network of research pilot lines for lithium battery …

Electrode and Cell Production | Robin Moschner (TUBS) | 09.11.2021 | Slide 1

NETWORK OF RESEARCH PILOT LINES FOR LITHIUM BATTERY CELLS

This Project has received funding

from the European Union’s

Horizon 2020 Research and

Innovation Programme under

Grant Agreement N. 875479

Robin Moschner (iPAT) | 09.11.2021

Li-Planet Training –Electrode and Cell Production


Lithium-Ion Battery (LIB) Cells consist of:

anode and cathode containing the lithium/energy storing materials (active materials)

Separator to prevent electric short circuit

Electrolyte providing ionic conductivity

Cell voltage and capacity is defined by active material (AM) and the respective specific electrode combinations

high AM amount is favourable to increase specific and volumetric energy

The Lithium-Ion Battery Cell

Discharge

An

od

eC

ath

od

e

e

e


To allow energy storage, electrons and lithium ions have to be moved to same active material sides

LIB electrodes are intercalation electrodes with a sponge like structure to allow

electron diffusion through solid structure

Lithium ion diffusion through electrolyte filled pore network

Binders provide structural integrity and substrate attachment

Conductive agents (CA) provide/improve electrical connection of AM

The Lithium-Ion Cell

Active

material

Binder Conductive

agent

Li+

e-


Dry pre-processing

Wet processing DryingCoating Calendering

Sealing Pre-formation

Module assemblyFurther Electrolyte

additionFormation /

cell test

Cutting

Stacking PackagingTab wieldingElectrolyte

addition

System integration

Final sealing / degassing

Battery-management

Electrode production

Cell assembly

Cell formation / testing

Module / system

design

Overview production process


Question

How efficient must each process step be

at least?

Process chain requirements


Efficience of eachstep: 97 %

Efficiency of process

chain: 57.8 %

Number of process

steps: 18

(0.97)18 = 0.578

Material pre-processing

System integration

Efficiency of process

chain: 83.4 %

Number of process

steps: 18

(0.99)18 = 0.834

Material pre-processing

System integration

Efficiency of each

step: 99 %

Process chain requirements


Process-Structure-Property

mechanical, structural and

electrical properties/analysis

electrochemical performance

(electron and ion transport)

Process

Mixing/Structuring

Structure Property

Process-Property

RelationProcess-Structure

Relation

Structure-Property Relation

Coating/Drying Calendering no essential

understanding

0,0

0,5

1,0

1,5

2,0

2,5

3,0

dis

ch

arg

e c

ap

ac

ity [

mA

h/c

m²]

dry mixing wet mixing

equipment equipment

PM PM

EIR EIR

RDM DIS

NOB DIS

(all electrodes 0% calendered)

0,01 0,1 1 10

0,00

0,05

0,10

0,15

0,20

0,25

* total mass (coating + current collector)

-dV

/d(l

og

d)

[cc

/g*]

pore diameter [µm]

dry mixing wet mixing

equipment equipment

PM PM

EIR EIR

RDM DIS

NOB DIS

Process-

Structure-

Property

Relation


0 20 40 60 80 100 120 140 160 180 200

1

10

100

1000

10000

100000

Sp

ecific

po

we

r [W

/kg

]

Specific energy [Wh/kg]

C/100

C/10

C

10C

100C

1000C

Supcercaps

Lead

Ni-Cd Ni-MH

High Power

Li-Ion

Medium Range

Li-Ion

High Energy

Li-Ion

Multiple parameters define performance of cells:

LIB R&D is a complex field

Further influences in module design and integration

Process-Structure-Property

[1] based on: Saft S.A. and Kurzweil, Peter; Dietlmeier, Otto K. (2015): Elektrochemische Speicher. Superkondensatoren, Batterien, Elektrolyse-Wasserstoff, rechtliche Grundlagen. Wiesbaden:

Springer Vieweg. http://dx.doi.org/10.1007/978-3-658-10900-4.

