Feel free to email Rachel for a PDF copy of any of these!
Timmins, A., & Kurchin, R. C. (2024). Addressing accuracy by prescribing precision: Bayesian error estimation of point defect energetics. Journal of Applied Physics, 136(9), 095701.
@article{beefdefects,
title = {Addressing accuracy by prescribing precision: Bayesian error estimation of point defect energetics},
author = {Timmins, Andrew and Kurchin, Rachel C.},
journal = {Journal of Applied Physics},
volume = {136},
issue = {9},
pages = {095701},
doi = {10.1063/5.0211543},
year = {2024}
}
With density functional theory (DFT), it is possible to calculate the formation energy of charged point defects and in turn to predict a range of experimentally relevant quantities, such as defect concentrations, charge transition levels, or recombination rates. While prior efforts have led to marked improvements in the accuracy of such calculations, comparatively modest effort has been directed at quantifying their uncertainties. However, in the broader DFT research space, the development of Bayesian Error Estimation Functionals (BEEF) has enabled uncertainty quantification (UQ) for other properties. In this paper, we investigate the utility of BEEF as a tool for UQ of defect formation energies. We build a pipeline for propagating BEEF energies through a formation-energy calculation and test it on intrinsic defects in several materials systems spanning a variety of chemistries, bandgaps, and crystal structures, comparing to prior published results where available. We also assess the impact of aligning to a deep-level transition rather than to the VBM (valence band maximum). We observe negligible dependence of the estimated uncertainty upon a supercell size, though the relationship may be obfuscated by the fact that finite-size corrections cannot be computed separately for each member of the BEEF ensemble. Additionally, we find an increase in estimated uncertainty with respect to the absolute charge of a defect and the relaxation around the defect site without deep-level alignment, but this trend is absent when the alignment is applied. While further investigation is warranted, our results suggest that BEEF could be a useful method for UQ in defect calculations.
Tang, J., Jiang, K., Tseng, P.-S., Kurchin, R. C., Porter, L. M., & Davis, R. F. (2024). Thermal stability and phase transformation of α-, κ(ε)-, and γ-Ga2O3 films under different ambient conditions. Applied Physics Letters, 125(9), 092104.
@article{ga2o3stability,
title = {Thermal stability and phase transformation of α-, κ(ε)-, and γ-Ga2O3 films under different ambient conditions},
author = {Tang, Jingyu and Jiang, Kunyao and Tseng, Po-Sen and Kurchin, Rachel C. and Porter, Lisa M. and Davis, Robert F.},
journal = {Applied Physics Letters},
volume = {125},
issue = {9},
pages = {092104},
doi = {10.1063/5.0214500},
year = {2024}
}
Phase transitions in metastable α-, κ(ε)-, and γ-Ga2O3 films to thermodynamically stable β-Ga2O3 during annealing in air, N2, and vacuum have been systematically investigated via in situ high-temperature x-ray diffraction (HT-XRD) and scanning electron microscopy (SEM). These respective polymorphs exhibited thermal stability to ∼471–525 °C, ∼773–825 °C, and ∼490–575 °C before transforming into β-Ga2O3, across all tested ambient conditions. Particular crystallographic orientation relationships were observed before and after the phase transitions, i.e., (0001) α-Ga2O3 → (-201) β-Ga2O3, (001) κ(ε)-Ga2O3 → (310) and (-201) β-Ga2O3, and (100) γ-Ga2O3 → (100) β-Ga2O3. The phase transition of α-Ga2O3 to β-Ga2O3 resulted in catastrophic damage to the film and upheaval of the surface. The respective primary and possibly secondary causes of this damage are the +8.6% volume expansion and the dual displacive and reconstructive transformations that occur during this transition. The κ(ε)- and γ-Ga2O3 films converted to β-Ga2O3 via singular reconstructive transformations with small changes in volume and unchanged surface microstructures.
Wang, X., Musielewicz, J., Tran, R., Ethirajan, S. K., Fu, X., Mera, H., Kitchin, J. R., Kurchin, R., & Ulissi, Z. W. (2024). Generalization of Graph-Based Active Learning Relaxation Strategies Across Materials. Machine Learning: Science and Technology, 5(2), 025018.
