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DOE OSTI2021

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Elevating the Practical Application of Sodium-Ion Batteries through Advanced Characterization Studies on Cathodes

Sodium-ion batteries (SIBs) have emerged as promising alternatives to their lithium-ion counterparts due to the abundance of sodium resources and their potential for cost-effective energy storage solutions. The chemistry for SIBs has been investigated since the 1980s, but it went through a slow research and development process. Recently, there has been an acceleration in technology maturation due to a supply chain crisis originating from unequal resource distribution and sustainability and safety concerns regarding lithium-ion batteries. However, the practical application of SIBs has been hindered primarily by challenges related to cathode materials, specifically, surface and structural stabilities in different conditions. Through the integration of advanced techniques such as in situ spectroscopy, operando diffraction, and high-resolution microscopy, a comprehensive understanding of the cathode’s dynamic behavior and degradation mechanisms can be achieved. The identified structural modifications, phase transitions, and degradation pathways offer critical insights into the design of robust cathode materials with prolonged cycling stability, fast charging capability, high energy density, great low-temperature performance, and safety. This review underscores the pivotal role of cutting-edge characterization techniques in guiding the development of high-performance sodium-ion batteries, thereby fostering the realization of sustainable and efficient energy storage solutions for diverse technological applications.

25 ENERGY STORAGE↗

DOE OSTI2021

Secure LoRa Firmware Update with Adaptive Data Rate Techniques

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

What's on the Surface? Physics and Chemistry of Delta-Doped Surfaces

Outline of presentation: 1. Detector surfaces and the problem of stability 2. Delta-doped detectors 3. Physics of Delta-doped Silicon 4. Chemistry of the Si-SiO2 Interface 5. Physics and Chemistry of Delta-doped Surfaces a. Compensation b. Inversion c. Quantum exclusion. Conclusions: 1. Quantum confinement of electrons and holes dominates the behavior of delta-doped surfaces. 2. Stability of delta-doped detectors: Delta-layer creates an approx 1 eV tunnel barrier between bulk and surface. 3. At high surface charge densities, Tamm-Shockley states form at the surface. 4. Surface passivation by quantum exclusion: Near-surface delta-layer suppresses T-S trapping of minority carriers. 5. The Si-SiO2 interface compensates the surface 6. For delta-layers at intermediate depth, surface inversion layer forms 7. Density of Si-SiO2 interface charge can be extremely high (>10(exp 14)/sq cm)

detectors↗

NASA NTRSDate not supplied

Systems Health Management and Decision Making

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Discuss research approach to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms. Note - This presentation is for the short workshop conducted at the same conference and contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS2018

Systems Health Monitoring and Prognostics Using Model Based Approach

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms.

Electronics Prognostics↗

DOE OSTI2024

Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0

The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual’s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.

Lazarus, Jessica↗

DOE OSTI2025

Long-Lived Charge-Transfer Excitons in a Graphene–PTCDI–TiOPc Trilayer Heterostructure

Excitation transfer across the interfaces between graphene, perylenetetracarboxylic diimide (PTCDI), and titanyl phthalocyanine (TiOPc) was studied by using transient absorption and photoluminescence spectroscopy. Both photoluminescence quenching and transient absorption measurements confirm the presence of a type-II interface between PTCDI and TiOPc. While the graphene/PTCDI interface is expected to exhibit type-I behavior, transient absorption measurements indicate that only electrons transfer from PTCDI to graphene, with no evidence of hole transfer. Density functional theory calculations reveal significant ground-state electron transfer from graphene to PTCDI, resulting in band bending that prevents excited holes from transferring from PTCDI to graphene. This feature is exploited in a trilayer heterostructure of graphene/PTCDI/TiOPc, where the spatial separation of photoexcited electrons and holes in graphene and TiOPc, respectively, leads to the formation of long-lived photoexcitations with a lifetime of approximately 500 ps. Furthermore, spatially resolved transient absorption measurements reveal the immobile nature of these excitations, confirming that they are charge-transfer excitons rather than free electrons and holes. Furthermore, these results provide valuable insights into the complex interlayer photoexcitation transfer properties and demonstrate precise control over the layer population and the recombination lifetime of photocarriers in such hybrid heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Single Nanoflake Photoelectrochemistry Reveals Intrananoflake Doping Heterogeneity That Explains Ensemble-Level Photoelectrochemical Behavior