Cell

properties

Active

material

content

Additive

content/

type

Material

density

Material

structureVoltage

range

Processing

intensity

Coating thickness

Material

distribution

Component

interaction

Storage timeOrder of

process steps

Electrode

balancing

Electrolyte

type/amount

Electrode

contacting

Cell formation

Separator

type

[1]

0 20 40 60 80

3,0

3,5

4,0

4,5

charge

discharge

Vo

lta

ge

[V

]

Capacity [mAh]

lower cutoff voltage

upper cutoff voltage


Dry pre-processing

Wet processing DryingCoating Calendering

Sealing Pre-formation

Module assemblyFurther Electrolyte

additionFormation /

cell test

Cutting

Stacking PackagingTab wieldingElectrolyte

addition

System integration

Final sealing / degassing

Battery-management

Electrode production

Cell assembly

Cell formation / testing

Module / system

design

Overview production process


Important Influences:

Stress intensity

Stress number

Device type and geometry

Components involved

Influence on particle structure and particle interaction:

Pre-processing allows for specific structuring of components

Intense Pre-Processing can lead to mechanofusion

Intense Pre-processing can lead to AM particle breakage

can simplify dispersion or create structures not possible during dispersion

[1] Schilde, Carsten; Kampen, Ingo; Kwade, Arno (2010): Dispersion kinetics of nano-sized particles for different dispersing machines. In: Chemical Engineering Science 65 (11), S. 3518–3527.

DOI: 10.1016/j.ces.2010.02.043.

[1]

Dry Pre-processing – influences

[1]


Eirich-Mixer

Intense mixing

Desagglomeration

Improves homogeneity at

beginning of dispersion

Ring-shear Mixer

High-Intensity mixing

Desagglomeration and

Mechanofusion

potential particle damage

Rotary-Drum Mixer

Macroscopic mixture

No mechanical stress

Improves homogeneity at

beginning of dispersion

Dry Pre-processing – machines


Pyknometry

Supportive information

about particle structure

BET

Information

about

particle

structure

Can show

particle

breakage/

delamination

SEM

Qualitative

Image of

particle

structure

[1]

[1] Bockholt, Henrike (2016): Formulierungstechniken für eigenschaftsoptimierte Lithiumionenbatterieelektroden. Dissertation. Technische Universität Braunschweig, Braunschweig. iPat.

Particle size

measurement

Information about

particle structure/

interaction

Can show mechano-

fusion or breakage

0,1 1 10

0,0

0,5

1,0

1,5

2,0

part

icle

siz

e d

istr

ibu

tio

n q

3* [

-]

particle size x [µm]

rotor tip speed:

pristine

070

100

130

160

TGA

Data can give information

about particle interaction

[1]

Dry Pre-processing – analysis

low medium high1,5

2,0

2,5

3,0

3,5

4,0

BE

T s

urf

ac

e [

m²/

g]

Dispersion intensity [-]Mixing intensity [-]


Bockholt, Henrike (2016): Formulierungstechniken für eigenschaftsoptimierte Lithiumionenbatterieelektroden. Dissertation. Technische Universität Braunschweig, Braunschweig. iPat.

Component

interaction

Component

distribution

Viscoelastic

behaviour

Sedimentation

stability

Formation of

CA-binder

network

Coating

behaviour

Process

Parameters

Component

structure

Wet Processing – influences


Mixing intensity

Mixing time

Order of component addition

Device type and geometry

Temperature

Solid content

major influence on electrode structure and properties

Component structure/interaction is defined during wet mixing step

Processability during coating is defined by viscoelastic slurry behaviour


Dissolver

Small to medium

Batch production

Low to medium

viscosity

Low to medium

energy input

Eirich-Mixer

Small to large

Batch production

Low to high

viscosity

Low to very high

energy input

Wet Processing – machines

Extruder

Small to large

Continuous slurry production

Medium to very high viscosity

Low to very high energy input

Mixing

Zone

Output

Zone

Entry

Zone

Planetary-Mixer

Medium to large

Batch production

Low to high

viscosity

Low to high

energy input


Rheology

Information about

component interaction

Viscoelastic behaviour

defines sedimentation

and coating behaviour

Shear rate and complex

behaviour give detailed

information

Solid content

Measurement for quality- and process-control

Change in solid content changes viscoelastic behaviour

Particle size measurement

Information about particle

structure/ interaction

Quantitative information

about process changes/

dispersion progress

0,1 1 100,0

0,5

1,0

1,5

2,0

pa

rtic

le s

ize

dis

trib

utio

n q

3*

[-]

particle size x [µm]

particle sizes

during dispersion:

Time 1

Time 2

Time 3

Cryo-SEM

Information about binder-

particle interaction

Wet Processing – analysis



Coating speed

Device type

Interaction/contact/wetting of slurry and substrate

Influence on electrode properties:

Coating mainly defines areal loading distribution

Quality of coating device and slurry wetting defines electrode quality

Substrate surface/composition has to be fitting to applied coating

Mistakes during slurry production or coating (enclosed air, large agglomerates, insufficient wetting) can lead to coating defects

Coating – influences


Pre-metered

Areal loading and quality is defined by:

Volume flow

Position of slot-die

Viscosity of slurry

Pressure loss in slot-die

+ Closed system

+ High longitudinal coating quality

± For high transversal coating quality slot-die needs to be optimized for slurry viscosity

− Complex system

Self-metered

Areal loading and quality is defined by:

Gap height between coating knife and substrate

Viscosity of slurry

Wetting behaviour

+ Easy cleaning and handling

+ Flexible (usable with many different slurry types)

− Lower coating quality

− Open system contamination possible

Coating – machines


Gloss

Gloss is influenced by

component

distribution and

coating surface

Change in gloss can

indicate demixing or

inhomogeneity

Automated defect detection

In-line quality control

Allows automated wastage disposal or marking

Can give information on coating problems

In-line NIR

Detection of wave length characteristic can be used

to detect water content in coating during process

In-line residual moisture detection 1000 1500 2000 25000,21

0,22

0,23

0,24

0,25

0,26

Ad

so

rpti

on

[-]

wave length [nm]

Coating – analysis

Raman

Detection of different

chemical bonds

Component mapping

Topology/coating thickness

Information about coating

homogeneity before drying

Possibility of fast coating control



Drag by evaporating solvent ↔ Diffusion

More intense drying parameters lead to more intense gradients:

More binder and conductive agent at surface

Less additives at current collector

[1] Westphal, B.; Bockholt, H.; Gunther, T.; Haselrieder, W.; Kwade, A. (2015): Influence of Convective Drying Parameters on Electrode Performance and Physical Electrode Properties. In: ECS

Transactions 64 (22), S. 57–68. DOI: 10.1149/06422.0057ecst.

Drag Diffusion

Increases gradient

Lighter components

(binder, CA) follow

evaporating solvent

Increases with higher

temperature/airstream

Decreases gradient

Increases with higher

temperature

Slow

[1]

Drying – influences

[1]


ConvectionConduction Radiation

Drying – machines

New drying

methods

Laser

drying

Inductive

Drying


Simple

No easy scale-up

No vapour transport

Conduction

Easy scale-up

Easy vapour transport

Simultaneous double

sided coating possible

Energy-inefficient

Convection

Easy scale-up

No vapour

transport

Energy-efficient

Fast

Radiation

Drying – machines

New drying

methods

Laser

drying

Inductive

Drying

Electrode and Cell Production | Robin Moschner (TUBS) | 09.11.2021 | Slide 22[1] Westphal, B.; Bockholt, H.; Gunther, T.; Haselrieder, W.; Kwade, A. (2015): Influence of Convective Drying Parameters on Electrode Performance and Physical Electrode Properties. In: ECS Transactions 64 (22), S. 57– 68. DOI:

10.1149/06422.0057ecst.