@article{wang2024generalization,
title = {Generalization of Graph-Based Active Learning Relaxation Strategies Across Materials},
author = {Wang, Xiaoxiao and Musielewicz, Joseph and Tran, Richard and Ethirajan, Sudheesh Kumar and Fu, Xiaoyan and Mera, Hilda and Kitchin, John R and Kurchin, Rachel and Ulissi, Zachary W},
journal = {Machine Learning: Science and Technology},
volume = {5},
issue = {2},
pages = {025018},
doi = {10.1088/2632-2153/ad37f0},
year = {2024}
}
Although density functional theory (DFT) has aided in accelerating the discovery of new materials, such calculations are computationally expensive, especially for high-throughput efforts. This has prompted an explosion in exploration of machine learning (ML) assisted techniques to improve the computational efficiency of DFT. In this study, we present a comprehensive investigation of the broader application of Finetuna, an active learning framework to accelerate structural relaxation in DFT with prior information from Open Catalyst Project pretrained graph neural networks. We explore the challenges associated with out-of-domain systems: alcohol (C>2) on metal surfaces as larger adsorbates, metal oxides with spin polarization, and three-dimensional (3D) structures like zeolites and metal organic frameworks. By pre-training ML models on large datasets and fine-tuning the model along the simulation, we demonstrate the framework’s ability to conduct relaxations with fewer DFT calculations. Depending on the similarity of the test systems to the training systems, a more conservative querying strategy is applied. Our best-performing Finetuna strategy reduces the number of DFT single-point calculations by 80% for alcohols and 3D structures, and 42% for oxide systems.
Kurchin, R. C. (2024). Using Bayesian parameter estimation to learn more from data without black boxes. Nature Reviews Physics, 1–3.
@article{kurchin2024using,
title = {Using Bayesian parameter estimation to learn more from data without black boxes},
author = {Kurchin, Rachel C},
journal = {Nature Reviews Physics},
pages = {1--3},
year = {2024},
publisher = {Nature Publishing Group UK London},
doi = {10.1038/s42254-024-00698-0}
}
In an age of expensive experiments and hype around new data-driven methods, researchers understandably want to ensure they are gleaning as much insight from their data as possible. Rachel C. Kurchin argues that there is still plenty to be learned from older approaches without turning to black boxes.
Kurchin, R. C., Gandhi, D., & Viswanathan, V. (2023). Nonequilibrium Electrochemical Phase Maps: Beyond Butler–Volmer Kinetics. The Journal of Physical Chemistry Letters, 14(35), 7802–7807.
@article{Kurchin2023,
doi = {10.1021/acs.jpclett.3c01992},
year = {2023},
month = aug,
publisher = {American Chemical Society ({ACS})},
volume = {14},
number = {35},
pages = {7802--7807},
author = {Kurchin, Rachel C. and Gandhi, Dhairya and Viswanathan, Venkatasubramanian},
title = {Nonequilibrium Electrochemical Phase Maps: Beyond Butler{\textendash}Volmer Kinetics},
journal = {The Journal of Physical Chemistry Letters}
}
Accurate models of electrochemical kinetics at electrode–electrolyte interfaces are crucial to understanding the high-rate behavior of energy storage devices. Phase transformation of electrodes is typically treated under equilibrium thermodynamic conditions, while realistic operation is at finite rates. Analyzing phase transformations under nonequilibrium conditions requires integrating nonlinear electrochemical kinetic models with thermodynamic models. This had only previously been demonstrated for Butler–Volmer kinetics, where it can be done analytically. In this work, we develop a software package capable of the efficient numerical inversion of rate relationships for general kinetic models. We demonstrate building nonequilibrium phase maps, including for models such as Marcus–Hush–Chidsey that require computation of an integral, and also discuss the impact of a variety of assumptions and model parameters, particularly on high-rate phase behavior. Even for a fixed set of parameters, the magnitude of the critical current can vary by more than a factor of 2 among kinetic models.
Annevelink, E., Kurchin, R., Muckley, E., Kavalsky, L., Hegde, V. I., Sulzer, V., Zhu, S., Pu, J., Farina, D., Johnson, M., & others. (2022). AutoMat: Automated materials discovery for electrochemical systems. MRS Bulletin, 47(10), 1036–1044.
@article{annevelink2022automat,
title = {AutoMat: Automated materials discovery for electrochemical systems},
author = {Annevelink, Emil and Kurchin, Rachel and Muckley, Eric and Kavalsky, Lance and Hegde, Vinay I and Sulzer, Valentin and Zhu, Shang and Pu, Jiankun and Farina, David and Johnson, Matthew and others},
journal = {MRS Bulletin},
volume = {47},
number = {10},
pages = {1036--1044},
year = {2022},
publisher = {Springer},
doi = {doi.org/10.1557/s43577-022-00424-0}
}
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical materials will be critical, but their development currently relies heavily on human-time-intensive experimental trial and error and computationally expensive first-principles, mesoscale, and continuum simulations. We present an automated workflow, AutoMat, which accelerates these computational steps by introducing both automated input generation and management of simulations across scales from first principles to continuum device modeling. Furthermore, we show how to seamlessly integrate multi-fidelity predictions, such as machine learning surrogates or automated robotic experiments “in-the-loop.” The automated framework is implemented with design space search techniques to dramatically accelerate the overall materials discovery pipeline by implicitly learning design features that optimize device performance across several metrics. We discuss the benefits of AutoMat using examples in electrocatalysis and energy storage and highlight lessons learned.
