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DOE OSTI2023

A dataset of cyber-induced mechanical faults on buildings with network and buildings data

We have collected data of cyber-induced mechanical faults on buildings using a simulation platform. A DOE reference building model was used for running the simulation under a Rogue device attack and collected the network data as well as the physical buildings data to better understand the impacts of cyber attacks on the building and help identify the source of the mechanical fault with the network data. Alfalfa is the tool used for simulating the DOE reference buildings and acts as an interface to the model for querying the status and providing input externally. The Building Automation System (BAS) is the centralized controller providing control commands to other BACnet devices on the network based on the building status received from Alfalfa. The BACnet devices like damper will listen for the control commands from BAS on the BACnet network and implement it. The attacker is the malicious actor on the network creating disruptions by placing cyber-attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Higher-order phonon scattering: advancing the quantum theory of phonon linewidth, thermal conductivity and thermal radiative properties

Phonon scattering plays a central role in the quantum theory of phonon linewidth, which in turn governs important properties including infrared spectra, Raman spectra, lattice thermal conductivity, thermal radiative properties, and also signifi- cantly affects other important processes such as hot electron relaxation. Since Maradudin and Fein’s classic work in 1962, three-phonon scattering had been considered as the dominant intrinsic phonon scattering mechanism and has seen tremendous advances. However, the role of the higher-order four-phonon scattering had been persistently unclear and so was ignored. The tremendous complexity of the formalism and computational challenges stood in the way, prohibiting the direct and quantitative treatment of four-phonon scattering. In 2016, a rigorous four-phonon scattering formalism was developed, and the prediction was realized using empirical potentials. In 2017, the method was extended using first-principles calculated force constants, and the thermal conductivities of boron arsenides (BAs), Si and diamond were predicted. The predictions for BAs were later confirmed by several independent experiments. Four-phonon scattering has since been investigated in a range of materials and established as an important intrinsic scattering mechanism for thermal transport and radiative properties. Specifically, four-phonon scattering is important when the fourth-order scattering potential or phase space becomes relatively large. The former scenario includes: (i) nearly all materials when the temperature is high; (ii) strongly anharmonic (low thermal conductivity) materials, including most rocksalt compounds, halides, hydrides, chalcogenides and oxides. The latter scenario includes: (iii) materials with large acoustic–optical phonon band gaps, such as XY compounds with a large atomic mass ratio between X and Y; (iv) two- dimensional materials with reflection symmetry, such as single-layer graphene, single-layer boron nitride and carbon nanotubes; and (v) phonons with a large density of states, such as optical phonons, which are important for Raman, infrared and thermal radiative properties. Four-phonon scattering is expected to gain broad interest in various technologically important materials for thermoelectrics, thermal barrier coatings, thermal energy storage, phase change, nuclear power, ultra-high temperature ceramics, infrared spectra, Raman spectra, radiative transport, hot electron relaxation and radiative cooling. Four-phonon scattering has been, and will continue to be, established as an important intrinsic phonon scattering mechanism beyond three-phonon scattering. The prediction of four-phonon scattering will transition from a breakthrough to a new routine in the next decade.

Feng, Tianli↗

DOE OSTI2020

Putting Our Industry's Data to Work: A Case Study of Large-Scale Data Aggregation: Preprint

With increasing deployment of Advanced Metering Infrastructure (AMI), Building Automation System (BAS) controls, Internet of Things (IoT) network devices, and data-driven evaluation, measurement, and verification studies, the building sector is currently generating a staggering amount of energy-related data. In the right hands, these data sets can contribute to increased comfort and energy savings for building occupants and a more reliable electrical grid; however, due to a combination of factors, including significant privacy concerns, much of the data that are presently generated and stored are not used outside of basic operational applications. In the past year, our team has dedicated over 2,000 person-hours to accessing building energy data for a project funded by the U.S. Department of Energy (DOE) Building Technologies Office. We sought whole-building or end-use (e.g., lighting) timeseries data at the individual-building or equipment level where possible or aggregated information, such as timeseries averages and quartiles by building type (e.g., office, retail, hospital), where sharing individual building information was not an option. We are additionally working with IoT and BAS data sets to derive information important to the project. We have assembled an extensive data set that will enable the development of publicly available end-use load profiles to benefit the U.S. building and electricity industries. Here we present an overview of the data set that we have assembled to date, the motivators and approaches that got us here, and the lessons we learned through our efforts. We also discuss work underway that presents additional options for future data access.