Transition metal dichalcogenide (TMD) nanoflake thin films are attractive electrode materials for photoelectrochemical (PEC) solar energy conversion and sensing applications, but their photocurrent quantum yields are generally lower than those of bulk TMD electrodes. The poor PEC performance has been primarily attributed to enhanced charge carrier recombination at exposed defect and edge sites introduced by the exfoliation process. Here, a single nanoflake PEC approach reveals how an alternative effect, doping heterogeneity, limits ensemble-level PEC performance. Photocurrent mapping and local photocurrent–potential (i–E) measurements of MoS 2 nanoflakes exfoliated from naturally occurring bulk crystals revealed the presence of n- and p-type domains within the same nanoflake. Interestingly, the n- and p-type domains in the natural MoS 2 nanoflakes were equally efficient for iodide oxidation and tri-iodide reduction (IQE values exceed 80%). At the single domain-level, the natural MoS 2 nanoflakes were nearly as efficient as nanoflakes exfoliated from synthetic n-type MoS 2 crystals. Single domain-level i–E measurements explain why natural MoS 2 nanoflakes exhibit an n-type to p-type photocurrent switching effect in ensemble-level measurements: the n- and p-type diode currents from individual domains oppose each other upon illuminating the entire nanoflake, resulting in zero photocurrent at the switching potential. Furthermore, the doping heterogeneity effect is likely due to nonideal stoichiometry, where p-type domains are S-rich according to XPS measurements. Although this doping heterogeneity effect limits photoanode or photocathode performance, these findings open the possibility to synthesize efficient TMD nanoflake photocatalysts with well-defined lateral p- and n-type domains for enhanced charge separation.

14 SOLAR ENERGY↗

DOE OSTI2024

Delineation of the impact on temporal behaviors of off-axis photoemission in an ultrafast electron microscope

Efforts to push the spatiotemporal imaging-resolution limits of femtosecond laser-driven ultrafast electron microscopes (UEMs) to the combined angstrom–fs range will benefit from stable sources capable of generating high bunch charges. Recent demonstrations of unconventional off-axis photoemitting geometries are promising, but connections to the observed onset of structural dynamics are yet to be established. Here we use the in-situ photoexcitation of coherent phonons to quantify the relative time-of-flight (r-TOF) of photoelectron packets generated from the Ni Wehnelt aperture and from a Ta cathode set-back from the aperture plane. We further support the UEM experiments with particle-tracing simulations of the precise electron-gun architecture and photoemitting geometries. In this way, we measure discernible shifts in electron-packet TOF of tens of picoseconds for the two photoemitting surfaces. Furthermore, these shifts arise from the impact that the Wehnelt-aperture off-axis orientation has on the electron-momentum distribution, which modifies both the collection efficiency and the temporal-packet distribution relative to on-axis emission. Future needs are identified; we expect this and other developments in UEM electron-gun configuration to expand the range of material phenomena that can be directly imaged on scales commensurate with fundamental structural dynamics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

A Parallel Kinetic Model for Surface and Bulk Charge Storage in ε -MnO 2 Pseudocapacitors

Pseudocapacitive materials such as manganese dioxide (MnO 2 ) are attractive for energy storage applications due to their ability to combine the fast kinetics of capacitors with the higher energy density of battery-type systems. However, the electrochemical behavior of MnO 2 remains difficult to interpret mechanistically, in part because existing models often fail to distinguish between surface-based redox processes and bulk intercalation mechanisms. In this work, we develop a physics-based model that represents MnO 2 pseudocapacitance as a linear combination of two independent, parallel electrochemical processes: (i) the surface or near-surface redox storage and (ii) lithium ion intercalation into the bulk material. These two processes are treated with distinct kinetic and thermodynamic parameters and are assumed to proceed independently. The total measured current is assumed to be the sum of these two partial currents. We validate the model using rate-dependent cyclic voltammetry experiments, demonstrating that it captures key trends and provides physically interpretable parameters reflecting the relative contributions of surface and bulk processes. By enabling a clear separation between these mechanisms, the model offers a useful framework for analyzing pseudocapacitive materials and can guide the rational design of high-performance energy storage electrodes.