Mistry, A., Verma, A., Sripad, S., Ciez, R., Sulzer, V., Brosa Planella, F., Timms, R., Zhang, Y., Kurchin, R., Dechent, P., Li, W., Greenbank, S., Ahmad, Z., Krishnamurthy, D., Fenton, A. M., Tenny, K., Patel, P., Juarez Robles, D., Gasper, P., … Viswanathan, V. (2021). A Minimal Information Set to Enable Verifiable Theoretical Battery Research. ACS Energy Letters, 3831–3835.
@article{Mistry2021,
title = {A Minimal Information Set to Enable Verifiable Theoretical Battery Research},
author = {Mistry, Aashutosh and Verma, Ankit and Sripad, Shashank and Ciez, Rebecca and Sulzer, Valentin and Brosa Planella, Ferran and Timms, Robert and Zhang, Yumin and Kurchin, Rachel and Dechent, Philipp and Li, Weihan and Greenbank, Samuel and Ahmad, Zeeshan and Krishnamurthy, Dilip and Fenton, Alexis M. and Tenny, Kevin and Patel, Prehit and Juarez Robles, Daniel and Gasper, Paul and Colclasure, Andrew and Baskin, Artem and Scown, Corinne D. and Subramanian, Venkat R. and Khoo, Edwin and Allu, Srikanth and Howey, David and DeCaluwe, Steven and Roberts, Scott A. and Viswanathan, Venkatasubramanian},
date = {2021-10-11},
year = {2021},
month = oct,
journaltitle = {ACS Energy Letters},
shortjournal = {ACS Energy Lett.},
pages = {3831--3835},
issn = {2380-8195, 2380-8195},
doi = {10.1021/acsenergylett.1c01710},
langid = {english}
}
Kurchin, R., & Viswanathan, V. (2020). Marcus–Hush–Chidsey Kinetics at Electrode–Electrolyte Interfaces. The Journal of Chemical Physics, 153(13), 134706.
@article{Kurchin2020-1,
title = {Marcus–{{Hush}}–{{Chidsey}} Kinetics at Electrode–Electrolyte Interfaces},
author = {Kurchin, Rachel and Viswanathan, Venkatasubramanian},
date = {2020-10-07},
year = {2020},
month = oct,
journaltitle = {The Journal of Chemical Physics},
shortjournal = {J. Chem. Phys.},
volume = {153},
number = {13},
pages = {134706},
issn = {0021-9606, 1089-7690},
doi = {10.1063/5.0023611},
langid = {english}
}
Electrochemical kinetics at electrode–electrolyte interfaces limit the performance of devices including fuel cells and batteries. While the importance of moving beyond Butler–Volmer kinetics and incorporating the effect of electronic density of states of the electrode has been recognized, a unified framework that incorporates these aspects directly into electrochemical performance models is still lacking. In this work, we explicitly account for the density functional theory-calculated density of states numerically in calculating electrochemical reaction rates for a variety of electrode–electrolyte interfaces. We first show the utility of this for two cases related to Li metal electrodeposition and stripping on a Li surface and a Cu surface (anode-free configuration). The deviation in reaction rates is minor for cases with flat densities of states such as Li, but is significant for Cu due to nondispersive d-bands creating large variation. Finally, we consider a semiconducting case of a solid-electrolyte interphase consisting of LiF and Li2CO3 and note the importance of the Fermi level at the interface pinned by the redox reaction occurring there. We identify the asymmetry in reaction rates as a function of discharge/charge naturally within this approach.
Kurchin, R. C., Poindexter, J. R., Vahanissi, V., Savin, H., del Canizo, C., & Buonassisi, T. (2020). How Much Physics Is in a Current–Voltage Curve? Inferring Defect Properties from Photovoltaic Device Measurements. IEEE Journal of Photovoltaics, 1–6.
@article{Kurchin2020,
title = {How Much Physics Is in a Current–Voltage Curve? {{Inferring}} Defect Properties from Photovoltaic Device Measurements},
shorttitle = {How Much Physics Is in a Current–Voltage Curve?},
author = {Kurchin, Rachel C. and Poindexter, Jeremy R. and Vahanissi, Ville and Savin, Hele and del Canizo, Carlos and Buonassisi, Tonio},
options = {useprefix=true},
year = {2020},
journaltitle = {IEEE Journal of Photovoltaics},
shortjournal = {IEEE J. Photovoltaics},
pages = {1--6},
issn = {2156-3381, 2156-3403},
doi = {10.1109/JPHOTOV.2020.3010105},
langid = {english}
}
Defect-assisted recombination processes are critical to understand, as they frequently limit the photovoltaic (PV) device performance. However, the physical parameters governing these processes can be extremely challenging to measure, requiring specialized techniques and sample preparation. And yet the fact that they limit performance as measured by current–voltage (JV) characterization indicates that they must have some detectable signal in that measurement. In this work, we use numerical device models that explicitly account for these parameters alongside highthroughput JV measurements and Bayesian inference to construct probability distributions over recombination parameters, showing the ability to recover values consistent with previously reported literature measurements. The Bayesian approach enables easy incorporation of data and models from other sources; we demonstrate this with temperature dependence of carrier capture cross-sections. The ability to extract these fundamental physical parameters from standardized, automated measurements on completed devices is promising for both established industrial PV technologies and newer research-stage ones.