building energy data↗

DOE OSTI2024

Breaking Barriers in Chalcogenide Perovskite Synthesis: A Generalized Framework for Fabrication of BaMS 3 (M═Ti, Zr, Hf) Materials

Abstract Chalcogenide perovskites have garnered increasing attention as stable, non‐toxic alternatives to lead halide perovskites. However, their conventional synthesis at high temperatures (>1000 °C) has hindered widespread adoption. Recent studies have developed low‐to‐moderate temperature synthesis methods (<600 °C) using reactive precursors, yet a comprehensive understanding of the pivotal factors affecting reproducibility and repeatability remains elusive. This study delineates the critical factors in the low‐temperature synthesis of BaMS 3 (M═Zr, Hf, Ti) compounds and presents a generalized framework. Innovative approaches are developed for synthesizing BaMS 3 compounds using this framework involving organometallics for solution deposition. The molecular precursor routes, employing metal acetylacetonates to generate soluble metal–sulfur bonded complexes and metal–organic compounds to produce soluble metal‐thiolate, metal‐isothiocyanate, and metal‐trithiocarbonate species, are demonstrated to yield carbon‐free BaMS 3 . These methods have achieved the most contiguous films of BaZrS 3 and BaHfS 3 using solution deposition to date. Furthermore, a hybrid solution processing method involving stacking sputter‐deposited Zr and solution‐deposited BaS layers is employed to synthesize a contiguous, oxygen‐free BaZrS 3 film. The diffuse reflectance measurements indicate a direct bandgap of ≈ 1.85 eV for the BaZrS 3 films and ≈ 2.1 eV for the BaHfS 3 film under investigation.

25 ENERGY STORAGE↗

DOE OSTI2020

Energy cost savings and expected payback for Re-tuning the controls of US Army buildings

The Headquarters Department of the Army (HQDA) sponsored a study to determine the national impact of deploying the Re-tuning™ methodology in 5 buildings types that account for over 40% of the Army’s conditioned building stock. Re-tuning is a systematic process that improves operational efficiency and reduces energy consumption at no- or low-cost through the building automation system (BAS) by correcting operational problems that plague buildings. The study relied on successful demonstration of the re-tuning methodology at 4 pilot US Army installations that informed a holistic effort that included simulating 12 individual re-tuning energy efficiency measures (EEMs) and 6 packages of EEMs in 5 selected Army building prototype models that represent 311 million ft2 (28.9 million m2) of the Army’s conditioned floor space. Both the baseline buildings and the packages were customized to capture the expected outcomes of re-tuning a diverse set of buildings. The study highlighted the benefit of individual re-tuning EEMs and economics of implementing packages of EEMs in applicable Army buildings across 16 climates and 2 building vintages. The average whole-building energy savings ranged from 10.8% to 40.5% by building type, with the company operations facility (COF) building having the highest value proposition from re-tuning. In addition, the study reveals that all large office (LO) buildings in the Army are economical to re-tune. The total modeled cost savings potential for re-tuning the five building types across the US Army is $204/1,000 sf ($220/100 m2), or $64M annually. This cost savings represents 5.6% of all the Army’s energy expenditures.