Energy - Storage↗

DOE OSTI2023

Experimental measurements of soot formation in fuel-rich homogeneous mixtures using an optical rapid compression machine

Advanced combustion strategies are necessary for the use of more environmentally sustainable fuels than traditional diesel. Alcohol fuels and alcohol/gasoline blends are of particular interest as they are readily available in the marketplace. Heavy-duty engines typically use compression ignited, conventional diesel mixing controlled combustion. Mixing controlled combustion features a non-premixed diffusion flame with a wide range of local equivalence ratios, leading to potentially high rates of soot formation. This work studies the sooting behavior of iso-octane and ethanol as a function of equivalence ratio. Measurements are carried out in a rapid compression machine (RCM) and are reported for pre-ignition conditions of 10–30 bar and temperatures of 650–800 K. Theoretical equilibrium and bulk gas temperatures are calculated for both fuels. These data are used to identify the critical equivalence ratio, the lowest equivalence ratio where soot is detected with a single-pass laser extinction diagnostic. The critical equivalence ratio for iso-octane varies between 1.82 and 1.77 for compressed pressures of 10 and 20 bar, respectively. Ethanol, sometimes considered sootless, had a critical equivalence ratio between 2.37 and 2.12 for compressed pressures of 20 and 30 bar, respectively. When characterizing soot formation by oxygenated equivalence ratio, the critical equivalence ratios for ethanol approach those of iso-octane. This suggests the oxygenated nature of alcohol fuels reduces sooting tendency, but other factors such as fuel molecular structure and morphology may play a role. It was observed that ethanol will form soot at equivalence ratios only slightly higher than iso-octane, which could have implications in mixing controlled combustion. It was seen for both fuels that soot formation is pressure sensitive, with the critical equivalence ratio being inversely proportional to compressed pressure and the rate of soot formation. Future work will investigate the sooting behavior of gasoline/ethanol blends.

02 PETROLEUM↗

DOE OSTI2025

A Conjugated Oligoelectrolyte Exhibiting Room Temperature Spin-Correlated Radical Pair Character for Biological Sensing

We report a water-soluble conjugated oligoelectrolyte (COE) composed of carbazole-benzophenone, COE-CbzBP, that exhibits photogenerated spin-correlated radical pair (SCRP) behavior sensitive to static electric fields from DNA but not from lipid bilayers. The SCRP forms from a thermally activated, spin-polarized state enabled by partial π-conjugation disruption at the donor–acceptor (carbazole-benzophenone) nitrogen–carbon (N–C) junction, which facilitates a twisted intramolecular charge-transfer (TICT) geometry. This state minimizes the singlet–triplet energy gap (ΔE ST = 0.12 eV), radical–pair exchange coupling (J RP ∼ ΔE ST /2), and charge separation free energy (ΔG CS ) in both DNA (−0.19 eV) and lipid bilayers (−0.55 eV). Room-temperature continuous-wave electron paramagnetic resonance (CW-EPR) reveals a photogenerated spin-polarized singlet for COE-CbzBP that splits upon DNA association, consistent with modulation of J RP and hyperfine coupling (A x ), presumably via electric field-spin coupling. No spin-polarized signal was observed under dark, cryogenic conditions, or in liposomes, but was quenched by the spin trap 4-POBN. Transient absorption and spectroelectrochemistry confirmed magnetic-field sensitive long-lived excited-state absorption features attributed to charge-separated states 3 [Cbz •+ -BP •– ]*, which were lengthened by DNA, and quenched in lipid bilayers and 4-POBN. Quantum chemical simulations show that planar geometries (lipid-like) increase ΔE ST by 0.31 eV compared to TICT-optimized structures. This geometry-dependent modulation explains the absence of SCRP signatures in rigid environments, underscoring the importance of TICT states, minimized ΔE ST , and favorable ΔG CS for achieving room-temperature SCRP generation. These findings establish design principles for TICT-enabled molecules exhibiting qubit-like behavior that operate under ambient and biologically relevant conditions, with direct implications for quantum information science (QIS).

