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At least 991 records · Page 55

Development of Transition-Edge Sensor X-ray Microcalorimeter Linear Array for Compton Scattering and Energy Dispersive Diffraction Imaging

In this paper we present a strip transition-edge sensor microcalorimeter linear array detector developed for energy dispersive X-ray diffraction imaging and Compton scattering applications. The prototype detector is an array of 20 transition-edge sensors with absorbers in strip geometry arranged in a linear array. We discuss the fabrication steps needed to develop this array including Mo/Cu bilayer, Au electroplating, and proofof-principle fabrication of long strips of SiNx membranes. We demonstrate minimal unwanted effect of strip geometry on X-ray pulse response and showlinear relationship of 1/pulse height and pulse decay times with absorber length. For the absorber lengths studied, our preliminary measurements show energy resolutions of 40-180eV near 17 keV. Furthermore, we show that the heat flow to the cold bath is nearly independent of the absorber area and depends on the SiNx membrane geometry.

47 OTHER INSTRUMENTATION↗

PR100 One-Year Progress Summary Report: Preliminary Modeling Results and High-Resolution Solar and Wind Data Sets

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a 2-year study by the U.S. Department of Energy's (DOE's) Grid Deployment Office and six national laboratories to comprehensively analyze stakeholder-driven pathways to Puerto Rico's clean energy future. In Year 1 of the study, the PR100 team rigorously modeled and analyzed scenarios that meet Puerto Rico's renewable energy targets and achieve short-term recovery goals and long-term energy resilience. This report, which summarizes PR100 progress in Year 1, provides considerations that can inform potential funding and implementation decisions by key federal and local agencies and stakeholders. The summary report follows the publication in July 2022 of a PR100 Six-Month Progress Update (in English and Spanish), as well as public webinars in February 2022 to kick off the study and in July 2022 to present the 6-month update. A final written report and web-based visuals will be published in late 2023. All publications and public events associated with the study will be available in Spanish and English. This report is also available in Spanish https://www.nrel.gov/docs/fy23osti/85144.pdf.

100%↗

Intersubband Transitions in Lead Halide Perovskite-Based Quantum Wells for Mid-Infrared Detectors

Due to their excellent optical and electrical properties as well as versatile growth and fabrication processes, lead halide perovskites have been widely considered as promising candidates for green energy and applications related to optoelectronics. Here, we investigate their potential applications at infrared wavelengths by modeling the intersubband transitions in perovskite-based quantum well systems. Both single-well and double-well structures are studied, and their energy levels as well as the corresponding wave functions and intersubband transition energies are calculated by solving the one-dimensional Schrödinger equations. Via adjustment of the quantum well and barrier thicknesses, the intersubband transition energies can be tuned to cover a broad infrared wavelength range. We also find that the lead halide perovskite-based quantum wells possess high absorption coefficients. In conclusion, the widely tunable transition energies and high absorption coefficients of the perovskite-based quantum well systems, combined with their unique material and electrical properties, may enable an alternative material system for infrared photodetector applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Computationally Accelerated Discovery and Experimental Demonstration of High-Performance Materials for Advanced Solar Thermochemical Hydrogen Production

