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At least 163 records · Page 9

Numerical investigation of microbial quorum sensing under various flow conditions

Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.

59 BASIC BIOLOGICAL SCIENCES↗

Incorporation of Membrane Proteins Into Bicontinuous Microemulsions Through Winsor‐III System‐Based Extraction

Abstract The membrane proteins (MP) α‐synuclein (ASYN) and bacteriorhodopsin (BR) were readily incorporated into bicontinuous microemulsions (BμEs) formed by two microemulsion systems: water/heptane/Aerosol‐OT (AOT)/CK‐2,13 and water/dodecane/sodium dodecyl sulfate (SDS)/1‐pentanol. (CK‐2,13 is an alkyl ethoxylate possessing two alkyl tail groups of carbon chain length 2 and 13 and an average degree of ethoxylation of 5.6.) MP were encapsulated in BμEs through preparation of Winsor‐III systems at optimal salinity, with the anionic surfactants AOT and SDS providing the driving force for extraction. Dissolution of ASYN in BμEs greatly increased the former's α‐helicity, similar to ASYN's behavior in the presence of biomembranes, while BμE‐ and vesicle‐encapsulated BR possessed similar secondary structure. Small‐angle neutron scattering (SANS) results clearly demonstrated the direct interaction of MP with the surfactants, resulting in a decrease of surface area per volume for surfactant monolayers due to decreased surfactant efficiency. The SANS signal for ASYN was isolated through the use of neutron contrast matching for the surfactants through partial deuteration of water and oil, one of the first reports of contrast matching for BμEs in the literature. The SANS results of the contrast‐matched sample reflected similar aggregation for ASYN in BμEs as was reported previously for vesicles and SDS solution. This study demonstrates the potential use of BμEs as MP host systems for conducting biochemical reactions such as the conversion of sunlight into adenosine triphosphate by BR and studying the fundamental behavior of MP, such as the role of ASYN dysfunction in Parkinson's disease, as well as for isolation and purification of MP via Winsor‐III‐based extraction.

Hayes, Douglas G.↗

A Multi-Branch Decoder Network Approach to Adaptive Temporal Data Selection and Reconstruction for Big Scientific Simulation Data

A key challenge in scientific simulation is that the simulation outputs often require intensive I/O and storage space to store the results for effective post hoc analysis. This article focuses on a quality-aware adaptive temporal data selection and reconstruction problem where the goal is to adaptively select simulation data samples at certain key timesteps in situ and reconstruct the discarded samples with quality assurance during post hoc analysis. This problem is motivated by the limitation of current solutions that a significant amount of simulation data samples are either discarded or aggregated during the sampling process, leading to inaccurate modeling of the simulated phenomena. Two unique challenges exist: 1) the sampling decisions have to be made in situ and adapted to the dynamics of the complex scientific simulation data; 2) the reconstruction error must be strictly bounded to meet the application requirement. To address the above challenges, we develop DeepSample , an error-controlled convolutional neural network framework, that jointly integrates a set of coherent multi-branch deep decoders to effectively reconstruct the simulation data with rigorous quality assurance. The results on two real-world scientific simulation applications show that DeepSample significantly outperforms other state-of-the-art methods on both sampling efficiency and reconstructed simulation data quality.

Zhang, Yang↗

Structure of Complex Liquid–Liquid Extraction Organic Phases for Rare Earth Separations