Aromatic compounds↗

DOE OSTI2025

Charge density fluctuations with enhanced superconductivity at the proposed quantum critical point of Sr0.77⁢Ba0.23⁢Ni2⁢As2

A quantum critical point (QCP) represents a continuous phase transition at absolute zero. In unconventional superconductors, enhanced superconducting transition temperature and magnetic fluctuation strength are often observed together, indicating magnetism-mediated superconductivity. This raises the question of whether quantum fluctuations in other degrees of freedom, such as charge, could similarly boost superconductivity. However, because charge is frequently intertwined with magnetism, isolating and understanding its specific role in Cooper pair formation pose a significant challenge. Here, we report persistent charge density fluctuations (CDFs) down to 15 K in the nonmagnetic superconductor Sr0.77⁢Ba0.23⁢Ni2⁢As2, which lie near a proposed nematic QCP associated with a sixfold enhancement of superconductivity. Our results show that the quasielastic CDFs do not condense into resolution-limited Bragg peaks but, rather, display nonsaturated strength. The phonons associated with CDFs completely soften at 25 K, with their critical behavior described by the same mathematical framework as the antiferromagnetic Fermi liquid model, yielding a fitted Curie-Weiss temperature of 𝜃≈0K. Additionally, we find that the nematic fluctuations are weakly coupled to the lattice, as evidenced by the absence of softening in nematic-coupled in-plane transverse acoustic phonons. Our discovery positions Sr𝑥⁢Ba1−𝑥⁢Ni2⁢As2 as a promising candidate for charge-fluctuation-driven superconductivity.

Aczel, Adam [ORNL] (ORCID:0000000319641943)↗

DOE OSTI2026

A Vibrational Probe of Electrical Doping in N2200 and Fermi-Level Alignment at Polymer Cathode/Metal Cocatalyst/Electrolyte Junctions

Hybrid (photo)cathodes consisting of conjugated polymer and hydrogen evolution reaction (HER) cocatalysts are an emerging platform for low-cost solar fuel generation. Poly{[N,N′-bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)}, known as P(NDI2OD-T2) or N2200, is a promising electron accepting material for bulk heterojunction photocathodes. Unlike inorganic (photo)electrodes, much less is known about the energetic alignment of conjugated polymer electrode/metal/electrolyte junctions. Here, in this work, we investigate the electrical doping behavior in an N2200 cathode and its Fermi-level alignment with gold nanoparticles, which is used here as a model for the hydrogen evolution metal cocatalyst. Through UV/visible, Raman, and attenuated total-reflectance infrared spectroelectrochemistry, we observe the impact of electrical doping on the vibrational frequencies of neutral, anion, and dianion species in N2200, which suggests that electron density changes within the corresponding naphthalene-diimide (NDI) units. Upon one-electron reduction, the $C=O$ stretching frequency of the NDI anion unit (polaron) shows a red shift by ∼ 68 cm –1 . Additionally, the $C=O$ stretching frequency of neutral units in the doped N2200 shows a minor red shift of ∼ 5 cm –1 , suggesting charge transfer from neighboring polaron units. Surface-enhanced Raman spectroscopy measurements of a gold nanoparticle-functionalized N2200 electrode revealed that the Au Fermi level only shifts with that of N2200 upon polaron formation; thus, the formal potential of polymer polaron formation determines the behavior of the catalyst Fermi level, which we posit will modulate reaction capability. This mechanistic study provides a new approach for understanding the nanometer-scale energetics at the conjugated polymer/cocatalyst junction and provides critical insights for the future design of HER (photo)cathodes.

charge transfer↗

DOE OSTI2022

Influence of temporal variations in plasma conditions on the electric potential near self-organized dust chains