Fernandez, Nicholas EP↗

DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗

DOE OSTI2022

From fault-detection to automated fault correction: A field study

A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Finally, technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Investigating the Role of Acid Sites in the Hydrocracking of Polyethylene-EVOH Multilayer Film Waste over Pt/BEA Catalyst

Multilayer polymer films (MFs) containing poly(ethylene-co-vinyl alcohol) (EVOH) and polyolefins are ubiquitous in single-use food and medical packaging. MFs are currently landfilled or incinerated rather than mechanically recycled because of the processing difficulties associated with their form factor and complex multicomponent structures. Advanced chemical recycling is a promising solution. Prior reports have explored hydrogenolysis and hydrodeoxygenation to convert EVOH, but these technologies are limited by catalyst deactivation and slow apparent kinetics, respectively. Alternatively, in this work, we demonstrate the efficient hydrocracking of commercial MFs into naphtha range (C5-C12) alkanes over platinum (Pt) supported on acidic zeolites. Mixtures of low-density polyethylene (LDPE) and EVOH are utilized as MF surrogates to gain fundamental insights. Pt deposited on BEA supports with varying Lewis acid site (LAS) concentrations are synthesized and tested for hydrocracking. Surprisingly, Pt/BEA with high LAS concentrations demonstrate improved activity for LPDE/EVOH blends over LDPE alone. In contrast, LAS concentrations are shown to have no influence on LDPE hydrocracking. LAS and Brønsted acid sites (BAS) catalyze the dehydration of EVOH to form water, which improves LDPE hydrocracking. Polyaromatics formed primarily via EVOH thermal degradation lead to detrimental coke formation, which hinders hydrocracking activity. Reaction conditions and feed ratios of LDPE and EVOH are tuned to balance these competing effects. Reusability tests demonstrate that Pt/BEA maintains high activity (81% conversion in 2 h) and high selectivity towards naphtha (78%) over multiple reuse cycles. Furthermore, these findings position hydrocracking as a promising technology for the circularity of complex MF plastic waste.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Designing transparent conductors using forbidden optical transitions

Many semiconductors present weak or forbidden transitions at their fundamental band gaps, inducing a widened region of transparency. This occurs in high-performing n-type transparent conductors (TCs) such as Sn-doped In 2 O 3 (ITO); however, thus far, the presence of forbidden transitions has been neglected in the search for new p-type TCs. To address this, we first compute high-throughput absorption spectra across ~18, 000 semiconductors, showing that over half exhibit forbidden or weak optical transitions at their band edges. Next, we demonstrate that compounds with highly localized band-edge states are more likely to present forbidden transitions. Lastly, we search this set for p-type and n-type TCs with forbidden transitions and, by performing defect calculations, propose unexplored TC candidates such as ambipolar BeSiP 2 , p-type wurtzite BAs, and n-type Ba 2 InGaO 5 , among others. In conclusion, we share our dataset and recommend that future screenings for optical properties consider the impact of forbidden transitions.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Porous Cu 2 BaSn(S,Se) 4 Film as a Photocathode Using Non-Toxic Solvent and a Ball-Milling Approach

Cu 2 BaSn(S,Se) 4 (CBTSSe) has been proposed as an alternative to Cu 2 ZnSn(S,Se) 4 (CZTSSe) for solar absorbers due to its reduced propensity for antisite disorder and band tailing, while maintaining the desirable characteristics of band gap tunability, earth-abundance, and low toxicity constituent metals. However, current film deposition methods require high-vacuum conditions or toxic solvents, less desirable features for prospective large-scale production. Here, ball milling is demonstrated as a route towards a scalable processing method for CBTSSe, using a precursor ink consisting of common elements Cu 2 S, BaS, Sn, and S in low-toxicity ethanol. A final film with a thickness and average grain size on the order of 1 µm was synthesized with a band gap of 1.56 eV, corresponding to a Cu 2 BaSnS 4-x Se x (x ≈ 3) stoichiometry. A porous CBTSSe photocathode with Pt/TiO 2 /CdS overlayers was fabricated to demonstrate the photocurrent-generating capabilities of the film, yielding current densities of as high as 5.54 mA/cm 2 at 0 V versus a reversible hydrogen electrode (V/RHE) .