Complex, multicomponent liquids with hierarchical structure and phase transitions are encountered in many natural and industrial processes, including in chemical separations. One notable example is aggregation and organic phase splitting in liquid–liquid extraction (LLE) of metal ions. While these two phenomena that have long been closely associated, a mechanistic link between mesoscale structure and the capacity-limiting organic phase splitting remains elusive due to complexity of these systems. Here, in this study, we combine small-angle X-ray scattering (SAXS), X-ray photon correlation spectroscopy (XPCS), and molecular dynamics simulation to reveal a comprehensive picture of structure at the nano- and mesoscale in these complex solutions. For the representative case of rare earth extraction from an acidic aqueous phase by a malonamide extractant in dodecane, we investigate a wide range of process-relevant extractant and acid concentrations to provide a complete picture of how aggregation depends on composition. We decompose organic phase structure from SAXS into two contributions, which together can capture the scattering at all compositions: composition fluctuations described by the Ornstein–Zernike equation at low wavenumber Q, and nanostructure modeled by a “pre-peak” at intermediate Q. The former contains information about the thermodynamics of demixing, while the latter reflects nanoscopic self-assembly of the extractant and extracted solutes. While fluctuations have typically not been considered in the literature, we find they in fact dominate the total structure for nearly all practical conditions. As only the fluctuations have a strong temperature response, we confirm this attribution with temperature-dependent SAXS measurements, including for extracted europium nitrate complexes. SAXS and XPCS measurements near the critical point find static and dynamic scaling consistent with theory. Overall, this new paradigm for understanding LLE organic phases connects composition, nanoscale, and mesoscale structuring to phase behavior, providing both a comprehensive picture of solution structure and a quantitative link between aggregation and third phase formation.

Peroutka, Allison A. [Argonne National Laboratory ↗

Heat accelerates degradation of β -lactoglobulin fibrils at neutral pH

Fibrous aggregates of β-lactoglobulin display superior mechanical and interfacial properties compared to the native protein. These properties directly link to the protein morphology and structure. When incorporated into food matrices, during processing protein fibrils are exposed to pH shifts and high temperature conditions, which accelerate their degradation. In the present study, neutralized β-lactoglobulin fibrils were heated at 100 °C and 121 °C for various times to assess their degradation. Fibril morphology, structure, and viscosity in solution were examined by microscopy, scattering, spectroscopy, and rheology. Atomic force microscopy showed the contour length of the protein fibrils decreased gradually with heating at 100 °C and 121 °C, with greater decreases at 121 °C. Increased fibril diameters (~15–25 nm) were observed at 121 °C for 5–15 min heating and were disrupted upon further heating. Small-angle x-ray scattering indicated an increase in fibril radius with heating at pH 7 followed by a decrease at prolonged heating, whereas fibril length decreased continuously with heating. Thioflavin T fluorescence, circular dichroism and Fourier transform infrared spectroscopy confirmed the conversion of β-sheet to random coils as fibrils were degraded during thermal treatment at pH 7. Surface hydrophobicity of fibrils decreased with increase in heating temperature and time, coinciding with an increase in the content of non-aggregated proteins. Viscosity of fibril solutions increased when fibrils were heated at 100 °C, whereas at 121 °C their viscosity first increased and then decreased. Furthermore, these findings imply heating at 100 °C and 121 °C facilitates degradation and depolymerisation of β-lactoglobulin fibrils with aggregation as an intermediate step.

59 BASIC BIOLOGICAL SCIENCES↗

Distribution Feeder-Scale Fast Frequency Response via Optimal Coordination of Net-load Resources Part I: Solution Design

This work is the first of a two-part series that develops and experimentally demonstrates a first-of-its-kind hierarchical control solution for optimally dispatching thousands of deferrable loads and distributed energy resources (DERs) across a distribution feeder to provide fast frequency response (FFR) within 500 ms to the bulk power system. This approach rapidly coordinates resources online after a frequency event occurs, allowing fast-changing, behind-the-meter (BTM) resources to be incorporated and aggregate FFR power set points to be achieved more quickly and accurately than existing approaches. We also present a solution for determining the optimal amount of headroom to operate solar inverters with to minimize opportunity cost while ensuring the FFR response viability of a building with the inverter and deferrable loads. In Part I, we develop practical algorithms for fast, cost-based optimal dispatch at multiple aggregation scales (single building, multiple buildings, and full distribution feeder), establish their optimality, and demonstrate via simulation that they are faster than state-of-the-art, coordinated frequency response approaches. In Part II, the entire platform is implemented and experimentally verified using a unique power hardware-in-the-loop demonstration, including more than 100 powered loads and DERs connected to a real-world distribution network model and over 10,000 net-load resources dispatched.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Molecular Mechanisms Underlying Surfactant-Based Plastics De-Inking

