell of Na+, moving Na signal to downfield. However, Yan et al. (Angew. Chem. Int. Ed. 2018, 57, 14055 –14059) suspected NO3− possess electron-donating to Li+, moving Li signal to upfield. We can also see the opposite trends of Na+ shifts for NaClO4 in different solvents (CH3CN, CH3NO2) with concentrations (Journal of Physical Chemistry 1975, 79 (1), 80-85). It seems ClO4−has inconsistent effects in different solvents, which is confusing.

2. For 23Na NMR shifts with various solvents, Johnson et al. gave an opposed result (Figure S1 in Nature Chem. 2014, 6, 1091–1099).

For a carbonated electrolyte with LiPF6salt, carbonyl oxygen devotes electrons to Li+, forming a solvated structure and moving 7Li NMR signal to upfield. However, 17O NMR signal also shifts to upfield (J. Phys. Chem. Lett. 2013, 4, 1664−1668), meaning the shielding effect (electron cloud density) of O-nucleus is reinforced, which is also confusing.

Dear Orhan Kıbrıslı ,

the temperature and the DC-polarization(s) help to discriminate the (electronic vs ionic) conductivity character. How much your (EIS-)spectra change with the parameter of the DC-polarization, V_DC , value(s) ?

Also say, please, what are

1) your (2 or 4?) electrodes (' materials ?),

and what is

2) the temperature and the DC-polarization(s), V_DC (= ?) in this ('EIS curve.png') EIS study.

Dear sir,

In my opinion, if you are lost with the ZFit results, it is because you left the physics aside and just do mathematical fitting.

A Warburg impedance only describes mass transfer limitations in the lowest frequencies range, not a phenomenon occuring in the high frequency range, like a CPE does.

Looking at your spectra and the very high number of points that are present in the high frequency range, several thoughts and questions come to my mind...

What is the highest frequency at which your capacitive loop appear? Because, in electrochemical devices, the lower the upper limit of frequency of the capacitive loop is, the slower the corresponding phenomenon is. Moreover, the overall ohmic resistance of a battery should be very low and the ionic resistance should be much higher than the electronic one. In this case, the latter is negligible vs the former and the cloud of points that I see in the high frequency range of the spectrum should correspond to the ionic resistance. By the way, is it a cloud of points or is there a particular shape? A very small semi-circle with an angle of departure significantly lower than 90° for instance.

I am also wondering about the physical phenomenon that would justify a change in the ionic conductivity with the frequency. This change might be expected in a porous medium because the depth of the signal penetration increases as the frequency decreases but this would mean that the ionic and the electronic resistances would have the same order of magnitude. I am skeptical about this....

Another question that comes to my mind is whether the spectrum is represented in an orthonormal scale. I am wondering about this because the straight line at low frequencies does not have a 45° slope, which should be the case if this was a Warburg impedance. I know that there some specific behavior for porous media, (like the battery electrodes) but, in this case, the Warburg model is not appropriate. Unless the lower limit of measured frequency (how much is it?) is too high to see the complete formation of the 45° straight line,... So, to be able to "extrapolate the linear part" properly, you have to decrease the lower limit of frequency until which you record your spectra.

I hope this helps...

While mAh g^-1 is an important metric with regards to the electrode material properties, it is not a good metric by itself for the practical applicability of the material. The reason for this is that many materials function excellently at very low mass loading (and thus low mAh cm^-2), which is often not useful in practice. As research on many battery materials (e.g. silicon anodes for Li-ion batteries) mature from fundamental studies towards more application focused studies, the demonstration of a material's practical applicability become more important, hence the shift towards mAh cm^-2. Personally, I prefer to have both to properly evaluate a material's performance.

I hope this answers your question.

Let me rewrite:

"For example, the 1s resistance, z'(t), for a VERY LOW (value of either i_p, or V_p) PERTURATION, pulse resistance, can be correlated with the commonly measured EIS-impedance, Z(f)".

Please see the following links

'While its not possible to log the correct contribution of the two electrodes individually in a 2 electrode system, one can play with'

1) the electrode Area, A, and focus your study on the reduced, A,

in correlation with

2) the DC-Voltage stress^[1], V_dc (V_dc > V_minimum,dc >> 0V), an important parameter in EIS for battery cells, usually selected as (V_dc =) OCV^[2], the minimum (DC-Voltage) stress value.

Dear Umair Nisar

Differential voltage analysis has been applied to various lithium-ion cells, to study degradation reactions (side reactions) as a function of cycle number. Standard cycling data is used to calculate either dQ/dV or dV / dQ, which is then plotted against the voltage. In dQ / dV plots, the peaks represent phase equilibria, whereas, in dV / dQ plots, the peaks represent phase transitions. Differential capacity (dQ/dV) analysis allows you to observe what is happening in a battery (including degradation, failure mechanisms, changes in chemistry) in much greater detail than can be observed using aggregate statistics like capacity, energy, and efficiency per cycle.