[2] Haselrieder, W.; Ivanov, S.; Tran, H. Y.; Theil, S.; Froböse, L.; Westphal, B. et al. (2014): Influence of formulation method and related processes on structural, electrical and electrochemical properties of LMS/NCA-blend

electrodes. In: Progress in Solid State Chemistry 42 (4), S. 157–174. DOI: 10.1016/j.progsolidstchem.2014.04.009.

SEM/EDX

Information on structure and

component distribution

Areal loading distribution

Measurement of areal

loading shows

homogeneity of electrodes

Good homogeneity

improves cell performance

Adhesion

Relevant for further

processability

Electric conductivity

Influences cell

performance

Pore-size distribution

Pore-size distribution

influences ionic conductivity

Measurement allows

process-structure relations[2]

Temperature profile

Electrode temperature during

drying shows end of drying

[1]

Drying – analysis



Temperature

Increased temperature leads to more elastic electrode behaviour

Increased temperatures decrease line loads

Line load

Increased compaction leads to higher energy density

Very high line loads can lead to particle breakage and even electrode damage

major influence on electrode structure and properties

Electrode porosity ↓

[1] Meyer, Chris; Bockholt, Henrike; Haselrieder, Wolfgang; Kwade, Arno (2017): Characterization of the calendering process for compaction of electrodes for lithium-ion batteries. In: Journal of

Materials Processing Technology 249, S. 172–178. DOI: 10.1016/j.jmatprotec.2017.05.031.

[2] Dr. Wolfgang Haselrieder (2014): Calendering: Coupling structural, electrical and mechanical electrode properties with performance. Kraftwerk Batterie. Münster, 25.03.2014.

Electric conductivity ↑

Ionic conductivity ↓

[1]

Calendering – influences


Calender

Continuous compression (lab to industry

scale)

Hot and cold compression

Line compression (line load/ gap

controlled)

Press

Sheet compression (Lab scale)

Hot and cold compression

Areal compression (pressure controlled)

Calendering – machines

[1] Patil, Hardik R. (2020): Entwicklung und Validierung eines neuartigen Trockenbeschichtungs-Prozess zur Herstellung von Next-Generation Batterieelektroden. Master Thesis. Technische

Universität Braunschweig, Braunschweig. iPat.

[1]


Electric conductivity

Calendering can improve

electrode conductivity by

increasing particle contacts

Electric conductivity one

factor defining cell

performance

[1] Haselrieder, Wolfgang (2016): Kalandrierung zur gezielten Einstellung der Batterieelektroden-Performance. Dissertation. Technische Universität Braunschweig, Braunschweig. iPat.

[2] Westphal, Bastian Georg; Mainusch, Nils; Meyer, Chris; Haselrieder, Wolfgang; Indrikova, Maira; Titscher, Paul et al. (2017): Influence of high intensive dry mixing and calendering on relative

electrode resistivity determined via an advanced two point approach. In: Journal of Energy Storage 11, S. 76–85. DOI: 10.1016/j.est.2017.02.001.

line loads and

electrode thickness

Data on plastic and

elastic deformation

behaviour

Data on

deformability of

electrodes

Adhesion

Adhesion relevant

for processability

of electrodes

Long term cycling

stability influenced

by adhesion

Binder demixing

can be seen in

electrode adhesion

Pore-size

measurement

SEM

Information on

structural and

surface changes

[2]

Lineload q [N/mm]

Ad

hesio

n σ

[MP

a]

[1]

Cathode AM

EDX

Calendering – analysis


Mechanical Cutting

Cheaper to purchase

Metal abrasion possible

Mechanical cutting can lead to coating

breakage at the edges

Laser Cutting

Less abrasion and contamination

Longer lifespan

More flexible

Introduced heat can damage coating

More complex

Cutting


The LiPLANET consortium at a glance

www.liplanet.eu

This Project has received funding from the European

Union’s Horizon 2020 Research and Innovation

Programme under Grant Agreement N. 875479

Acknowledgement

@[email protected]

M. Sc. Robin Moschner

TU Braunschweig

Research Associate

Battery Process Engineering

[email protected]

network of research pilot lines for lithium battery …

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