Self-organization of dust grains into stable filamentary dust structures (or “chains”) largely depends on dynamic interactions between individual charged dust grains and complex electric potential arising from the distribution of charges within a local plasma environment. Recent studies have shown that the positive column of the gas discharge plasma in the Plasmakristall-4 (PK-4) experiment at the International Space Station supports the presence of fast-moving ionization waves, which lead to variations of plasma parameters by up to an order of magnitude from the average background values. The highly variable environment resulting from ionization waves may have interesting implications for the dynamics and self-organization of dust particles, particularly concerning the formation and stability of dust chains. Here, we investigate the electric potential surrounding dust chains in the PK-4 experiment by employing a molecular dynamics model of the dust and ions with boundary conditions supplied by a particle-in-cell with Monte Carlo collision simulation of the ionization waves. The model is used to examine the effects of the plasma conditions within different regions of the ionization wave and compare the resulting dust structure to that obtained by employing the time-averaged plasma conditions. Here, the comparison between simulated dust chains and experimental data from the PK-4 experiment shows that the time-averaged plasma conditions do not accurately reproduce observed results for dust behavior, indicating that more careful treatment of plasma conditions in the presence of ionization waves is required. It is further shown that commonly used analytic forms of the electric potential do not accurately describe the electric potential near charged dust grains under these plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

An energetic link between order and strength in metals: A nanocrystalline strength limit in high-entropy alloys and intermetallic compounds

The metallurgy and materials communities have long understood and exploited fundamental links between chemical and structural ordering in metallic solids to tailor their mechanical properties. We extend these ideas to include prediction of the nanocrystalline strength limit in high-entropy alloys and intermetallic compounds, where a breakdown occurs in the classical Hall-Petch strengthening behavior. The highest reported strength achievable through alloying has rapidly climbed and given rise to new classifications of materials with extraordinary properties, with a notable case being nanocrystalline metals. High-entropy alloys (chemically disordered, concentrated solid solutions) and intermetallic compounds are two boundary cases of how tailored order can be used to manipulate mechanical behavior. Here, we show that the complex electronic-structure mechanisms governing the peak strength of alloys and pure metals can be reduced to a few physically meaningful parameters based on their atomic arrangements and used – with no fitting parameters – to predict the maximum strength of these materials. This includes a generalized energy-based accounting for the degree of structural and chemical ordering that allows for rapid and reasonably accurate prediction of peak strength (validated in the nanocrystalline limit) as a function of temperature. Predictions of maximum strength based on the activation energy (with all materials properties derived from DFT calculations or experiments) for a stress-driven transition to an amorphous state is shown to accurately describe the breakdown in Hall-Petch behavior at the smallest crystallite sizes for pure metals, intermetallic compounds, high-entropy alloys, and metallic glasses. Further, this activation energy is also shown to be directly proportional to interstitial electronic charge density, which is a good predictor of ductility, stiffness (moduli), and phase stability in high-entropy alloys and solid metals generally. The proposed framework suggests the possibility of coupling ordering and intrinsic strength to mechanisms like dislocation nucleation, hydrogen embrittlement, and transport properties, such as through correlations between the activation energies for amorphization with stacking-fault and grain boundary energies. It additionally opens the prospect for greatly accelerated structural materials design and development to address materials challenges limiting more sustainable and efficient use of energy.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Solution and Interface Structure and Dynamics in Geochemistry: Gateway to Link Elementary Processes to Mineral Nucleation and Growth

Our understanding of the process of mineral nucleation is starting to evolve from the solely thermodynamical aspects in classical nucleation theory toward a mechanistic study of reactions influenced by solvation structures of ions and their dynamics. A knowledge of how these atomic and molecular interactions respond to changing solution composition and/or the nature of an interface will form a fundamental foundation to understand rate-limiting reactions and processes for nucleation and growth. Here, we review recent advances from multidisciplinary experimental and computational approaches of the structure and dynamics of aqueous solutions and mineral–liquid interfaces that will influence rates of nucleation (and growth behavior) both homogeneously in aqueous solutions and heterogeneously at mineral–liquid interfaces. Furthermore, these processes include structure (and extent) of solute clustering, solvent degrees of freedom, and the presence of noninnocent charge-balancing ions, all of which can drive the selectivity and exert control over nucleation mechanisms. Similar controlling reactions can also occur at interfaces with the added complexities of how solute ions interact with and assemble on surface sites and use different mechanisms from bulk solutes, such as lateral solvent exchanges between distinct surface sites. To gain a predictive understanding of nucleation chemistry, we emphasize several key knowledge gaps that will need to be addressed in this field and highlight the importance of combining computations and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