Kurchin, R., Romano, G., & Buonassisi, T. (2019). Bayesim: A Tool for Adaptive Grid Model Fitting with Bayesian Inference. Computer Physics Communications, 239, 161–165.
@article{bayesim,
title = {Bayesim: A Tool for Adaptive Grid Model Fitting with {{Bayesian}} Inference},
author = {Kurchin, Rachel and Romano, Giuseppe and Buonassisi, Tonio},
year = {2019},
journaltitle = {Computer Physics Communications},
shortjournal = {Comput. Phys. Commun.},
volume = {239},
pages = {161--165},
publisher = {{Elsevier B.V.}},
issn = {00104655},
doi = {10.1016/j.cpc.2019.01.022}
}
Bayesian inference is a widely used and powerful analytical technique in fields such as astronomy and particle physics but has historically been underutilized in some other disciplines including semiconductor devices. In this work, we introduce bayesim, a Python package that utilizes adaptive grid sampling to efficiently generate a probability distribution over multiple input parameters to a forward model using a collection of experimental measurements. We discuss the implementation choices made in the code, showcase two examples in photovoltaics, and discuss general prerequisites for the approach to apply to other systems.
Correa-Baena, J.-P., Nienhaus, L., Kurchin, R. C., Shin, S. S., Wieghold, S., Hartono, N. T. P., Layurova, M., Klein, N. D., Poindexter, J. R., Polizzotti, A., Sun, S., Bawendi, M. G., & Buonassisi, T. (2018). A-Site Cation in Inorganic A3Sb2I9 Perovskite Influences Structural Dimensionality, Exciton Binding Energy, and Solar Cell Performance. Chemistry of Materials.
@article{antimony,
ids = {A3Sb2I9},
title = {A-Site Cation in Inorganic {{A}}3{{Sb}}2{{I}}9 Perovskite Influences Structural Dimensionality, Exciton Binding Energy, and Solar Cell Performance},
author = {Correa-Baena, J.-P. and Nienhaus, L. and Kurchin, R.C. and Shin, S.S. and Wieghold, S. and Hartono, N.T.P. and Layurova, M. and Klein, N.D. and Poindexter, J.R. and Polizzotti, A. and Sun, S. and Bawendi, M.G. and Buonassisi, T.},
year = {2018},
journaltitle = {Chemistry of Materials},
shortjournal = {Chem. Mater.},
issn = {15205002},
doi = {10.1021/acs.chemmater.8b00676}
}
Kurchin, R. C., Gorai, P., Buonassisi, T., & Stevanović, V. (2018). Structural and Chemical Features Giving Rise to Defect Tolerance of Binary Semiconductors. Chemistry of Materials, 30(16), 5583–5592.
@article{binary_dt,
title = {Structural and Chemical Features Giving Rise to Defect Tolerance of Binary Semiconductors},
author = {Kurchin, Rachel C. and Gorai, Prashun and Buonassisi, Tonio and Stevanović, Vladan},
year = {2018},
journaltitle = {Chemistry of Materials},
shortjournal = {Chem. Mater.},
volume = {30},
number = {16},
pages = {5583--5592},
issn = {15205002},
doi = {10.1021/acs.chemmater.8b01505}
}
Defect tolerance, or the resilience of electronic transport properties of a crystalline material to the presence of defects, has emerged as a critical factor in the success of hybrid lead halide perovskites as photovoltaic absorbers. A key aspect of defect tolerance is the shallow character of dominant intrinsic defects. However, while qualitative heuristics to identify other defect-tolerant materials have been proposed, in particular, the presence of a partially oxidized ns2 cation such as Pb, no compelling comprehensive understanding of how these shallow defects arise has yet emerged. Using modern defect theory and defect calculations, we conduct a detailed investigation of the mechanisms and identify specific features related to the chemical composition and crystal structure that give rise to defect tolerance. We find that an ns2 cation is necessary but not sufficient to guarantee shallow cation vacancies in an s–p system, and that a compound’s crystal structure can ensure shallow anion vacancies in a ...
Brandt, R. E., Poindexter, J. R., Gorai, P., Kurchin, R. C., Hoye, R. L. Z., Nienhaus, L., Wilson, M. W. B., Polizzotti, J. A., Sereika, R., Raimundas, Z., Lee, L. C., Macmanus-driscoll, J. L., Bawendi, M., Stevanovic, V., & Buonassisi, T. (2017). Searching for “Defect-Tolerant” Photovoltaic Materials: Combined Theoretical and Experimental Screening. Chemistry of Materials, 29(11), 4667–4674.