Surfactant-mediated binder removal is critical for de-inking pretreatment in plastics recycling, yet the molecular mechanisms governing surfactant performance remain poorly understood. We used all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations alongside alkaline surfactant washing experiments to investigate interactions between a series of surfactants and a polyether urethane (PEU) binder in solution and on a polyethylene (PE) surface. Experiments reveal a range of de-inking efficiencies, ranging from <25 to >95% depending upon surfactant headgroup charge and tail length. AA simulations reveal that charged surfactants reach stable levels of surfactant coverage, while nonionic surfactants aggregate on the binder. CG umbrella sampling calculations quantify the thermodynamics of binder desorption in water. In ∼0.25 M surfactant solutions, up to a 52% reduction in the free energy barrier is computed, with trends in good agreement (R 2 = 0.92, Pearson’s r = –0.96, Spearman’s ρ = –0.83) with experimental de-inking efficiencies. We find that charged surfactants are more effective than nonionic surfactants for de-inking and propose three regimes of surfactant de-inking processes: good de-inking occurs in surfactants that promote PEU desorption with a low radius of gyration (R g ); moderate de-inking occurs when surfactants stabilize PEU but increase R g ; poor de-inking occurs in surfactants that aggregate on the binder and promote extensive anchoring to the surface. Overall, these molecular-level insights have the potential to guide the design of surfactant formulations for plastics recycling applications.

ink removal↗

Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions (FAST-DERMS)

This document provides system-level specifications for a federated architecture for secure and transactive distributed energy resource management solutions (FAST-DERMS), presents a solution, and describes operational concepts for the proposed solution. FAST-DERMS enables the provision of reliable, resilient, and secure transmission and distribution (T&D) grid services through the scalable aggregation and near-real-time management of utility-scale and small-scale distributed energy resources (DERs). We first present the principles and objectives of FAST-DERMS. Then, after discussing important system concepts, we present the specifications for FAST-DERMS and a solution that employs a distributed and federated control methodology in which the DERs connected to a single point of common coupling with the rest of the system, such as individual substations, are optimized coordinately to provide system-level grid services. FAST-DERMS aims to aggregate and coordinate the operations of DERs to support T&D grid operations. The key optimization and control component of this FAST-DERMS reference implementation is a flexible resource scheduler (FRS) that aggregates the DERs within a substation service area. These FRSs operate at the substation level and perform constrained economic dispatch of DERs, either directly or through a transactive market or aggregator, as shown in Figure ES-1. An FRS Coordinator at the distribution system operator (DSO) level aggregates distribution substations operated by FRSs and interfaces with the transmission system operator (TSO) to provide transmission services. FAST-DERMS also allows for the integration of the FRS Coordinator with an existing distribution utility management system that could be employed by the DSO to enhance distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

First-Principles study of interface capture of Ni during high-temperature oxidation of NiCr alloys

The formation of precipitated phases of less reactive metals within an oxide scale during alloy oxidation can disrupt its structural integrity, significantly compromising the protective function of the oxide. To better understand this phenomenon, it is crucial to investigate the atomic-level diffusion mechanisms that drive precipitate formation. In this study, we employ first-principles calculations to examine the diffusion and aggregation of Ni atoms across the NiCr/Cr 2 O 3 interface during the high-temperature oxidation of NiCr alloys. Our results reveal that, in the absence of Cr vacancies, Ni atoms predominantly remain within the NiCr substrate, with minimal migration toward the Cr 2 O 3 layer. However, when Cr vacancies are present at both the NiCr/Cr 2 O 3 interface and within the Cr 2 O 3 bulk, Ni atoms exhibit a strong propensity to migrate from the NiCr substrate into the Cr 2 O 3 bulk, where they aggregate into Ni-rich regions with a corundum structure. This study provides valuable atomic-level insights into the diffusion and aggregation of less-reactive metals at the alloy/oxide interface, enhancing our understanding of solute capture and its contribution to the degradation of oxidation resistance in alloys.