This project achieved its overarching goal of accelerating the discovery and validation of solar thermochemical hydrogen (STCH) materials through a tightly integrated approach that combined high-throughput computational screening, advanced machine learning (ML), and experimental testing. Guided by the objectives outlined in the Statement of Project Objectives (SOPO), our work fulfilled all major milestones across four technical tasks and delivered scientific breakthroughs and practical tools that significantly exceeded the original scope of the project. We began by addressing the challenge of predicting material phase stability through machine learning. A novel Python module was developed to generate thousands of meaningful features from composition, structure, and electronic properties, enabling rapid and reproducible ML model development. Using these tools, we trained a model to predict temperature-dependent Gibbs energies (G(T)) for inorganic crystalline materials with near-chemical accuracy—roughly 40 meV/atom—marking the first such descriptor of its kind. We also introduced a new machine-learned tolerance factor, τ, that accurately predicted perovskite formability with over 90% success, outperforming traditional heuristic models, such as the Goldschmidt tolerance factor. These capabilities allowed for rapid and accurate predictions of phase stability across a vast oxide composition space, setting the stage for high-throughput thermodynamic screening. Building on this foundation, we conducted an extensive computational screening of candidate STCH oxide materials. Over 1.1 million perovskite compositions were evaluated using the τ descriptor, leading to the identification of more than 27,000 predicted stable structures. Using density functional theory (DFT), we refined over 68,000 multinary perovskite structures and computed oxygen vacancy formation energies for over 1,300 ternary and double perovskites. These calculations enabled us to isolate compounds with redox behavior consistent with STCH requirements and resulted in a public dataset now hosted on the Materials Project. Recognizing that thermodynamic screening alone is insufficient, we addressed kinetic limitations by developing a suite of tools to estimate transition state (TS) energies for key redox reactions. We implemented a novel bounding approach that provides lower and upper estimates of TS energies with dramatically reduced computational cost, requiring less than 10% of the CPU time of a full nudged elastic band (NEB) calculation while maintaining high accuracy. This enabled rapid evaluation of over 200 reaction pathways across 90 materials. To further accelerate screening, we developed a SISSO-based ML model to predict diffusion barriers with a 96.7% success rate in classifying fast vs. slow materials, supporting a robust, data-driven framework for assessing redox kinetics. Experimental validation was critical to confirming the predictive power of our models. We synthesized and tested a wide array of candidate materials, including Mn-doped hercynite and several Gd- and La-based perovskites. Notably, Sr 0.4 Gd 0.6 Mn 0.6 Al 0.4 O 3 (SGMA) and Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF) emerged as leading STCH materials, exhibiting robust redox cycling and high hydrogen yields exceeding 150 µmol H 2 /g per cycle. These materials also retained over 50% of their hydrogen productivity under high-conversion conditions (H 2 O:H 2 = 1333:1), demonstrating strong thermodynamic favorability and promising performance under industrially relevant scenarios. Additional candidates, such as La 2 MnNiO 6 (L2MN), were found to produce even higher yields than ceria under standard STCH conditions. Our collaborators at Sandia National Laboratories confirmed these findings using high-temperature X-ray diffraction and thermogravimetric analysis, observing stable phase evolution and reversible redox activity. In several respects, the project went beyond the goals initially outlined in the SOPO. We published 17 peer-reviewed articles, including a large dataset of over 66,000 theoretical perovskites and a new structure prediction method (SPuDS-DFT) that accurately identifies ground-state structures at a fraction of the cost of traditional DFT. We demonstrated that our machine-learned G(T) model offers accuracy rivaling quasiharmonic calculations while being orders of magnitude faster. In partnership with the Materials Project, we made our datasets openly available, providing a powerful new resource for the broader materials science community. The combined computational and experimental advances of this project represent a significant advance in STCH materials discovery. By creating a robust, generalizable, and open workflow for thermodynamic and kinetic screening, and validating key findings through synthesis and reactor testing, we have provided a practical and scalable pathway for the rapid identification of new redox-active materials. The tools, data, and materials developed under this project are already supporting ongoing research and have laid the groundwork for the next generation of solar fuel technologies.

08 HYDROGEN↗

Biophysical and Structural Features of αβT ‐Cell Receptor Mechanosensing: A Paradigmatic Shift in Understanding T‐Cell Activation

ABSTRACT αβT cells protect vertebrates against many diseases, optimizing surveillance using mechanical force to distinguish between pathophysiologic cellular alterations and normal self‐constituents. The multi‐subunit αβT‐cell receptor (TCR) operates outside of thermal equilibrium, harvesting energy via physical forces generated by T‐cell motility and actin‐myosin machinery. When a peptide‐bound major histocompatibility complex molecule (pMHC) on an antigen presenting cell is ligated, the αβTCR on the T cell leverages force to form a catch bond, prolonging bond lifetime, and enhancing antigen discrimination. Under load, the αβTCR undergoes reversible structural transitions involving partial unfolding of its clonotypic immunoglobulin‐like (Ig) domains and coupled rearrangements of associated CD3 subunits and structural elements. We postulate that transitions provide critical energy to initiate the signaling cascade via induction of αβTCR quaternary structural rearrangements, associated membrane perturbations, exposure of CD3 ITAMs to phosphorylation by non‐receptor tyrosine kinases, and phase separation of signaling molecules. Understanding force‐mediated signaling by the αβTCR clarifies long‐standing questions regarding αβTCR antigen recognition, specificity and affinity, providing a basis for continued investigation. Future directions include examining atomistic mechanisms of αβTCR signal initiation, performance quality, tissue compliance adaptability, and T‐cell memory fate. The mechanotransduction paradigm will foster improved rational design of T‐cell based vaccines, CAR‐Ts, and adoptive therapies.

