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Energy-Related Materials & Applications
John Perkins
National Renewable Energy Laboratory, Golden, CO USA
Workshop on Combinatorial Approaches to Functional Materials
May 5, 2014
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Materials for Energy – A Big Topic
Slide
2
Focus Journal Issues
Books
Dedicated Journals
Current Conferences
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Topics To Discuss
Slide
3
I. Introduction – Scope of the Energy Challenge
II. High-Throughput Materials Property Measurements
III. Measuring Functionality
IV. High-Throughput Device Optimization
V. Characterizing Interfaces – A Practical Compromise ?
VI. Summary and Challenges
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World Energy Usage Increasing
mtoe: millions tons oil equivalent
from BP Statistical Review of World Energy June 2013 13000
0
An
nu
al E
ner
gy U
sage
(m
toe
)
14 % Carbon
Free
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CO2 Growth over 50 Thousand Years
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Recent CO2 Growth
What will it take to keep CO2 < 450 ppm ?
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60 % Low-Carbon Energy Needed by 2050
IPCC “Climate Change 2014: Mitigation of Climate Change" CO2 ≈ 450 ppm
(to keep atmospheric CO2 ≈ 450 ppm)
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Currently @ ~ 14% Low-Carbon Energy
mtoe: millions tons oil equivalent
from BP Statistical Review of World Energy June 2013 13000
0
An
nu
al E
ner
gy U
sage
(m
toe
)
14 % Carbon
Free
(incluces Nuclear, Hyrdoelectricity & Renewables)
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Example Technologies for Energy
Slide
9
Thin Film PV
Organic PV (OPV)
Organic LED (OLED)
Electrochromic Window (from Granqvist et al).
Solar Fuel Production (from JCAP)
Hydrogen Fuel Cell (from DOE.gov)
• Lots of Materials • Lots of Interfaces
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Development Time Historically Decades
Slide
10
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Can Materials-By-Design Change This ?
Slide
11
Want Disruptive Development Trajectories
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Materials Design via Design Principles
Slide
12
(as practiced within EFRC Center for Inverse Design)
Close Coupling of - HT-Theory & - HT-Experiment Central
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Easy HT-Materials Characterization
Slide
13
NREL UV/VIS Optical Mapping Optical Property Map
• Cost ≈ 30K in Hardware • Measurement time ≈ 5 sec / spot • Analysis Straight Forward
Everybody Can Have Their Own Taylor et al., Advanced Functional Materials, 18, 3169, (2008)
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HT-Structure/Phase Mapping @ NREL
Slide
14
CoO
NiO ZnO
Growth
Combi Co-Sputtering 2-4 “libraries” / day 50 spots / library
Structure - XRD Mapping
4 libraries / night
Composition – XRF Mapping
8 libraries / night
Structure / Phase Map (20 libraries)
Data Analysis: 1 Grad Student Month
• Medium Throughput Experiments
• Data Analysis Limited
Cost ≈ $700 K
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Prototype HT-XRD @ SLAC
Fe Ni
Co
• Libraries on 3 or 4 inch wafers • Concurrent XRD & XRF • Very Fast Data Acquisition in-situ Processing Experiments
X-rays
2D XRD Detector
Fluorescence Detector
Slide Courtesy of Apurva Mehta
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XRD w/in-situ Annealing
2D XRD Detector
Fluorescence Detector
• Today: ~ 2000 patterns/day • Future: Scalable to ~ 20-50K/day • Requires a synchrotron – Scarce Resource
Slide Courtesy of Apurva Mehta
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Challenges for Big Facility Experiments
Slide
17
Practical: 1. Standardizing library geometries to enable many users
vs. experimental flexibility ? 2. Remote Experimentation and Sample Throughput
- Mail in analysis with a few day turn around time ? Social: 1. Collaboration vs. Competition ? 2. Dedicated funding of measurement system and staff ?
Data Overload: 1. How do we turn this much data into actionable knowledge ?
(or How Can We Make Good Use of 10K Measurements Per Day ?)
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18
Spectrum Deconvolution Best Basis Patterns Phase Map
Long et al., Rev. Sci. Instr. (2009) (Takeuchi Group at U. Maryland & NIST)
Non-Negative Matrix Factorization applied to Fe-Pd-Ga Thin Film Alloys
Zarnetta et al., Intermetallics (2012) (used XRD Suite software from Takeuchi Group / NIST)
9 As-Deposited Phases ID’d Phase Evolution During Anneal
500 °C 600 °C 700 °C
Cluster Analysis applied to Phase Evolution in Ni-Cu-Ti Thin Film Alloys
XRD Data to Structure-Phase Maps (Current)
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Courtesy of Bruce van Dover
People Helping Computers Faster ?
Example: Al-Li-Fe phase diagram (Synthetic Data) • 28 composition points, 6 phases • 28170 seconds with no human input • 188 seconds with 4.3% of variables set by people (150x Faster!!)
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XRD Data to Knowledge: An Ongoing Challenge
Slide
20
http://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdf
http://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdfhttp://www-ssrl.slac.stanford.edu/content/sites/default/files/documents/high_throughput_workshop_technical_summary.pdf
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JCA
P H
IGH
TH
RO
UG
HP
UT E
XP
ERIM
ENTA
TION
SCANNING DROPLET CELL FOR SERIAL (PHOTO)ELECTROCHEMISTRY
1 mm2 sample
Photocurrent measured with sub-1 µA/cm2 sensitivity
Electrocatalysis experiments include collection of full CV at 4 s per sample. Catalytic activity of quaternary spaces are readily mapped.