Chen, Jianmin [Xiangtan University (China)] (ORCID↗

Charge Delocalization and Vibronic Couplings in Quadrupolar Squaraine Dyes

Squaraines are prototypical quadrupolar charge-transfer chromophores that have recently attracted much attention as building blocks for solution-processed photovoltaics, fluorescent probes with large two-photon absorption cross sections, and aggregates with large circular dichroism. Their optical properties are often rationalized in terms of phenomenological essential state models, considering the coupling of two zwitterionic excited states to a neutral ground state. As a result, optical transitions to the lowest S 1 excited state are one-photon allowed, whereas the next higher S 2 state can only be accessed by two-photon transitions. A further implication of these models is a substantial reduction of vibronic coupling to the ubiquitous high-frequency vinyl-stretching modes of organic materials. Here, in this study, we combine time-resolved vibrational spectroscopy, two-dimensional electronic spectroscopy, and quantum-chemical simulations to test and rationalize these predictions for nonaggregated molecules. We find small Huang–Rhys factors below 0.01 for the high-frequency, 1500 cm –1 modes in particular, as well as a noticeable reduction for those of lower frequency modes in general for the electronic S 0 → S 1 transition. The two-photon allowed state S 2 is well separated energetically from S 1 and has weak vibronic signatures as well. Thus, the resulting pronounced concentration of the oscillator strength in a narrow region relevant to the lowest electronic transition makes squaraines and their aggregates exceptionally interesting for strong and ultrastrong coupling of excitons to localized light modes in external resonators with chiral properties that can largely be controlled by the molecular architecture.

36 MATERIALS SCIENCE↗

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗

Science-integrated Artificial-intelligence for Flooding and precipitation Extremes (SAFE)

A grand challenge in hydrologic science is to understand why signals of climate change and variability, which are often visible in precipitation extremes at aggregate scales, are not consistently observed in the case of extreme flooding. However, a solution to this challenge may prove elusive unless the water cycle is viewed in an integrative manner. Thus, for riverine flooding, while Hortonian (infiltration excess) runoff may have stronger correlation with precipitation extremes and hence perhaps to warming trends or climate oscillators, Dunne (saturation excess) runoff may have a more complex relationships with time series of precipitation and with evaporation and transpiration, but rain-on-snow and snowmelt events may depend on land-surface and atmospheric temperatures. Atmospheric rivers and tropical cyclones lead to precipitation or flooding and are impacted by climate. Flooding assessments need to consider long-term baselines, evolving risk factors, coupled natural-human systems, and novel adaptation such as nature-inspired design.

54 ENVIRONMENTAL SCIENCES↗

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

The U.S. Department of Energy (DOE) has launched a Connected Communities program that supports projects that expand DOE's network of grid-interactive, efficient building communities nationwide. As an early pilot of Connected Communities, the National Renewable Energy Laboratory (NREL) and its partners have developed and demonstrated a community-scale, hierarchical control solution to address the potential grid issues arising from high penetration of solar photovoltaics (PV) as well as to improve grid reliability and resilience in this residential community. A field pilot study has been performed at an affordable housing development called the Basalt Vista Community, which was built for school teachers and other professionals in the local workforce and represents an autonomous energy grid with all-electric, energy-efficient homes. With no natural gas line in the community, this is the first all-electric net-zero community in rural Colorado. In the field pilot study, NREL has validated the performance of the hierarchical control solution, which consists of NREL's foresee home energy management systems (HEMS) and community aggregators, in increasing demand flexibility and self-consuming PV, reducing potential over-voltages, and supporting critical loads during emergency events. In this presentation, we will present the methodology, simulation and field pilot results, and lessons learned from the project.

all-electric community↗

Application of Manufacturing Quality Management Principles to PV System Installations

