440:221 Intro to Engineering Mechanics: Statics

ENGINEERING RESEARCH CENTER FOR

STRUCTURED ORGANIC PARTICULATE SYSTEMS

RUTGERS UNIVERSITY PURDUE UNIVERSITY NEW JERSEY INSTITUTE OF TECHNOLOGY UNIVERSITY OF PUERTO RICO AT MAYAGEZ

ENGINEERING RESEARCH CENTER FOR STRUCTURED ORGANIC PARTICULATE SYSTEMS

RUTGERS UNIVERSITY PURDUE UNIVERSITY

NEW JERSEY INSTITUTE OF TECHNOLOGY UNIVERSITY OF PUERTO RICO AT MAYAGEZ

AAPSMSE 2nd FDA/PQRI Conference on Advancing Product Quality

The Science of Tech Transfer/Scale-up

October 5-7, 2015 Bethesda North Marriott Hotel & Conference Center

5701 Marinelli Road North Bethesda, Maryland 20852 USA

Using material science methodology and modeling predictive tools for enabling scale-up Alberto Cuitino Mechanical & Aerospace Engineering Rutgers University




Strategy of material science approach to scale-up

Identification of intensive or material properties

(MECHANICAL PROPERTIES)

Identification of relevant processing variables

Utilization of modeling &

computational science

Predictive Modeling




Predictive modeling

Mechanical models and numerical methods that provide new insight into the behavior of materials and structures, and that enable design and optimization (D&O) of manufacturing processes (MP) and of product performance (PP).

Effective, efficient and convergent numerical

methods

Predictive and mechanistic

constitutive models

Well-defined procedures for verification, calibration

and validation

MP PP D&O

Process Structure

Property Performance

Strategy of material science approach to scale-up




Case Study: Integrated Modeling of Bilayers

Mechanical Properties (elastic, plastic )

Physical Properties (PSD )

Tooling (geometry, surface treatment )

Formulation & Equipment for Bilayers

First Layer Die Filling First Layer

Loading/Unloading Second Layer Die

Filling Second Layer

Loading/Unloading Bilayer Ejection

Making Bilayers

Density profiles Defects Hardness

Testing Bilayers




A Key Challenge: Predicting compact strength based on inter-particle bonding

Starch Layer

MCC Layer

Interfacial crack

X-ray Micro-Tomography

Hardness Test

Remarks: + The contact law is a function of material properties of the individual particles (not of the powder bed)

Akseli et al. Powder Technology, 2013




Granular systems at high levels of confinement - Predictive constitutive models of inter-particle interactions for a variety of physical mechanisms

+ Predictability at high levels of confinement remains an open problem - Concurrent and efficient multi-scale strategies which are fully-descriptive at the granular scale.

+ Based on a particle mechanics description

Dominant mechanisms:

- Elastic deformations - Plastic deformations - Bonding - Strain-rate mechanisms - Friction with die walls - Fracture

Predictive multi-scale modeling




~300% ~100

Hertz theory Hertz

theory

Question: Is our contact mechanics theory predictive for compaction? Restrict attention to: - Elastic spheres - Absence of gravitational forces, adhesion and friction

Tatara (1991): experimental data, rubber sphere of radius 10 mm, no hysteresis, no permanent deformations, E = 1.85 MPa, = 0.46

A Fundamental Question




8 Finite-element model.

Elements: ~1.00.000 Nodes: ~1.500.000 CPU-time: few days

Nonlocal formulation.

Memory requirements: none CPU-time: few seconds

Applied load

Hertz theory

Difference depends only on Poissons ratio

Hertz theory

Tatara-1989

SC granular crystal

Experimental setup

Discrepancy in the applied load

Theory Validation and Predictions




Similar materials - Different powder bed topologies Elasto-plastic deformations and bonding mechanisms

plastic loading

elastic (un)loading

Plastic and Bonding




Granular systems at high levels of confinement - Predictive constitutive models of inter-particle interactions for a variety of physical mechanisms

+ Predictability at high levels of confinement remains an open problem - Concurrent and efficient multi-scale strategies which are fully-descriptive at the granular scale.

+ Based on a particle mechanics description

Dominant mechanisms:

- Elastic deformations - Plastic deformations - Bonding - Strain-rate mechanisms - Friction with die walls - Fracture






Remark: Product

function and performance

(e.g., bonding strength) are

determined by granular

structure evolution.




Integrated Modeling of Bilayers

Mechanical Properties (elastic, plastic )

Physical Properties (PSD )

Tooling (geometry, surface treatment )

Formulation & Equipment for Bilayers

First Layer Die Filling First Layer

Loading/Unloading Second Layer Die

Filling Second Layer

Loading/Unloading Bilayer Ejection

Making Bilayers

Density profiles Defects Hardness

Testing Bilayers




Experiment

(Red line)

Simulation (bars)

Simulated PSD matches

experimentally measured PSD

Measured particle size distribution

Particle size greater than 100 m are represented

Integrated Modeling of Bilayers: Case Study Materials




Integrated Modeling of Bilayers: Case Study Die Filling Deposition of particles filling powder in die

g




Integrated Modeling of Bilayers: Case Study First Layer

die wall Before ejection

Tablet after unloading compression force The whole tablet is in the die

After ejection The tablet is completely out of die Diametral Expansion

Simulation: 0.8% Experiments ~ 0.6%

The tablet expands during and after ejection




Integrated Modeling of Bilayers: Case Study Filling and Loading Second Layer

First layer: compacted & compaction

load removed (after unloading stage)