Immunology↗

Port Technical Assistance Program: A Proposed Initiative to Support U.S. Ports Through Energy Innovation

This document highlights the crucial importance of the maritime sector within the United States (U.S.) economy, serving as a key node for trade and global goods transportation. U.S. ports are currently grappling with challenges posed by rising shipping demands, the health impacts of diesel fuel reliance, and the technology adoptions of global trade partners due to increasing environmental regulations. This document proposes forming a technical assistance program, led by Pacific Northwest National Laboratory (PNNL), to help U.S. ports transition to sustainable energy solutions that not only improve environmental and community outcomes, but also enhance resilience to unexpected weather events and reduce pressure on local utilities. Coordinated by PNNL, this initiative would offer a web-based platform of consolidated resources and tools for comprehensive strategic planning and cost-benefit analysis. It also seeks to establish a collaborative network between ports and national laboratories to facilitate the sharing of best practices. The document suggests that optimizing resource allocation and providing tailored support could be achieved through strategic categorization of ports within this network, with relevant attributes and examples detailed in the report. The anticipated benefits of such a program could include increased efficiency and cost savings in port operations and the advancement of scientific innovation via alternative energy research. Also, it could enhance economic growth and competitiveness in international trade by enabling ports to meet shipping demands and develop resilient critical infrastructure through informed, long-term strategies.

33 ADVANCED PROPULSION SYSTEMS↗

Today's Energy Challenges, Tomorrow's Solutions: Integrated Energy Pathways: Modernizing Our Energy Systems

Integrated Energy Pathways Today's electric grid was built for century-old needs, not the needs of tomorrow's emerging system. As the cost of generating electricity falls, products and systems that previously operated on other types of fuels are becoming increasingly "electrified." Instead of a one-way flow of electricity to systems that operate independently from one another, we are seeing more bi-directional connectivity between the grid and multiple end points. Integrated Energy Systems require a fundamental rethinking of grid infrastructure and the path electricity takes from the source of generation to the end point of use. Inevitably, the way the grid is managed today won't be the way it is managed 10-15 years from now. NREL is pioneering the fundamental research needed to guide this transition through renewable energy fuels and low-carbon electricity generation. Working with industry partners, we can collaboratively develop a fresh approach to energy generation, security, resilience, and advanced mobility.

energy security↗

Industry case studies: Finance

This article, the third in a series on the U.S. Department of Energy and IDEA collaboration, focuses on financial strategies used by institutions to support district energy system modernization and decarbonization. It highlights how effective funding models, long-term cost analysis, and leadership support are critical to implementing large-scale infrastructure upgrades. The case studies show different approaches to financing. Ball State University demonstrates how life-cycle cost analysis and phased funding—supported by state funding, bonds, and grants—enabled a transition to geothermal energy. Penn State’s Hershey Medical Center emphasizes the importance of financial leadership, shifting from reactive budgeting to data-driven, proactive investment in infrastructure. The University of Washington highlights how comprehensive data collection and analytics can justify investments and even create self-sustaining funding mechanisms like green revolving funds. Overall, the article shows that combining strong financial planning, data-driven decision-making, and innovative funding approaches is essential for advancing sustainable district energy systems while managing high upfront costs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Workshop on Addressing Rigor and Reproducibility in Thermal, Heterogeneous Catalysis

