Quantifying Innovation Patterns in Next Generation Solar Photovoltaics

David Garfield; Deborah Sunter; Isa Ferrall; Jessie Knapstein; Noah Kittner; Daniel Kammen

doi:10.1109/PVSC.2018.8548306

Quantifying Innovation Patterns in Next Generation Solar Photovoltaics

David Garfield, Deborah Sunter, Isa Ferrall, Jessie Knapstein, Noah Kittner, Daniel Kammen

Research output: Contribution to conference › Paper

1 Scopus Citations

Abstract

There have been numerous emerging next generation solar cell technologies with the potential to disrupt the solar industry. Perovskites in particular have taken the spotlight recently with unprecedented efficiency improvements. To quantify the rate of innovation in next generation solar technologies, we used learning curves to model improvements in efficiency relative to three parameters: time since first publication, cumulative publications, and cumulative patents. The learning rates found for perovskite solar cells are compared to those of dye-sensitized, and quantum dot solar cells. In doing so, this analysis aims to elicit a better understanding of the drivers of innovation for emerging solar technologies and identify technologies demonstrating extraordinary technological progress.

Original language	American English
Pages	1147-1151
Number of pages	5
DOIs	https://doi.org/10.1109/PVSC.2018.8548306
State	Published - 2018
Event	2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) - Waikoloa Village, Hawaii Duration: 10 Jun 2018 → 15 Jun 2018

Conference

Conference	2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC)
City	Waikoloa Village, Hawaii
Period	10/06/18 → 15/06/18

NREL Publication Number

NREL/CP-6A65-73744

Keywords

dye-sensitized
learning curves
perovskites
quantum dots
solar photovoltaics

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10.1109/PVSC.2018.8548306

Cite this

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title = "Quantifying Innovation Patterns in Next Generation Solar Photovoltaics",

abstract = "There have been numerous emerging next generation solar cell technologies with the potential to disrupt the solar industry. Perovskites in particular have taken the spotlight recently with unprecedented efficiency improvements. To quantify the rate of innovation in next generation solar technologies, we used learning curves to model improvements in efficiency relative to three parameters: time since first publication, cumulative publications, and cumulative patents. The learning rates found for perovskite solar cells are compared to those of dye-sensitized, and quantum dot solar cells. In doing so, this analysis aims to elicit a better understanding of the drivers of innovation for emerging solar technologies and identify technologies demonstrating extraordinary technological progress.",

keywords = "dye-sensitized, learning curves, perovskites, quantum dots, solar photovoltaics",

author = "David Garfield and Deborah Sunter and Isa Ferrall and Jessie Knapstein and Noah Kittner and Daniel Kammen",

year = "2018",

doi = "10.1109/PVSC.2018.8548306",

language = "American English",

pages = "1147--1151",

note = "2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) ; Conference date: 10-06-2018 Through 15-06-2018",

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TY - CONF

T1 - Quantifying Innovation Patterns in Next Generation Solar Photovoltaics

AU - Garfield, David

AU - Sunter, Deborah

AU - Ferrall, Isa

AU - Knapstein, Jessie

AU - Kittner, Noah

AU - Kammen, Daniel

PY - 2018

Y1 - 2018

N2 - There have been numerous emerging next generation solar cell technologies with the potential to disrupt the solar industry. Perovskites in particular have taken the spotlight recently with unprecedented efficiency improvements. To quantify the rate of innovation in next generation solar technologies, we used learning curves to model improvements in efficiency relative to three parameters: time since first publication, cumulative publications, and cumulative patents. The learning rates found for perovskite solar cells are compared to those of dye-sensitized, and quantum dot solar cells. In doing so, this analysis aims to elicit a better understanding of the drivers of innovation for emerging solar technologies and identify technologies demonstrating extraordinary technological progress.

AB - There have been numerous emerging next generation solar cell technologies with the potential to disrupt the solar industry. Perovskites in particular have taken the spotlight recently with unprecedented efficiency improvements. To quantify the rate of innovation in next generation solar technologies, we used learning curves to model improvements in efficiency relative to three parameters: time since first publication, cumulative publications, and cumulative patents. The learning rates found for perovskite solar cells are compared to those of dye-sensitized, and quantum dot solar cells. In doing so, this analysis aims to elicit a better understanding of the drivers of innovation for emerging solar technologies and identify technologies demonstrating extraordinary technological progress.

KW - dye-sensitized

KW - learning curves

KW - perovskites

KW - quantum dots

KW - solar photovoltaics

U2 - 10.1109/PVSC.2018.8548306

DO - 10.1109/PVSC.2018.8548306

M3 - Paper

SP - 1147

EP - 1151

T2 - 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC)

Y2 - 10 June 2018 through 15 June 2018

ER -

Quantifying Innovation Patterns in Next Generation Solar Photovoltaics

Abstract

Conference

NREL Publication Number

Keywords

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