14 SOLAR ENERGY↗

DOE OSTI2021

Chemical Kinetics of the Autoxidation of Poly(ethylenimine) in CO 2 Sorbents

The oxidative degradation rates of a CO 2 sorbent composed of a mesoporous alumina impregnated with poly- (ethylenimine) (PEI) are measured under systematically varied conditions and a reaction rate law is created. Good agreement is shown between the rate of oxidation obtained via in situ calorimetric heat measurement during oxidative degradation reactions and the loss of CO 2 capture performance presented as amine efficiency (mol CO 2 /mol amine). PEI mass loss and elemental composition are tracked over the course of the reaction and used in conjunction with the oxidation rate measurements to shed insight into the oxidation reaction(s). These data, in combination with measurements of the heat of reaction, suggest a common reaction set across the range of temperatures, oxygen concentrations, and sorbent compositions tested. The data are consistent with the basic autoxidation scheme (BAS), the accepted mechanism of autoxidation of aliphatic polymers. We propose a lumped kinetic model to describe the oxidation reaction set and estimate an activation energy of 105 kJ/mol and an oxygen reaction order of 0.5–0.7 from the data accordingly. Furthermore, these parameters can be incorporated into process cycle models to estimate the material lifetime, a critical uncertainty in the deployment of DAC technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Ga + -Chabazite Zeolite: A Highly Selective Catalyst for Nonoxidative Propane Dehydrogenation

Ga-chabazite zeolites (Ga-CHA) have been found to efficiently catalyze propane dehydrogenation with high propylene selectivity (96%). In situ FTIR spectroscopy and pulse titrations are employed to determine that upon reduction, surface Ga 2 O 3 is reduced and diffuses into the zeolite pores, displacing the Brønsted acid sites (BAS) and forming extra-framework Ga + sites. This isolated Ga + site reacts reversibly with H 2 to form GaHx (2034 cm -1 ) with an enthalpy of formation of ~ -51.2 kJ·mol -1 , a result supported by Density functional theory (DFT) calculations. The initial C 3 H 6 dehydrogenation rates decrease rapidly (40%) during the first 100 min and then decline slowly afterward, while the C 3 H 6 selectivity is stable at ~ 96%. The reduction in the reaction rate is correlated with the formation of polycyclic aromatics inside the zeolite (using UV-vis spectroscopy) indicating that the accumulation of polycyclic aromatics is the main cause of the deactivation. The carbon species formed can be easily oxidized at 600 °C with complete recovery of the PDH catalytic properties. The correlations between GaH x vs. Ga/Al ratio, and PDH rates vs. Ga/Al ratio show that extra-framework Ga + is the active center catalyzing propane dehydrogenation. The higher reaction rate on Ga + than In + in CHA zeolites, by a factor of 43, is the result of differences in the stabilization of the transition state due to the higher stability of Ga 3+ vs. In 3+ . The uniformity of the Ga + sites in this material makes it an excellent model for the molecular understanding of metal cation exchanged hydrocarbon interactions in zeolites.

10 SYNTHETIC FUELS↗

DOE OSTI2022

The influence of alloying on slip intermittency and the implications for dwell fatigue in titanium

Dwell fatigue, the reduction in fatigue life experienced by titanium alloys due to holds at stresses as low as 60% of yield, has been implicated in several uncontained jet engine failures. Dislocation slip has long been observed to be an intermittent, scale-bridging phenomenon, similar to that seen in earthquakes but at the nanoscale, leading to the speculation that large stress bursts might promote the initial opening of a crack. Here we observe such stress bursts at the scale of individual grains in situ, using high energy X-ray diffraction microscopy in Ti–7Al–O alloys. This shows that the detrimental effect of precipitation of ordered Ti 3 Al is to increase the magnitude of rare pri $\langle$a$\rangle$ and bas $\langle$a$\rangle$ slip bursts associated with slip localisation. By contrast, the addition of trace O interstitials is beneficial, reducing the magnitude of slip bursts and promoting a higher frequency of smaller events. This is further evidence that the formation of long paths for easy basal plane slip localisation should be avoided when engineering titanium alloys against dwell fatigue.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗

DOE OSTI2024

Proton and neutron density distributions at supranormal density in low- and medium-energy heavy-ion collisions. II. Central Pb + Pb collisions