Heterogeneous catalysis has long served as the bedrock of the manufacturing of energy carriers, fuels and chemicals, and various technologies for pollution abatement. The significant complexity and variability spanning the entire breadth of catalyst material properties, synthesis methods, characterization techniques, and evaluation procedures, has focused attention on the need to establish community-accepted best practices for ensuring high-quality, benchmarked, and reproducible data. In addition, increased societal urgency to transition to clean energy and reduce greenhouse gas concentrations has incentivized interdisciplinary, convergent, and translational approaches to catalysis research in recent years. Research engineers and scientists with expertise cutting broadly across materials science, chemical synthesis, interfacial science, spectroscopy, and methods of data science and computational simulation, all bring diverse and important perspectives to catalysis research, but often with little awareness of the complexity of catalytic systems, especially in their working environment. As has already occurred in other scientific fields, there has been growing recognition and consensus in the heterogeneous catalysis research community that mechanisms are needed to improve the rigor and reproducibility (R&R) of experimental measurements, to ensure alignment of the broader research community with a common core of best practices specific to the realization of high-quality catalysis research. Similarly, the field is moving rapidly toward computationally informed and data science-driven catalyst design, but the success of implementing such predictive tools hinges on model training and validation rooted in rigorously obtained and reproducible experimental data that are benchmarked to common specifications. As such, this workshop was convened to prepare a report summarizing best practices for reporting data and performing experiments that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal, heterogeneous catalysis. Additionally, we discussed recommendations for future actions that may improve R&R in this field. The workshop organizers and participants include a diverse range of catalysis researchers from various employment sectors (e.g., academia, industry, national laboratory), institutional mission and resources (e.g., PhD-granting research universities, non-PhD-granting teaching universities), career stage (e.g., early, mid and late-career), technical expertise, and demographic background. This diverse group was involved in the discussion of workshop agenda items, writing this report, and discussing possible future action items for the community to consider, which helped ensure that a broad range of perspectives were captured in the description of the problems at hand and the creation of actionable solutions that may be effectively adopted by the diverse practitioners in catalysis research. Importantly, this group of workshop participants also included very early career researchers (e.g., senior PhD students, postdoctoral scholars) who will become the next generation of scientific leaders in various sectors, thus capturing emerging perspectives of newcomers to the field to shape its future while positively impacting the development of its future workforce. We envision that this effort will help advance the field of catalysis science by improving the rigor and reproducibility of experimental data collected by current researchers and future newcomers to the field, which is of broad importance to health and vitality of any scientific discipline. Therefore, best practices identified in this endeavor for thermal heterogeneous catalysis can be translated to such efforts in other areas of catalysis and other scientific fields involving the study of materials, and vice versa. We also envision this to be an ongoing effort, with future workshops that are convened to discuss issues of rigor and reproducibility on technical topics that were unable to be covered in this workshop due to its scope limitations, and as emerging methods and materials become more prevalent in the research community.

36 MATERIALS SCIENCE↗

Structural Phase Transitions between Layered Indium Selenide for Integrated Photonic Memory

The primary mechanism of optical memoristive devices relies on phase transitions between amorphous and crystalline states. The slow or energy-hungry amorphous–crystalline transitions in optical phase-change materials are detrimental to the scalability and performance of devices. Leveraging an integrated photonic platform, nonvolatile and reversible switching between two layered structures of indium selenide (In 2 Se 3 ) triggered by a single nanosecond pulse is demonstrated. The high-resolution pair distribution function reveals the detailed atomistic transition pathways between the layered structures. With interlayer “shear glide” and isosymmetric phase transition, switching between the α- and β-structural states contains low re-configurational entropy, allowing reversible switching between layered structures. Broadband refractive index contrast, optical transparency, and volumetric effect in the crystalline–crystalline phase transition are experimentally characterized in molecular-beam-epitaxy-grown thin films and compared to ab initio calculations. Finally, the nonlinear resonator transmission spectra measure of incremental linear loss rate of 3.3 GHz, introduced by a 1.5 µm-long In 2 Se 3 -covered layer, resulted from the combinations of material absorption and scattering.

