Feel free to email Rachel for a PDF copy of any of these! If you are interested in Rachel’s earlier work prior to founding the ACME group, check out her Google Scholar page!
Akrap, A., Bordelon, D., Chatterjee, S., Dahlberg, E. D., Devaty, R. P., Frolov, S. M., Gould, C., Greene, L. H., Guchhait, S., Hamlin, J. J., Hunt, B. M., Jardine, M. J. A., Kayyalha, M., Kurchin, R. C., Kozii, V., Legg, H. F., Mazin, I. I., Mourik, V., Özgüler, A. B., … Zwolak, J. P. (2026). Report on reproducibility in condensed matter physics. Phys. Rev. B, 113(11), 119601. https://link.aps.org/doi/10.1103/27h6-yghn
@article{pqi_workshop,
title = {Report on reproducibility in condensed matter physics},
author = {Akrap, A. and Bordelon, D. and Chatterjee, S. and Dahlberg, E. D. and Devaty, R. P. and Frolov, S. M. and Gould, C. and Greene, L. H. and Guchhait, S. and Hamlin, J. J. and Hunt, B. M. and Jardine, M. J. A. and Kayyalha, M. and Kurchin, R. C. and Kozii, V. and Legg, H. F. and Mazin, I. I. and Mourik, V. and \"Ozg\"uler, A. B. and Pe\~nuela-Parra, J. and Seradjeh, B. and Skinner, B. and Quader, K. F. and Zwolak, J. P.},
journal = {Phys. Rev. B},
volume = {113},
issue = {11},
pages = {119601},
numpages = {13},
year = {2026},
month = mar,
publisher = {American Physical Society},
doi = {10.1103/27h6-yghn},
url = {https://link.aps.org/doi/10.1103/27h6-yghn}
}
We present recommendations to improve reproducibility and replicability in condensed matter physics. This area of physics has consistently produced both fundamental insights into the workings of matter and transformative inventions. Our recommendations result from a collaboration that includes researchers from academia and government laboratories, scientific journalists, legal professionals, representatives of publishers, professional societies, and other experts. The group met in person in May 2024 at a conference at the University of Pittsburgh to discuss the growing challenges related to research reproducibility and replicability in condensed matter physics. In this report, we discuss best practices and policies at all stages of the scientific process to safeguard the value of condensed matter. We hope this report will lay the groundwork for a broader conversation to develop subfield-specific recommendations.
Jo, S., Jia, H., Wang, X., Wu, R. E., Wang, L., Gershanok, S. A., Rivnay, J., Chan, M. K. Y., Kurchin, R., & Cohen-Karni, T. (2026). 4-Electron Oxygen Reduction Reaction (ORR) with Iron Phthalocyanine (FePc) Functionalized Nanowire Templated-3D Fuzzy Graphene (NT-3DFG). ACS Catalysis.
@article{FePc,
title = {4-Electron Oxygen Reduction Reaction (ORR) with Iron Phthalocyanine (FePc) Functionalized Nanowire Templated-3D Fuzzy Graphene (NT-3DFG)},
author = {Jo, Seonghan and Jia, Haili and Wang, Xiaoxiao and Wu, Ruiheng Edbalt and Wang, Liyang and Gershanok, Samuel Ariav and Rivnay, Jonathan and Chan, Maria KY and Kurchin, Rachel and Cohen-Karni, Tzahi},
journal = {ACS Catalysis},
year = {2026},
publisher = {ACS Publications},
doi = {10.1021/acscatal.6c01943}
}
Iron phthalocyanine (FePc) is a promising alternative to platinum-based catalysts for sustainable energy devices; however, the plane-symmetry of Fe-N4 sites, random aggregation, and poor conductivity of FePc present major barriers for their application as oxygen reduction reaction (ORR) electrocatalysts. Here, we report the synergistic effects of FePc electrocatalysts supported by a nanowire-templated three-dimensional fuzzy graphene (FePc@NT-3DFG) substrate. The in situ functionalized oxygen groups (iFOGs) at the edge of NT-3DFG localize Fe active sites in FePc under alkaline ORR conditions. With a uniform FePc distribution through many single layers of graphene, the NT-3DFG substrates improve O2 adsorption and catalytic activity while stabilizing the electrochemical activity during reactions. The FePc@NT-3DFG catalyst exhibits fast ORR kinetics with an extremely low Tafel slope of 28.3 ± 2.7 mV/dec, a higher half-wave potential of 0.911 ± 0.004 V (vs RHE), and notable long-term stability at 0.5 V (vs RHE) of 96.0 ± 0.4% retention after 30 h. Surface chemistry spectra validate electronic configuration modification of Fe at the iFOGs. Density functional theory calculations indicate that the extra layers of graphene improve oxygen adsorption. Moreover, additional exploration of other transition metal phthalocyanines supports the effects of iFOGs through the transition toward 4e− ORR. This work offers an expanded strategy for active site modification through edge-based graphene substrates for 4e− ORR.
Drew, J., Godse, S., Liang, Y., Pathak, A., Malen, J. A., & Kurchin, R. C. (2026). Analysis and uncertainty quantification of thermal transport measurements through Bayesian parameter estimation. Review of Scientific Instruments, 97(3).