This paper represents a continuation of our investigation into the limitations on total, proton, and neutron particle number densities, as well as the asymmetry of proton and neutron density distributions achievable in central heavy-ion collisions. We explore these aspects at low and medium energies within the framework of the Boltzmann-Uhlenbeck-Uehling (pBUU) transport and time-dependent Hartree-Fock (TDHF) models. Previous studies, focusing on symmetric and asymmetric collisions of Ca and Sn nuclei [1], and initial results on Pb-nuclei collisions [2], emphasized the role of the Coulomb interaction in these events. Our findings indicated that: (i) the highest total densities predicted at 𝐸 beam = 800 MeV/nucleon were on the order of ≈ 2.5⁢𝜌 0 (𝜌 0 = 0.16 fm −3 ), (ii) the proton-neutron asymmetry for maximal densities, 𝛿=(𝜌$^{max}_{n}$− 𝜌$^{max}_{p}$)/(𝜌$^{max}_{n}$+𝜌$^{max}_{p}$), did not generally exceed the asymmetry in the initial state of the collision at all beam energies and tended to decrease during the reaction, and (iii) a significant portion of this asymmetry had its microscopic origin in Coulomb forces, masking the pure nuclear contribution. These new findings, particularly relevant in the astrophysical context, are further examined in this work, focusing on the heaviest target-projectile combination 212,208 Pb accessible in an experiment. We introduce the SkT3 Skyrme force model, not previously used for the Pb system, and compare it to the SV-bas and SV-sym34 models to explore the symmetry-energy dependence of the results. Contour plots of nucleonic densities are presented, contrasting the time evolution of the density distributions in low (TDHF) and high (pBUU) models. We also present the evolution of normalized maximal proton, neutron, and total nucleon number density with increasing beam energy in the full pBUU model and the Vlasov approximation, aiming to explore the impact of correlations in the reaction. The time evolution of the proton and neutron density distributions in the plane transverse to the beam direction is illustrated at both low and high beam energy. In conclusion, our detailed examination of the Pb system in this work provides further essential evidence that the aforementioned findings (i)–(iii) are only weakly dependent on system size and a symmetry-energy model, and thus, they are of more general importance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

BrickQA: Bridging the Semantic Gap in Building Operations with Dynamic Graph Exploration

While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher token cost-efficiency. Beyond these metrics, the framework maintains structural fidelity across heterogeneous buildings and remains resilient to ambiguous queries without requiring site-specific fine-tuning. Furthermore, a case study on operational analytics validates the framework’s capability to handle temporal and aggregation constraints, effectively transforming abstract semantic models into actionable facility management insights.1

Ko, Yun-Dam↗

DOE OSTI2022

Electrochemical Separation of Ag 2 S and Cu 2 S from Molten Sulfide Electrolyte

The production of precious metals from Cu-rich sources such as ore products or secondary sources is slow and complex largely due to limited solubility in aqueous electrolytes. This results in sequential processing with various electrolytes and chemistries, where first Cu is electrorefined, followed by Ag, followed by Au and the platinum group metals. These are separate processes, often conducted in separate electrorefining and electrowinning facilities. The chemical properties of molten sulfides, and their ability to operate at a temperature where liquid metal cathodes are used, suggest the possibility of an alternative, streamlined processing route for Cu and precious metals. Unfortunately, little thermodynamic or electrochemical information is available regarding the behavior of Cu and precious metal sulfides in molten sulfide electrolytes. Herein, the relative activity of the Cu 2 S-Ag 2 S pseudobinary dissolved in a BaS-La 2 S 3 supporting electrolyte is measured at 1523 K. It was found that the supporting electrolyte favors mixing with Ag 2 S over Cu 2 S. Molten sulfide electrolysis of Cu and Ag was conducted, with results in good agreement with the thermodynamic model. It is found that the Ag-Cu cathode chemistry will influence the electrochemical selectivity in the Ag-Cu-Ba-La-S system.

25 ENERGY STORAGE↗