Second layer deposition

Apply main compaction force




Integrated Modeling of Bilayers: Case Study Validation

22

- There is no need for recalibration of material parameters for simulation of bilayer tablets We use parameters from the monolayer tablets




Mechanistic Understanding via Simulations

Simulations provide: Understanding about mechanisms Quantification of competing effects Microstructural information Network of force distribution Residual stresses Defects Bonding

Characterization of the Bilayer Tablet Properties attendant to process parameters and material properties

23




Tensile strength tester

Experimental characterization




Tensile strength (Avicel + Avicel)

0

2

4

6

8

10

12

0 2 4 6 8 10 12 14 16 18 20

Tens

ile St

reng

th (M

Pa)

Initial Compaction Force (kN)

Ffinal = 18kN

Ffinal = 14kN

Ffinal = 10kN

Ffinal = 6kN

Tablets failed at the initial layer

Tensile strength values of MCC mono-layer tablets

Predicted Tensile Strength of the Interface

4/18 kN

2/18 kN

6/18 kN

8/18 kN


Ilayer failure




Physical mechanisms

Interface

Strong bonding: Capacity for further elastic and plastic deformation. Asperities are in the order of the particle size.

Weak bonding: Capacity for further deformation is reduced. Compact becomes more rigid.

100m

Fist layer: 8kN

100m

Fist layer: 6kN

100m

Fist layer: 4kN Fist layer: 2kN

100m

Interface





Initial layer (8kN)

Final layer (22kN)

Initial layer (6kN)

Final layer (22kN) 0.791MPa

0.585MPa

6kN initial compacted layer has the capability for further elastic and plastic deformation compared to 8kN initial compacted layer.

When 22kN compaction force is applied, more deformation (e.g. nesting, interlocking) is observed for 6kN case at the interface which increases the tensile strength value.





28

Particle Simulations Force Network

COMPRESSIVE FORCES TENSILE FORCES




Particle Simulations Microstructural evolution during processing

Access to inter-particle forces in the bulk and also across layers interface

Histogram of contact forces




Particle Simulations Contact Area

First layer compaction = 30MPa First layer compaction = 95MPa

Second layer load

0 MPa 250 MPa 0 MPa 200 MPa

R = radius of smallest particles




Particle Simulations First layer deformation and roughness




Particle Simulations First layer deformation and roughness

32

Decreasing Roughness

First layer compaction = 30MPa

Surface roughness = 0.40 Surface roughness = 0.30 First layer compaction = 95MPa




Particle Simulations Reloading plastically deformed particles

No contact force until the new particle touches the deformed surface

No bonding force develops in the reloading phase of the plastically deformed region




Particle Simulations Bonding Networks

34




35

Second layer load

0 MPa 250 MPa 0 MPa 200 MPa

First layer compaction = 30MPa First layer compaction = 95MPa

Increasing First Layer Force

Particle Simulations Bonding contact area




In-silico exploration of: Different formulations Different geometries Different processing conditions

Monolayer M1 Monolayer M2 Random Multilayer Cylindrical core

Predictive Compaction multi-scale modeling A Tool for Pharmaceutical Dosage Design




Modeling provides guidelines for product and process design including scale-up through understanding and quantification of the competing mechanisms

Many remaining challenges still ahead

Material characterization Databases Inter-particle models Simulation platforms Validation

Collaborators:

Adamssu Abebe Ilgaz Akseli Marcial Gonzalez Niranjan Kottala San Kiang Farank Nikfar Omar Sprockel Bereket Yohannes

Support from: Bristol-Myers Squibb Engineering Research Center (C-SOPS) National Science Foundation Gratefully acknowledged

In Summary




Thanks!

38

Using material science methodology and modeling predictive tools for enabling scale-up Strategy of material science approach to scale-upStrategy of material science approach to scale-upCase Study: Integrated Modeling of BilayersA Key Challenge: Predicting compact strength based on inter-particle bonding Predictive multi-scale modelingA Fundamental QuestionTheory Validation and Predictions Plastic and Bonding Predictive multi-scale modelingPredictive multi-scale modelingIntegrated Modeling of BilayersIntegrated Modeling of Bilayers: Case StudyMaterialsIntegrated Modeling of Bilayers: Case StudyDie FillingIntegrated Modeling of Bilayers: Case StudyFirst Layer Integrated Modeling of Bilayers: Case StudyFilling and Loading Second LayerIntegrated Modeling of Bilayers: Case StudyValidation Mechanistic Understanding via SimulationsExperimental characterizationExperimental characterizationExperimental characterizationSlide Number 27Slide Number 28Particle SimulationsMicrostructural evolution during processingParticle SimulationsContact Area Particle SimulationsFirst layer deformation and roughnessParticle SimulationsFirst layer deformation and roughnessSlide Number 33Particle SimulationsBonding NetworksParticle SimulationsBonding contact areaPredictive Compaction multi-scale modelingA Tool for Pharmaceutical Dosage Design In SummaryThanks!

440:221 Intro to Engineering Mechanics: Statics

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