@article{nspaper,
ids = {DT_search},
title = {Searching for “Defect-Tolerant” Photovoltaic Materials: Combined Theoretical and Experimental Screening},
author = {Brandt, Riley E and Poindexter, Jeremy R and Gorai, Prashun and Kurchin, Rachel C and Hoye, Robert L Z and Nienhaus, Lea and Wilson, Mark W B and Polizzotti, J Alexander and Sereika, Raimundas and Raimundas, Z and Lee, Lana C and Macmanus-driscoll, Judith L and Bawendi, Moungi and Stevanovic, Vladan and Buonassisi, Tonio},
year = {2017},
journaltitle = {Chemistry of Materials},
shortjournal = {Chem. Mater.},
volume = {29},
number = {11},
eprint = {1},
eprinttype = {pmid},
pages = {4667--4674},
doi = {10.1021/acs.chemmater.6b05496}
}
Recently, we and others have proposed screening criteria for “defect-tolerant” photovoltaic (PV) absorbers, identifying several classes of semiconducting compounds with electronic structures similar to those of hybrid lead−halide perovskites. In this work, we reflect on the accuracy and prospects of these new design criteria through a combined experimental and theoretical approach. We construct a model to extract photoluminescence lifetimes of six of these candidate PV absorbers, including four (InI, SbSI, SbSeI, and BiOI) for which time-resolved photoluminescence has not been previously reported. The lifetimes of all six candidate materials exceed 1 ns, a threshold for promising early stage PV device performance. However, there are variations between these materials, and none achieve lifetimes as high as those of the hybrid lead−halide perovskites, suggesting that the heuristics for defect-tolerant semiconductors are incomplete. We explore this through firstprinciples point defect calculations and Shockley−Read−Hall recombination models to describe the variation between the measured materials. In light of these insights, we discuss the evolution of screening criteria for defect tolerance and high-performance PV materials.
Poindexter, J. R., Hoye, R. L. Z., Nienhaus, L., Kurchin, R. C., Morishige, A. E., Looney, E. E., Osherov, A., Lai, B., Bulovic, V., Stevanovic, V., Bawendi, M. G., & Buonassisi, T. (2017). High Tolerance to Iron Contamination in Lead Halide Perovskite Solar Cells. ACS Nano, 11(7), 7101–7109.
@article{Fe_MAPI,
title = {High Tolerance to Iron Contamination in Lead Halide Perovskite Solar Cells},
author = {Poindexter, Jeremy R and Hoye, Robert L Z and Nienhaus, Lea and Kurchin, Rachel C and Morishige, Ashley E and Looney, Erin E and Osherov, Anna and Lai, Barry and Bulovic, Vladimir and Stevanovic, Vladan and Bawendi, Moungi G and Buonassisi, Tonio},
year = {2017},
journaltitle = {ACS Nano},
volume = {11},
number = {7},
pages = {7101--7109},
doi = {10.1021/acsnano.7b02734}
}
The relationship between charge-carrier lifetime and the tolerance of lead halide perovskite (LHP) solar cells to intrinsic point defects has drawn much attention by helping to explain rapid improvements in device efficiencies. However, little is known about how charge-carrier lifetime and solar cell performance in LHPs are affected by extrinsic defects (i.e., impurities), including those that are common in manufacturing environments and known to introduce deep levels in other semiconductors. Here, we evaluate the tolerance of LHP solar cells to iron introduced via intentional contamination of the feedstock and examine the root causes of the resulting efficiency losses. We find that comparable efficiency losses occur in LHPs at feedstock iron concentrations approximately 100 times higher than those in p-type silicon devices. Photoluminescence measurements correlate iron concentration with nonradiative recombination, which we attribute to the presence of deep-level iron interstitials, as calculated from first-principles, as well as iron-rich particles detected by synchrotron-based X-ray fluorescence microscopy. At moderate contamination levels, we witness prominent recovery of device efficiencies to near-baseline values after biasing at 1.4 V for 60 s in the dark. We theorize that this temporary effect arises from improved charge-carrier collection enhanced by electric fields strengthened from ion migration toward interfaces. Our results demonstrate that extrinsic defect tolerance contributes to high efficiencies in LHP solar cells, which inspires further investigation into potential large-scale manufacturing cost savings as well as the degree of overlap between intrinsic and extrinsic defect tolerance in LHPs and “perovskite-inspired” lead-free stable alternatives.
Hoye, R. L. Z., Lee, L. C., Kurchin, R. C., Huq, T. N., Zhang, K. H. L., Sponseller, M., Nienhaus, L., Brandt, R. E., Jean, J., Polizzotti, J. A., Kursumović, A., Bawendi, M. G., Bulović, V., Stevanović, V., Buonassisi, T., & Macmanus-Driscoll, J. L. (2017). Strongly Enhanced Photovoltaic Performance and Defect Physics of Air-Stable Bismuth Oxyiodide (BiOI). Advanced Materials.
