Search NASA⌕ Search

SEARCH · Search NASA

Results for “reactivity control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Improving the Performance of Integrated Power-Hardware-in-the-Loop and Quasi-Static Time-Series Simulations

This paper introduces a novel multirate cosimulation architecture that overcomes previous challenges integrating faster real-time, microseconds-scale, power-hardware-in-the-loop (PHIL) with larger scale but slower, real-time, seconds-scale, quasi-static time-series (QSTS) simulation. Specifically, an intermediate reduced-equivalent electromagnetic transient (EMT) model duplicates the key power system topology to capture high-speed dynamics and converge hardware-power system interactions between QSTS updates. Exchanging multidimensional parameter vectors (loads, control status, etc.) between the QSTS and EMT models enables capturing the interactions of the rich, high-node-count (thousands of electrical nodes) QSTS model with the hardware. This architecture offers full spatial resolution from QSTS, including individual load dynamics, actual distribution management system controls, and nodal voltages. Simultaneously, the intermediate EMT model provides more detailed high-speed transients of key distributed energy resource hardware interactions. In addition, we use careful PHIL interface design and the exchange of complex power data, rather than current, to further improve performance. This cosimulation architecture is demonstrated by testing a simulated distribution system with an interconnected 500-kVA advanced photovoltaic (PV) inverter in PHIL. In conclusion, the architecture successfully captured PV local volt-volt ampere reactive (volt-VAR) control interactions with the larger network under time-varying electrical and weather conditions.

42 ENGINEERING↗
DOE OSTI2022

Facile synthesis of epoxide-co-propylene sulphide polymers with compositional and architectural control

Here, we present a facile method to produce propylene sulphide (PS) homopolymers up to 100 kg mol -1 and PS-epoxide statistical, block, and ABA copolymers using inexpensive and versatile thio-aluminium (SAl) based initiators. Homopolymerizations of PS with SAl initiators are living and controlled, with number averaged molecular weights ($\bar M$ n ) up to 100 kg mol -1 while maintaining narrow polydispersity (Ð < 1.4). Statistical and block copolymers of PS and epichlorohydrin (ECH) or propylene oxide (PO) are synthesized and characterized by size-exclusion chromatography (SEC), differential scanning calorimetry (DSC), 1 H and 13 C NMR spectroscopy, diffusion ordered spectroscopy (DOSY), and small-angle X-ray scattering (SAXS). This work represents the first statistical copolymerization of PS and epoxides with similar reactivity ratios, allowing fine control over composition. Block-copolymers of PS and epoxides are synthesized by sequential addition, without intermediate preparative steps. Polymer architecture is controlled through modification of the initiator; we synthesized a di-functional (d-H) SAl initiator to produce ABA tri-block-copolymers. Finally, poly(ethylene glycol) (PEG) was used as a macroinitiator to create PEG-b-PPS block copolymers and characterized by 1 H, 13 C NMR spectroscopy, DOSY, DSC, and SEC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Review of Power System Support Functions for Inverter-Based Distributed Energy Resources - Standards, Control Algorithms, and Trends

Penetration of renewable energy in power systems has been increasing in the past decades in response to increased global electricity demand and concerns for the environment. Distributed energy resources (DERs) based on renewables have experienced rapid growth thanks to the incentive programs and broad-based participation. With the growing prevalence of DERs, the risk of grid instability and vulnerability increases due to the intermittent nature of renewable energy. At the same time, the voltage and frequency deviation problems emerge more often when the reverse power flow occurs under supply-demand imbalance in distributed power systems. Standards and grid codes have been issued for DER inverters to interconnect with the distribution grid. The updated standard and grid codes expect DERs to provide a variety of power system support functions in order to incorporate higher DER penetration and to maximize DER value to the grid. This paper provides an overview of the power system support functions from renewable DER inverters, which are categorized as: voltage regulation by active/reactive power control, frequency regulation by active power control, voltage ride-through, and frequency ride-through. The benefits and drawbacks of each algorithm are presented and compared with its predecessor, manifesting the logic in the evolution of the algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Comprehensive compilations of computation results and validations for neutronics start-up tests at China Experimental Fast Reactor

This paper compiles and analyzes refined results of the coordinated research project (CRP) on Neutronics Benchmark of China Experimental Fast Reactor (CEFR) Start-Up Tests conducted by the International Atomic Energy Agency (IAEA) since 2018. Twenty-eight research organizations participated with various code systems. The China Institute of Atomic Energy (CIAE) provided the benchmark specifications and participants conducted the benchmark through blind and refined phases. This paper presents the benchmark results on six experimental measurements, criticality, control rod worth, temperature reactivity coefficients, sodium void worth, assembly swap reactivities, and foil activations. Except for a few outlier results, the simulation results show good agreement with the measured data within 1-σ experiment uncertainties. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Quantitative Trade-Off in Distributed Secondary Control for Autonomous AC Microgrids

In this paper, we propose to quantify the trade-off between voltage regulation and reactive power sharing in autonomous AC microgrids with distributed secondary control. It is known that voltage regulation and reactive power sharing in droop-controlled autonomous AC microgrids are two conflicting control objectives that present a natural trade-off between voltage regulation towards the voltage magnitude reference and reactive power sharing accuracy. This trade-off is commonly shown qualitatively without sufficient quantification. In this work, to quantify the trade-off between the two objectives, we focus on distributed secondary control and utilize regression and polynomial surface fitting to identify the requisite parameter area to satisfy the predefined error bands for voltage magnitude regulation and reactive power sharing. Extensive case studies are presented to validate the proposed method.