@article{bpe_fdtr,
title = {Analysis and uncertainty quantification of thermal transport measurements through Bayesian parameter estimation},
author = {Drew, Jeremy and Godse, Shravan and Liang, Yuxing and Pathak, Abhishek and Malen, Jonathan A and Kurchin, Rachel C},
journal = {Review of Scientific Instruments},
volume = {97},
number = {3},
year = {2026},
publisher = {AIP Publishing},
doi = {10.1063/5.0316853}
}
The thermal transport community is increasingly interested in rigorous uncertainty quantification (UQ) of their measurements. In this study, we argue that Bayesian parameter estimation (BPE) represents a powerful framework for both analysis/fitting and UQ. We provide a detailed walkthrough of the technique (including code to duplicate our results) and example analysis based on measuring the thermal conductance of a gold/sapphire interface with frequency domain thermoreflectance. Comparisons are made against traditional analysis/UQ techniques adopted by the thermal transport community. Notable advantages of BPE include the interpretability of its results, including the capacity to indicate incorrect input assumptions, as well as a way to balance overall goodness of fit against prior knowledge of feasible parameter values. In some cases, incorporating this additional information can affect not only the magnitude of error bars but also the inferred values themselves.
Wang, X., Loli, J. A., Ulissi, Z. W., de Boer, M. P., Webler, B. A., & Kurchin, R. C. (2025). Constraint Active Search in Process Window Optimization for Powder Feed Directed Energy Deposition. Integrating Materials and Manufacturing Innovation.
@article{cas_immi,
title = {Constraint Active Search in Process Window Optimization for Powder Feed Directed Energy Deposition},
author = {Wang, Xiaoxiao and Loli, Jose A. and Ulissi, Zachary W. and de Boer, Maarten P. and Webler, Bryan A. and Kurchin, Rachel C.},
journal = {Integrating Materials and Manufacturing Innovation},
doi = {10.1007/s40192-025-00393-7},
year = {2025}
}
Optimizing process parameters for directed energy deposition is crucial to achieve high-quality printed parts. However, this optimization process often entails significant time and cost investments. An initial investigation into the process window can be conducted through the examination of single tracks. In this work, we investigate the utility of constraint active search (CAS) to efficiently identify process window that yield 4340 low-alloy steel single tracks with desired geometrical features. The effectiveness of the CAS method was assessed through experiments with physical and interpolated measurement. Fifty single tracks from randomly sampled process parameter combinations with different power, scan velocity, and laser spot size and ten single tracks from CAS-generated parameters were produced and analyzed. The results demonstrate that our search method outperforms random search, with 80% of parameter sets identified as desirable compared to only 4% in the case of random search. Moreover, an interpolated ground truth in input spaces of various dimensionalities was built in order to assess repeatability without excessive experimental cost. The results indicate that the CAS achieves higher precision compared to grid search and random search, especially in higher-dimensional process parameter spaces.
Diehl, P., Soneson, C., Kurchin, R. C., Mounce, R., & Katz, D. S. (2025). The Journal of Open Source Software (JOSS): Bringing Open-Source Software Practices to the Scholarly Publishing Community for Authors, Reviewers, Editors, and Publishers. Journal of Librarianship and Scholarly Communication, 12(2), eP18285.
@article{joss_jlsc,
title = {The Journal of Open Source Software (JOSS): Bringing Open-Source Software Practices to the Scholarly Publishing Community for Authors, Reviewers, Editors, and Publishers},
author = {Diehl, Patrick and Soneson, Charlotte and Kurchin, Rachel C. and Mounce, Ross and Katz, Daniel S.},
journal = {Journal of Librarianship and Scholarly Communication},
volume = {12},
issue = {2},
pages = {eP18285},
doi = {10.31274/jlsc.18285},
year = {2025}
}
Introduction: Open-source software (OSS) is a critical component of open science, but contributions to the OSS ecosystem are systematically undervalued in the current academic system. The Journal of Open Source Software (JOSS) contributes to addressing this by providing a venue (that is itself free and diamond OA and all open-source, built in a layered structure using widely available elements/services of the scholarly publishing ecosystem) for publishing OSS, run in the style of open-source software itself. One element of JOSS is that it uses open peer review in a collaborative, iterative format, unlike most publishers. Additionally, all the parts of JOSS, from the reviews to the papers to the software that is the subject of the papers to the software that the journal runs, are open.
Background: We describe JOSS’s history and its peer review process using an editorial bot, and present statistics gathered from JOSS’s public review history on GitHub showing an increasing number of peer reviewed papers each year. We discuss the new JOSSCast and use it as a data source to understand reasons why interviewed authors decided to publish in JOSS.
Discussion and Outlook: JOSS’s process differs significantly from traditional journals, which has impeded JOSS’s inclusion in indexing services such as Web of Science. In turn, this discourages researchers within certain academic systems, such as Italy’s, which emphasize the importance of Web of Science and/or Scopus indexing for grant applications and promotions. JOSS is a fully diamond open access journal with a cost of around US$5 per paper for the 401 papers published in 2023. The scalability of running JOSS with volunteers and financing JOSS with grants and donations is discussed.
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.