To help SETO/DOE achieve its goals, the IBTS team proposed a project addressing system reliability by improving installation standards and quality management. The proposed approach was designed to help achieve measurable reductions in installation defect density and improvements in the performance of PV systems by optimizing design and installation of residential and commercial PV systems. This approach addressed the soft costs associated with installations and quality management. The project demonstrated improved system reliability and reduced PV system installation costs. The software developed improved operations, decreased risk, and increased the overall value of PV systems across their lifecycle. The project used several data collection methods, including extensive industry surveys, face-to-face high-level interviews at industry conferences, stakeholder teleconferences, and in-depth interviews conducted by IBTS staff. Results from the research found the industry needs a uniform assessment method for national providers to be more efficient; the software should support both code officials and installers; most industry stakeholders would find value in a centralized software system that allows them to collect, report, and review information on in-process and completed solar installations; and mobile solutions that bridge existing knowledge gaps with inspectors and integrate with existing methodologies (such as permitting software) are of great value. The software solution developed is web-based, allowing for national access, and is built on a Google Firebase platform that can handle significant users and data. It can be used onsite or remotely, allowing for code compliance to continue despite ongoing pandemic related delays or shutdowns for local economies. The information provided by the software tool allows users to uniformly assess a system for compliance and use that aggregated data to identify training topics or create internal process designed to improving issues and reducing occurrence. This solution has multiple benefits in managing quality at time of use and promoting an increase in future safety and quality through education. Perhaps most importantly, this software increases public safety by ensuring compliance of installed systems and allows for local AHJs to remotely engage specialized and qualified solar specific expertise for oversite of the installation in their jurisdictions. Data analysis provides the quality feedback loop identifying the root cause of failure and drives installation practices to improve through training and education, resulting in systems with higher performance, greater reliability, and reduced operations and maintenance costs. With the successful completion of this project, the industry can expect reduced soft costs and increased performance and safety and will ultimately benefit from longer performing systems that cost less to operate.

14 SOLAR ENERGY↗

Adsorption and Catalytic Activity of Gold Nanoparticles in Mesoporous Silica: Effect of Pore Size and Dispersion Salinity

The assembled state of nanoparticles (NPs) within porous matrices plays a governing role in directing their biological, electronic, and catalytic properties. However, the effects of the spatial confinement and environmental factors, such as salinity, on the NP assemblies within the pores are poorly understood. In this study, we use adsorption isotherms, spectrophotometry, and small-angle neutron scattering to develop a better understanding of the effect of spatial confinement on the assembled state and catalytic performance of gold (Au) NPs in propylamine-functionalized SBA-15 and MCM-41 mesoporous silica materials (mSiO 2 ). We carry out a detailed investigation of the effect of pore diameter and ionic strength on the packing and spatial distribution of AuNPs within mSiO 2 to get a comprehensive insight into the structure, functioning, and activity of these NPs. We demonstrate the ability of the adsorbed AuNPs to withstand aggregation under high salinity conditions. We attribute the observed preservation of the adsorbed state of AuNPs to the strong electrostatic attraction between oppositely charged pore walls and AuNPs. The preservation of the structure allows the AuNPs to retain their catalytic activity for a model reaction in high salinity aqueous solution, here, the reduction of p-nitrophenol to p-aminophenol, which otherwise is significantly diminished due to bulk aggregation of the AuNPs. This fundamental study demonstrates the critical role of confinement and dispersion salinity on the adsorption and catalytic performance of NPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of γ-Irradiation, Cation Size, and Salt Concentration on the Aggregation of Boehmite Nanoplatelets