@article{BiOI,
title = {Strongly Enhanced Photovoltaic Performance and Defect Physics of Air-Stable Bismuth Oxyiodide ({{BiOI}})},
author = {Hoye, R.L.Z. and Lee, L.C. and Kurchin, R.C. and Huq, T.N. and Zhang, K.H.L. and Sponseller, M. and Nienhaus, L. and Brandt, R.E. and Jean, J. and Polizzotti, J.A. and Kursumović, A. and Bawendi, M.G. and Bulović, V. and Stevanović, V. and Buonassisi, T. and Macmanus-{D}riscoll, J.L.},
year = {2017},
journaltitle = {Advanced Materials},
shortjournal = {Adv. Mater.},
issn = {15214095},
doi = {10.1002/adma.201702176}
}
Brandt, R. E., Kurchin, R. C., Steinmann, V., Kitchaev, D., Roat, C., Levcenco, S., Ceder, G., Unold, T., Buonassisi, T., & Berlin, H. Z. (2017). Rapid Semiconductor Device Characterization through Bayesian Parameter Estimation. Joule, 1(4), 843–856.
@article{SnSJoule,
ids = {SnS_Joule},
title = {Rapid Semiconductor Device Characterization through {{Bayesian}} Parameter Estimation},
author = {Brandt, Riley E and Kurchin, Rachel C and Steinmann, Vera and Kitchaev, Daniil and Roat, Chris and Levcenco, Sergiu and Ceder, Gerbrand and Unold, Thomas and Buonassisi, Tonio and Berlin, Helmholtz Zentrum},
year = {2017},
journaltitle = {Joule},
volume = {1},
number = {4},
pages = {843--856},
publisher = {{Elsevier Inc.}},
issn = {25424351},
doi = {10.1016/j.joule.2017.10.001}
}
High-performance computing can greatly improve the workflow of experimentalists in energy materials, through the use of Bayesian inference. This allows us to solve the inverse problem of extracting underlying materials properties through the measurement of the electrical behavior of completed devices. Cheaper, faster measurements can be substituted for longer direct measurements of individual properties, without sacrificing accuracy or precision. We provide a general framework to apply this to other materials systems and devices.
Shin, S. S., Correa-Baena, J.-P., Kurchin, R. C., Polizzotti, A., Yoo, J. J., Wieghold, S., Bawendi, M. G., & Buonassisi, T. (2017). Solvent-Engineering Method to Deposit Compact Bismuth-Based Thin Films: Mechanism and Application to Photovoltaics. Chemistry of Materials, acs.chemmater.7b03227.
@article{Shin2017,
ids = {Bi_films},
title = {Solvent-Engineering Method to Deposit Compact Bismuth-Based Thin Films: Mechanism and Application to Photovoltaics},
author = {Shin, Seong Sik and Correa-Baena, Juan-Pablo and Kurchin, Rachel C. and Polizzotti, Alex and Yoo, Jason Jungwan and Wieghold, Sarah and Bawendi, Moungi G. and Buonassisi, Tonio},
year = {2017},
journaltitle = {Chemistry of Materials},
shortjournal = {Chem. Mater.},
pages = {acs.chemmater.7b03227},
issn = {0897-4756},
doi = {10.1021/acs.chemmater.7b03227}
}
Bismuth-based materials have been studied as alternatives to lead-based perovskite materials for photovoltaic applications. However, poor film quality has limited device performance. In this work, we develop a solvent-engineering method, and show that it is applicable to several bismuth-based compounds. Through this method, we obtain compact films of methylammonium bismuth iodide (MBI), cesium bismuth iodide (CBI), and formamidinium bismuth iodide (FBI). On the basis of film growth theory and experimental analyses, we propose a possible mechanism of film formation. Additionally, we demonstrate that the resultant compact MBI film is more suitable to fabricate efficient and stable photovoltaic devices, compared to baseline MBI films with pinholes. We further employ a new hole-transporting material to reduce the valence-band offset with the MBI. The best-performing photovoltaic device exhibits an open-circuit voltage of 0.85 V and fill factor of 73%, and a power conversion efficiency of 0.71 %, the highest reported values for MBI-based photovoltaic devices.
Needleman, D. B., Poindexter, J. R., Kurchin, R. C., Peters, I. M., Wilson, G., & Buonassisi, T. (2016). Economically Sustainable Scaling of Photovoltaics to Meet Climate Targets. Energy & Environmental Science, 9, 2122–2129.