36 MATERIALS SCIENCE↗

Electronic correlations and flattened band in magnetic Weyl semimetal candidate Co 3 Sn 2 S 2

The interplay between electronic correlations and topological protection may offer a rich avenue for discovering emergent quantum phenomena in condensed matter. However, electronic correlations have so far been little investigated in Weyl semimetals (WSMs) by experiments. Here, we report a combined optical spectroscopy and theoretical calculation study on the strength and effect of electronic correlations in a magnet Co 3 Sn 2 S 2 . The electronic kinetic energy estimated from our optical data is about half of that obtained from single-particle ab initio calculations in the ferromagnetic ground state, which indicates intermediate-strength electronic correlations in this system. Furthermore, comparing the energy and side-slope ratios between the interband-transition peaks at high energies in the experimental and single-particle-calculation-derived optical conductivity spectra with the bandwidth-renormalization factors obtained by many-body calculations enables us to estimate the Coulomb-interaction strength (U ~ 4 eV) in Co 3 Sn 2 S 2 . Besides, a sharp experimental optical conductivity peak at low energy, which is absent in the single-particle-calculation-derived spectrum but is consistent with the optical conductivity peaks obtained by many-body calculations with U ~ 4 eV, indicates that an electronic band connecting the two Weyl cones is flattened by electronic correlations and emerges near the Fermi energy in Co 3 Sn 2 S 2 . Our work paves the way for exploring flat-band-generated quantum phenomena in WSMs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evidence for an isomeric {pi}½{sup +}[411] state in {sup 183}Ta

We report on the identification of a new isomeric state in Ta populated via the ground-state -decay of Hf. The experiment was performed at the KISS setup at RIKEN, where neutron-rich hafnium isotopes were produced via multi-nucleon transfer (MNT) reactions, followed by laser ionization of hafnium atoms, mass separation, and detection using an electron-gamma coincidence system. Isomeric spectroscopy was carried out by gating on different electron-gamma time correlations. A 459.1 keV -ray transition was identified in delayed spectra, and a half-life of μ was extracted through time-distribution fitting. The 459.1 keV state in Ta is known from previous work and has been assigned a Nilsson orbital configuration of , while a proposed new isomeric state above it is interpreted as a configuration that decays to via a low-energy, unobserved E2 transition. This is consistent with the systematic trends in neighbouring odd-A nuclei and transition rate calculations. Similar content being viewed by others

Doshi, S.↗

Solar and battery can reduce energy costs and provide affordable outage backup for US households

Distributed energy resources are promising solutions for household energy affordability and resilience as weather extremes and aging infrastructure intensify grid reliability risks. This study presents a comprehensive nationwide assessment of over 500,000 U.S. households, evaluating economic and backup viability of solar-battery systems. We find that 60% of households could reduce electricity costs with average savings of 15%, while 63% of households could achieve affordable backup power during power outages covering an average of 51% of their essential energy needs. However, these benefits show limited alignment with areas of greatest need, particularly in regions facing high outage risks. We also identify significant disparities in access to solar and battery, with less-populated and disadvantaged communities showing consistently lower viability. Furthermore, these findings demonstrate the need for targeted policy interventions to ensure equitable access to solar-battery benefits, especially as states transition from net energy metering to other electricity tariff policies.

14 SOLAR ENERGY↗

Search for in-band transitions in the candidate superdeformed band in Si 28

Background: Superdeformed (SD) bands are suggested by theory around Ca 40 and in lighter alpha-conjugate nuclei such as Mg 24 , Si 28 , and S 32 . Such predictions originate from a number of theoretical models including mean-field models and antisymmetrized molecular dynamics (AMD) calculations. While SD bands have been identified in Ca 40 and its near neighbors, evidence of their existence in the lighter, midshell nuclei is circumstantial at best. Additionally, the key evidence of superdeformation would be the observation of transitions with high B ( E 2 ) transition strengths connecting states in a rotational sequence. This is challenging information to obtain since the bands lie at a high excitation energy and competition from out-of-band decay is dominant. Purpose: The purpose of the present study is to establish a new methodology to circumvent the difficulties in identifying and quantifying in-band transitions through directly populating candidate states in the SD band in Si 28 through inelastic alpha scattering, selecting such states with a spectrometer, and measuring their gamma-ray decay with a large array of high-purity germanium detectors, allowing direct access to electromagnetic transition strengths. Methods: Excited states in Si 28 were populated in the Si 28 ( α , α ' ) reaction using a 130-MeV He 4 beam from the K140 AVF cyclotron at the Research Center for Nuclear Physics. Outgoing alpha particles were analyzed using the Grand Raiden spectrometer positioned at an angle of 9 . 1 ° to favor the population of states with J ≈ 4 . Coincident gamma rays were detected with the CAGRA array of 12 HPGe clover detectors augmented by a set of four large LaBr 3 detectors. Results: Data analysis showed that it was possible to identify additional low-energy transitions in competition with high-energy decays from excited states in Si 28 in the vicinity of 10 MeV. However, while the candidate 4 + SD state at 10.944 MeV was populated, a 1148-keV transition to the candidate 2 + SD state at 9.796 MeV was not observed, and only an upper limit for its transition strength of B ( E 2 ) < 43 W.u. could be established. This contradicts AMD predictions of ≈ 200 W.u. for such a transition. Conclusion: The present study strongly rejects the hypothesis that the candidate set of states identified in Si 28 represents an SD band, which demonstrates the potential of the methodology devised here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states