The effects of radiation on the aggregation of nanoplatelets of aluminum oxyhydroxide (boehmite) in slurries of M 1+ cation nitrates has been observed using tumbler small- and ultra-small-angle neutron scattering. Nitrate solutions of H, Li, Na, K, and Rb at concentrations of 10 -5 , 10 -3 , 10 -1 , 2, and 4 molal were compared to the results for pure H 2 O. Primary aggregates consisting of small stacks of boehmite platelets that form immediately after the boehmite is placed in water are smaller for irradiated boehmite than the pristine material. Here, the primary aggregates for irradiated boehmite also appear to have a rougher surface than those observed for unirradiated materials. Both results are possibly due to breaking of the surface OH species and a neutralization of the surface. At low salt concentrations, the pH of the irradiated boehmite slurries is lower than that of the corresponding pristine material indicating that irradiated boehmite adsorbs fewer protons or more hydroxide onto its surface than the pristine boehmite. Increasing the salt concentration decreases the pH to near neutral at 7 due to screening of the electric double layer at the solid/liquid interface. Irradiation does not seem to affect the size of secondary aggregates formed from the aggregation of primary aggregates or of the overall size of the primary aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling thermal energy storage in structural cementitious composites with a novel phase change material microcapsule featuring an inorganic shell and a bio-inspired silica coating

Phase change material (PCM) microcapsules offer a promising approach for integrating PCM into building materials for efficient thermal energy storage. Here, this study presents the development of a novel PCM microcapsule specifically designed for incorporation into cementitious materials. The microcapsule consists of a low-cost PCM core derived from vegetable oil by-products and a durable inorganic shell made from cenosphere, a hollow fly ash generated from coal burning power plants. A novel process is developed to apply a silica coating to these cenosphere-based PCM microcapsules (CPCM), resulting in bioinspired-silica-coated CPCM microcapsules (BCPCM). This coating process draws inspiration from marine microorganism-based silica production and utilizes low-cost sodium silicate as a precursor, enabling eco-friendly and cost-effective manufacturing at ambient temperature and mild pH conditions. The morphology, chemical stability, and thermal properties of the BCPCM along with its thermo-mechanical performance in cementitious composites were comprehensively analyzed. Experimental results demonstrate successful silica deposition on BCPCM, leading to enhanced latent heat properties of the produced BCPCM. With the silica coating, BCPCM exhibits a 50 °C delay in thermal decomposition compared to CPCM, enhancing fire resistance and preventing premature PCM leakage of the microcapsule. The bioinspired silica coating effectively restores over 10% of the strength loss for each percent increase in CPCM incorporated into the mortar. The thermal performance experiments reveal that increasing the BCPCM content reduces temperature peaks and rates of temperature increase, indicating an improved capacity for thermal energy storage. This new PCM microcapsule provides a cost-effective solution to integrate thermal energy storage to cementitious material, as evidenced that over 30% of aggregates (in volume) can be replaced by the microcapsule without a drastic loss of strength.

25 ENERGY STORAGE↗

Freeze-induced crystallization: An overlooked pathway for mineral genesis in natural waters

Natural ice plays salient roles in making the Earth habitable and sustainable. Previously overlooked, its role in chemical processes is now of emerging interest, particularly due to the freeze concentration effect, which can substantially promote chemical reactions during ice formation. We demonstrate here that ice formation can serve as a dynamic and unique pathway for mineral genesis. Freezing solutions containing dissolved manganese and carbonates produced rhodochrosite (Mn II CO 3 ) even under slightly undersaturated conditions. At room temperature, by contrast, this occurred when the solution saturation level was increased by ca. 30,000 times. The cryogenic rhodochrosite formed spherical aggregates of nano-polycrystallites, distinctly different from the cubic monocrystalline particles observed at room temperature. The distinct feature likely resulted from the combined effects of the intensified supersaturation induced by the freeze concentration effect and the low temperatures within liquid-like layers, conditions that make liquid-like layers an exceptional environment for mineral genesis, unlike typical natural water systems. The cryogenic rhodochrosite formation was successfully demonstrated using in situ, real-time X-ray absorption spectroscopy (XAS), enabling direct observation of freeze-induced solid formation. In conclusion, our findings reveal that freeze-induced crystallization may be an active mineralization pathway, potentially influencing elemental cycles within the cryosphere and contributing to minerals with distinguishing properties and reactivities in the environment.

Earth, Atmospheric, and Planetary Sciences↗