@article{climatepaper,
title = {Economically Sustainable Scaling of Photovoltaics to Meet Climate Targets},
author = {Needleman, D. Berney and Poindexter, Jeremy R. and Kurchin, Rachel C. and Peters, I. Marius and Wilson, Gregory and Buonassisi, Tonio},
date = {2016},
year = {2016},
journaltitle = {Energy \& Environmental Science},
shortjournal = {Energy Environ. Sci.},
volume = {9},
pages = {2122--2129},
publisher = {{Royal Society of Chemistry}},
issn = {1754-5692},
doi = {10.1039/C6EE00484A}
}
To meet climate targets, power generation capacity from photovoltaics (PV) in 2030 will have to be much greater than is predicted from either steady state growth using today’s manufacturing capacity or industry roadmaps. Analysis of whether current technology can scale, in an economically sustainable way, to sufficient levels to meet these targets has not yet been undertaken, nor have tools to perform this analysis been presented. Here, we use bottom-up cost modeling to predict cumulative capacity as a function of technological and economic variables and find that today’s technology falls short in two ways. Profits are too small relative to upfront factory costs to grow manufacturing capacity rapidly enough to meet climate targets, and cost is too high to generate enough demand to meet climate targets. We show that decreasing the capital intensity (capex) of PV manufacturing to increase manufacturing capacity and effectively reducing cost (e.g., through higher efficiency) to increase demand are the most effective and least risky ways to address these barriers to scale. We also assess the effects of variations in demand due to hard-to-predict factors, like public policy, on the necessary reductions in cost. Finally, we review examples of redundant technology pathways for crystalline silicon PV to achieve the necessary innovations in capex, performance, and price.
Hoye, R. L. Z., Schulz, P., Schelhas, L. T., Holder, A. M., Stone, K. H., Perkins, J. D., Vigil-Fowler, D., Siol, S., Scanlon, D. O., Zakutayev, A., Walsh, A., Smith, I. C., Melot, B. C., Kurchin, R. C., Wang, Y., Shi, J., Marques, F. C., Berry, J. J., Tumas, W., … Buonassisi, T. (2016). Perovskite-Inspired Photovoltaics: Best Practices in Materials Characterization and Calculations. Chemistry of Materials, 1964–1988.
@article{bestpractices,
ids = {Hoye2016},
title = {Perovskite-Inspired Photovoltaics: Best Practices in Materials Characterization and Calculations},
author = {Hoye, R. L. Z. and Schulz, P. and Schelhas, L. T. and Holder, A. M. and Stone, K. H. and Perkins, J. D. and Vigil-Fowler, D. and Siol, S. and Scanlon, D. O. and Zakutayev, A. and Walsh, A. and Smith, I. C. and Melot, B. C. and Kurchin, R. C. and Wang, Y. and Shi, J. and Marques, F. C. and Berry, J. J. and Tumas, W. and Lany, S. and Stevanović, V. and Toney, M. F. and Buonassisi, T.},
year = {2016},
journaltitle = {Chemistry of Materials},
shortjournal = {Chem. Mater.},
pages = {1964--1988},
issn = {0897-4756},
doi = {10.1021/acs.chemmater.6b03852}
}
Recently, there has been an explosive growth in research based on hybrid lead–halide perovskites for photovoltaics owing to rapid improvements in efficiency. The advent of these materials for solar applications has led to widespread interest in understanding the key enabling properties of these materials. This has resulted in renewed interest in related compounds and a search for materials that may replicate the defect-tolerant properties and long lifetimes of the hybrid lead-halide perovskites. Given the rapid pace of development of the field, the rises in efficiencies of these systems have outpaced the more basic understanding of these materials. Measuring or calculating the basic properties, such as crystal/electronic structure and composition, can be challenging because some of these materials have anisotropic structures, and/or are composed of both heavy metal cations and volatile, mobile, light elements. Some consequences are beam damage during characterization, composition change under vacuum, or compound effects, such as the alteration of the electronic structure through the influence of the substrate. These effects make it challenging to understand the basic properties integral to optoelectronic operation. Compounding these difficulties is the rapid pace with which the field progresses. This has created an ongoing need to continually evaluate best practices with respect to characterization and calculations, as well as to identify inconsistencies in reported values to determine if those inconsistencies are rooted in characterization methodology or materials synthesis. This article describes the difficulties in characterizing hybrid lead–halide perovskites and new materials and how these challenges may be overcome. The topic was discussed at a seminar at the 2015 Materials Research Society Fall Meeting & Exhibit. This article highlights the lessons learned from the seminar and the insights of some of the attendees, with reference to both recent literature and controlled experiments to illustrate the challenges discussed. The focus in this article is on crystallography, composition measurements, photoemission spectroscopy, and calculations on perovskites and new, related absorbers. We suggest how the reporting of the important artifacts could be streamlined between groups to ensure reproducibility as the field progresses.
Hoye, R. L. Z., Brandt, R. E., Osherov, A., Stevanović, V., Stranks, S. D., Wilson, M. W. B., Kim, H., Akey, A. J., Kurchin, R. C., Poindexter, J. R., Wang, E. N., Bawendi, M. G., Bulović, V., & Buonassisi, T. (2015). Methylammonium Bismuth Iodide as a Lead-Free, Stable Hybrid Organic-Inorganic Solar Absorber. Chemistry - A European Journal, n/a-n/a.