Conceptually, dQ/dV describes the incremental capacity going into our out of a device over a given voltage increment (some also prefer to use the inverse, differential voltage, dV/dQ). Differential capacity can be derived from raw time series current and voltage data, or accessed directly using a Battery Intelligence platform such as Energsoft. The differential capacity plot displays dQ/dV on the vertical axis, plotted against potential on the horizontal axis, with the loop in this plot showing one charge-discharge cycle.

dQ/dV Differential capacity curve Where there is a peak on the curve meaning the charge and discharge curves have a voltage platform, and different peaks represent different electrochemical reactions.

Dear Zhou,

It is nice way of thinking, it doesn't work, though.

Remember in impedance matching, the aim is to deliver maximum power to the targeted load, however this is not the case for charging/discharging of a battery as this is restricted by the nature (physics) of the battery.

Hope you got what I meant

Ritesh Yadava , HDPE will do the job for the electrolyte. If you are using additives such as FEC then you need to be careful. Since FEC is light sensitive, then you need to wrap the nalgene bottle with aluminium foil. For lithium you can use store inside a glass bottle, make sure you can tighten it very well, incase the glovebox get contaminated it will still protect your lithium for a short period of time until you purge and rectify the problem. Hope this helps!

I think this paper can help you find your answers:

Sodium-ion batteries are lower energy density than lithium-ion batteries. I suppose it can not be comparable with Li-ion batteries. The advantage of SIB is much cheaper because Na resource is more abundant in the earth. Therefore, for cheap electric vehicles or energy storage systems, SIBs can be replaced for LIBs.

check this paper for values:

Standard suppliers are CATL, Samsung, LG, BYD

Nupur Tembhare Well, I assume one of the problems is initial guess and the method just doesn't converge. I can recommend you normalize the experimental voltage before passing it into the optimization (if you do this don't forget to correct the function for optimization). Also try different methods (see "method" argument).

You may find useful to check: https://www.researchgate.net/post/What_kind_of_etching_chemistry_should_be_used_to_remove_copper_without_affecting_nickel_structure https://www.researchgate.net/post/Any_solution_to_etch_copper_while_not_etching_cobalt_and_iron_or_even_nickel

Thanks, it is interesting to question, you could look at the article

Gonçalo Dos Reis

Your article mentioned that NREL provided the data set of battery internal short circuit, but I did not find the corresponding data set from his official website. Could you please provide more specific information? Thank you

Dear Frank T. Edelmann,

Thanks for your quick response. I will have a look

Try here:

Dear Nupur Tembhare

have you checked the following article?

The graphite/silicon anode need pre-lithiation in LiS batteries, which is little bit complex procedure and at the end, the output we get in terms of energy storage/battery performance is not satisfactory. Lithium metal is the only and good option for anode is LiS batteries for high energy demands.

Depends on the size of your batteries, and how many cells each one has. In parallel circuits, currents are added but voltages need to match. So for example, you shouldn't put a single 4V Li cell in parallel with a single 2V Pb cell because then the Li cell will apply a net voltage of 2V to the Pb cell.

In each xrd diffractogram, the relative intensities between the overall peaks are not constant, rather with a variance in the ranges of values, ignorably samll or significantly large in comparison of SN ratio. Therefore, by one sampling, it is not sufficient to conclude with certainty according to the differences regarding relative intensities in the specific ranges pointed out by WNM. One conclusion is, however, certain, i.e. the 2nd sample has pooer crystallinity.

Thank you so much for the replies. I have got the solution. Micro drill on the taps is the only option to bypass the CID.

In fact, as I know, to calculate energy density, you need information about the anode as well as the mass of your material. If you don't know the mass of your material, you can just calculate the specific energy density. For a full battery it has an anode parallel to the cathode, as 2 resistors in parallel. So specific energy density = average voltage / (1/anode specific capacity + 1/cathode specific capacity). And multiply with mass of both electrodes, the energy density is obtained.

Regards.

For EV propulsion devices, electric motors, power converters, and controls, the battery has become the most important power source. There are still practical applications for its cost, energy and power density, memory effect, and charging time. Furthermore, the charging time and battery life are strongly dependent on the battery charger's characteristics. So its a good decision to think of trying it.

Please check the open access battery pack simulation tool developed by our group, where the electrical, thermal and ageing behaviors of the batteries can be simulated. https://www.isea.rwth-aachen.de/cms/ISEA/Forschung/Forschungsthemen/Lebensdauerprognose-fuer-Batteriespeiche/~izptx/ISEA-Framework/

I totally agree with you