We report molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. The application of Nesbet’s theorem makes it possible to recast a typical extrapolation task, training on correlation energies for small molecules and predicting correlation energies for large molecules, into an interpolation task based on the properties of orbital pairs. We demonstrate the importance of preserving physical constraints, including invariance conditions and size consistency, when generating the input for the machine learning model. Numerical improvements are demonstrated for different datasets covering total and relative energies for thermally accessible organic and transition-metal containing molecules, non-covalent interactions, and transition-state energies. MOB-ML requires training data from only 1% of the QM7b-T dataset (i.e., only 70 organic molecules with seven and fewer heavy atoms) to predict the total energy of the remaining 99% of this dataset with sub-kcal/mol accuracy. This MOB-ML model is significantly more accurate than other methods when transferred to a dataset comprising of 13 heavy atom molecules, exhibiting no loss of accuracy on a size intensive (i.e., per-electron) basis. It is shown that MOB-ML also works well for extrapolating to transition-state structures, predicting the barrier region for malonaldehyde intramolecular proton-transfer to within 0.35 kcal/mol when only trained on reactant/product-like structures. Finally, the use of the Gaussian process variance enables an active learning strategy for extending the MOB-ML model to new regions of chemical space with minimal effort. We demonstrate this active learning strategy by extending a QM7b-T model to describe non-covalent interactions in the protein backbone–backbone interaction dataset to an accuracy of 0.28 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Colorado Alternatively Powered Aircraft Airport Infrastructure Study

Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.

33 ADVANCED PROPULSION SYSTEMS↗

Crystal structure of Cu2Zn(GexSi1−x)Se4 solid solution: the kesterite to wurtz–kesterite structural phase transition

Developing low-cost, sustainable, and environmentally friendly top absorber layers for tandem solar cells is essential to advancing photovoltaic technologies and accelerating the transition to renewable energy. In this work, we explore the potential of tetravalent (Cu2Zn(GexSi1−x)Se4) cation mutations in chalcogenide compound semiconductors with the aim of finding a material with increased band gap and reduced structural disorder. A combination of high-resolution synchrotron powder diffraction and neutron powder diffraction was used to determine the atomic positions and monoclinic angles in monoclinic wurtz–kesterite type Cu2Zn(GexSi1−x)Se4 mixed crystals as well as to determine the cation distribution in the crystal structure of Ge-rich kesterite-type and Si-rich wurtz–kesterite type mixed crystals. These investigations enabled us to deduce the structural transition scenario within the Cu2Zn(GexSi1−x)Se4 series. The transition occurs via a region where two phases with different crystal structures, tetragonal and monoclinic and thus a different distortion of the coordination tetrahedra, but the same cation distribution within the element specific cation sites co-exist. Thus, the structural transition between the kesterite and the wurtz–kesterite structure within the Cu2Zn(GexSi1−x)Se4 series is a distortion driven transition. The study identifies cation mutation in quaternary chalcogenides as a promising strategy beyond chalcopyrites and kesterites for low cost and environmentally friendly top absorbers in tandem solar cells.

Gurieva, Galina [Helmholtz Center Berlin for Mater↗