@article{MBI,
ids = {Hoye2015,MABI},
title = {Methylammonium Bismuth Iodide as a Lead-Free, Stable Hybrid Organic-Inorganic Solar Absorber},
author = {Hoye, Robert L. Z. and Brandt, Riley E. and Osherov, Anna and Stevanović, Vladan and Stranks, Samuel D. and Wilson, Mark W. B. and Kim, Hyunho and Akey, Austin J. and Kurchin, Rachel C. and Poindexter, Jeremy R. and Wang, Evelyn N. and Bawendi, Moungi G. and Bulović, Vladimir and Buonassisi, Tonio},
date = {2015-12},
year = {2015},
month = dec,
journaltitle = {Chemistry - A European Journal},
shortjournal = {Chem. - Eur. J.},
pages = {n/a-n/a},
issn = {09476539},
doi = {10.1002/chem.201505055}
}
Methylammonium lead halide (MAPbX3) perovskites exhibit exceptional carrier transport properties. But their commercial deployment as solar absorbers is currently limited by their intrinsic instability in the presence of humidity and their lead content. Guided by our theoretical predictions, we explored the potential of methylammonium bismuth iodide (MBI) as a solar absorber through detailed materials characterization. We synthesized phasepure MBI by solution and vapor processing. In contrast to MAPbX3, MBI is air stable, forming a surface layer that does not increase the recombination rate. We found that MBI luminesces at room temperature, with the vapor-processed films exhibiting superior photoluminescence (PL) decay times that are promising for photovoltaic applications. The thermodynamic, electronic, and structural features of MBI that are amenable to these properties are also present in other hybrid ternary bismuth halide compounds. Through MBI, we demonstrate a lead-free and stable alternative to MAPbX3 that has a similar electronic structure and nanosecond lifetimes.
Brandt, R. E., Kurchin, R. C., Hoye, R. L. Z., Poindexter, J. R., Wilson, M. W. B., Sulekar, S., Lenahan, F., Yen, P. X. T., Stevanović, V., Nino, J. C., Bawendi, M. G., & Buonassisi, T. (2015). Investigation of Bismuth Triiodide (BiI3) for Photovoltaic Applications. The Journal of Physical Chemistry Letters, 6, 4297–4302.
@article{BiI3,
title = {Investigation of Bismuth Triiodide ({{BiI}}3) for Photovoltaic Applications},
author = {Brandt, Riley E. and Kurchin, Rachel C. and Hoye, Robert L. Z. and Poindexter, Jeremy R. and Wilson, Mark W. B. and Sulekar, Soumitra and Lenahan, Frances and Yen, Patricia X.T. and Stevanović, Vladan and Nino, Juan C. and Bawendi, Moungi G. and Buonassisi, Tonio},
date = {2015-10-12},
year = {2015},
month = oct,
journaltitle = {The Journal of Physical Chemistry Letters},
shortjournal = {J. Phys. Chem. Lett.},
volume = {6},
pages = {4297--4302},
publisher = {{American Chemical Society}},
issn = {1948-7185},
doi = {10.1021/acs.jpclett.5b02022}
}
Guided by predictive discovery framework, we investigate bismuth triiodide (BiI3) as a candidate thin-film photovoltaic (PV) absorber. BiI3 was chosen for its optical properties and the potential for ?defect-tolerant? charge transport properties, which we test experimentally by measuring optical absorption and recombination lifetimes. We synthesize phase-pure BiI3 thin films by physical vapor transport and solution processing and single-crystals by an electrodynamic gradient vertical Bridgman method. The bandgap of these materials is ?1.8 eV, and they demonstrate room-temperature band-edge photoluminescence. We measure monoexponential recombination lifetimes in the range of 180?240 ps for thin films, and longer, multiexponential dynamics for single crystals, with time constants up to 1.3 to 1.5 ns. We discuss the outstanding challenges to developing BiI3 PVs, including mechanical and electrical properties, which can also inform future selection of candidate PV absorbers. Guided by predictive discovery framework, we investigate bismuth triiodide (BiI3) as a candidate thin-film photovoltaic (PV) absorber. BiI3 was chosen for its optical properties and the potential for ?defect-tolerant? charge transport properties, which we test experimentally by measuring optical absorption and recombination lifetimes. We synthesize phase-pure BiI3 thin films by physical vapor transport and solution processing and single-crystals by an electrodynamic gradient vertical Bridgman method. The bandgap of these materials is ?1.8 eV, and they demonstrate room-temperature band-edge photoluminescence. We measure monoexponential recombination lifetimes in the range of 180?240 ps for thin films, and longer, multiexponential dynamics for single crystals, with time constants up to 1.3 to 1.5 ns. We discuss the outstanding challenges to developing BiI3 PVs, including mechanical and electrical properties, which can also inform future selection of candidate PV absorbers.