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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
Materials for Energy – A Big Topic
Slide
2
Focus Journal Issues
Books
Dedicated Journals
Current Conferences
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
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
CO2 Growth over 50 Thousand Years
Recent CO2 Growth
What will it take to keep CO2 < 450 ppm ?
60 % Low-Carbon Energy Needed by 2050
IPCC “Climate Change 2014: Mitigation of Climate Change" CO2 ≈ 450 ppm
(to keep atmospheric CO2 ≈ 450 ppm)
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)
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
Development Time Historically Decades
Slide
10
Can Materials-By-Design Change This ?
Slide
11
Want Disruptive Development Trajectories
Materials Design via Design Principles
Slide
12
(as practiced within EFRC Center for Inverse Design)
Close Coupling of - HT-Theory & - HT-Experiment Central
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)
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
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
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
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 ?)
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)
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!!)
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
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
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
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 ?
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
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!
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
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
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