• The JCAP scanning droplet cell enables serial (photo)electrochemical measurements with data quality rivaling traditional techniques
• Solution flow provides contact to 1 mm2 thin film sample
• 3-electrode cell with low uncompensated resistance
• Continuous solution flow replenishes active solution volume more than once per second
• Gasket-free design allows rapid rastering
. Gregoire, J. M. et al., Scanning Droplet Cell for High Throughput Electrochemical and Photoelectrochemical Measurements. Review of Scientific Instruments 2013, 84 (2), 024102 . JCAP is supported through the Office of Science of the U.S. Department of Energy (Award No. DE-SC0004993)
Slide Courtesy of John Gregoire
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JCA
P H
IGH
TH
RO
UG
HP
UT E
XP
ERIM
ENTA
TION
PARALLEL ELECTROCATALYST SCREEN FOR GAS EVOLVING REACTIONS: BUBBLE IMAGING
Array of 1mm2 catalyst samples
Image of samples in solution
Catalysts held at potential, t=0
Catalysts held at potential, t=30s
Automated bubble identification
• Parallel imaging of evolved gas bubbles for HER and OER catalysts
• Array of catalysts held at operating potential, 10-2s/sample demonstrated
• Independent of solution pH
• Carefully designed geometry and nucleation agents provide registry between catalyst samples and imaged bubbles
. Xiang, C. et al, A High Throughput Bubble Screening Method for Combinatorial Discovery of Electrocatalysts for Water Splitting. ACS Combinatorial Science 2014 . JCAP is supported through the Office of Science of the U.S. Department of Energy (Award No. DE-SC0004993)
Slide Courtesy of John Gregoire
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Full Device Optimization ?
Slide
23
Layered Cu(In,Ga)Se2 (CIGS) Solar Cell
Complex Optimization - 6 Materials
(TCO has 2 layers) - 5 Interfaces
How To Address ?
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24
Combinatorial Device Optimization (e.g. solar)
Figure: results of JV mapping of 1 row of combinatorial solar cell library
Composition
Real result (test material):
ZnS ZnO
Vertical gradient in absorber thickness e.g. SnS, CuSbS2
Uniform front grid and scribing (e.g. Al, Ag)
Horizontal gradient in n-type front contact = e.g. Zn(O,S), (Zn,Mg)O
Fabrication procedure: (hypothetical materials)
Figure: Schematics of high-throughout PV device fabrication approach
thin
t
hic
k SnS
O rich S rich contact gradient
abso
rber grad
ient
Combinatorial device capabilities are needed to bridge the gap between
materials research and technology development
Fabrication details
- common back contact
by evaporation
- absorber and contact
by co-sputtering
- shadow mask grid by e-
beam
Characterization/analysis details
- JV-curves under 1 Sun (AM1.5) solar simulator, 0.4 cm2 device area
- Automated analysis for PV device parameters VOC, JSC, FF, Eff., n, Rs, Rsh
Slide Courtesy of Andriy Zakutayev
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Devices by Design ?
Slide
25
Substrate
Back Contact
Charge Selective Contact Layer
Absorber
Junction Partner
Charge Selective Contact Layer
Front Contact
Generic Thin Film PV
- 7 Layers - 10 Variants / Layer
Empirical Optimization
107 Combinations!
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Devices by Design ?
Slide
26
Substrate
Back Contact
Charge Selective Contact Layer
Absorber
Junction Partner
Charge Selective Contact Layer
Front Contact
Generic Thin Film PV
- 7 Layers - 10 Variants / Layer
Empirical Optimization
107 Combinations!
Focus on the Interfaces
- 6 Interfaces - 102 Variants / Interface
600 Interfaces
Full Device
Modeling
Bulk Properties - via Theory - via Experiment
Interface Properties - via Theory - via Experiment
Devices By
Design
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27
Combi Interface Characterization (e.g. band offset)
Combinatorial: thickness wedge (parallel)
- deposit 1 thickness wedge (all at once)
- cool and transfer in vacuum (1 time)
Figure: Schematics of the Thickness-Wedge method
substrate thin film (0.1-10 nm)
thick film (>10 nm) hn
e-
Figure: Schematics of the traditional layer-by-layer method
Traditional: layer-by-layer method (serial method)
thickness
EF-E
VB
0
E
g
FB,p
FB,n
ECB
BE (CL)
ECL
EF-EVB
ΔEVB,CL
FB,n
FB,p Eg
- sequentially deposit 5-10 steps in thickness
- cool and transfer in vacuum to PES (5-10 times)
~5-10x faster parallel thickness wedge methods helps to study/optimize interfaces
- measure XPS/UPS core, VB, SEC energies
- plot vs thickness, determine offsets/barriers
EVB
Slide Courtesy of Andriy Zakutayev
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Summary
Slide
28
• Materials are critical to energy technologies
• High-throughput experiments are key to Materials-by-Design
• Materials are not enough
Need Devices-by-Design
• Challenges are not all technical
Large scale cooperation vs. competition
Funding models to promote such
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