autonomous AC microgrids↗
DOE OSTI2020

Thermally Activated Delayed Photoluminescence: Deterministic Control of Excited-State Decay

Thermally activated photophysical processes are ubiquitous in numerous organic and metal-organic molecules, leading to chromophores with excited state properties that can be considered an equilibrium mixture of the available low-lying states. Relative populations of the equilibrated states are governed by temperature. Such molecules have been devised as high quantum yield emitters in modern organic light-emitting diode technology and for deterministic excited state lifetime control to enhance chemical reactivity in solar energy conversion and photocatalytic schemes. This recent discovery of thermally activated photophysics at CdSe nanocrystal-molecule interfaces enables a new paradigm wherein molecule-quantum dot constructs are used to systematically generate material with predetermined photophysical response and excited state properties. Semiconductor nanomaterials feature size-tunable energy level engineering, which considerably expands the purview of thermally activated photophysics beyond what is possible using only molecules. This Perspective is intended to provide a non-exhaustive overview of the advances that led to the integration of semiconductor quantum dots in thermally activated delayed photoluminescence (TADPL) schemes and to identify important challenges moving into the future. The initial establishment of excited state lifetime extension utilizing triplet-triplet excited-state equilibria is detailed. Next, advances involving the rational design of molecules composed of both metal-containing and organic-based chromophores that produce the desired TADPL are described. Lastly, the recent introduction of semiconductor nanomaterials into hybrid TADPL constructs is discussed, paving the way towards the realization of fine-tuned deterministic control of excited state decay. It is envisioned that libraries of synthetically facile composites will be broadly deployed as photosensitizers and light emitters for numerous synthetic and optoelectronic applications in the near future.

14 SOLAR ENERGY↗
DOE OSTI2023

Automated power-following control for nuclear thermal propulsion startup and shutdown using MOOSE-based applications

This paper describes an investigation of various automated control strategies applied to a full-core multiphysics Griffin/Bison/RELAP-7 model of a prototypical nuclear thermal propulsion system. In all cases, control is achieved by actuating control drums based on the demanded power and predicted quantities from the numerical model. One key finding is that hybrid proportional integral derivative controllers – a novel type of controller that uses both power and reactivity predicted signals – can demonstrate a level of performance rivaling that of period-generated control. The former requires parameter tuning, while the latter mostly necessitates providing reactivity coefficients and temperature rates of change, which could be very challenging to accurately measure in real-time. In addition, decay heat plays an important role in determining cooling requirements during cooldown phases. A decay heat model, accounting for burn time and throttling, was derived, and is incorporated within the model to simulate the steady-state and shutdown phases and satisfyingly follow the power demand. However, temperature overshoots and non-constant specific impulse during throttling will necessitate further improvements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Data-Driven Chance-Constrained Design of Voltage Droop Control for Distribution Networks: Preprint

This paper addresses the design of local control methods for voltage control in distribution networks with high level of distributed energy resources (DERs). The designed control methods adapt the active and reactive power output of distributed energy resources proportional to the deviation of the local measured voltage magnitudes from a reference voltage, which is referred to as droop control. Thus, the design focuses on determining the droop characteristics which satisfy network-wide voltage magnitude constraints. The uncertainty and variability of DERs renders the design of optimal droop controls very challenging. Hence, this paper proposes chance constraints to limit the risk from intermittent DERs, by designing droop control coefficients that guarantee the satisfaction of network operational constraints with a specific probability. In addition, the proposed approach relies entirely on historical data rather than assuming knowledge of the probability distributions that characterize the uncertainty of DERs. The efficacy of the proposed method is demonstrated on a 37-bus distribution feeder.

chance-constrained optimization↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2020

Current Observer Based Predictive Decoupled Power Control Grid-Interactive Inverter

This paper presents a sensor-less current model predictive control (MPC) scheme via a full state observer based current estimator. The grid interactive inverters’ control schemes require current and voltage sensors. Elimination of current sensor enhances the inverter reliability. This paper leverages the inherent characteristics of MPC towards robust current sensor-less grid interactive inverter with LC filter. The observer for inductor current is developed based on the existing capacitor voltage measurement. The estimator dynamic state-space matrices are then obtained through reconstruction of the inverter model with the capacitor voltage and inductor current being the state variables. The controller objectives are to regulate active and reactive power in a decoupled manner. The theoretical expectation, controller performance, and accuracy of the current estimation are verified by conducting a real-time simulation via Typhoon HIL.

Zhang, Zhen↗
DOE OSTI2022

Radical SAM enzymes: Nature's choice for radical reactions

Enzymes that use a [4Fe-4S] 1+ cluster plus S-adenosyl-L-methionine (SAM) to initiate radical reactions (radical SAM) form the largest enzyme superfamily, with over half a million members across the tree of life. This review summarizes recent work revealing the radical SAM reaction pathway, which ultimately liberates the 5´-deoxyadenosyl (5´-dAdo•) radical to perform extremely diverse, highly regio- and stereo-specific, transformations. Most surprising was the discovery of an organometallic intermediate Ω exhibiting an Fe-C5´-adenosyl bond. Ω liberates 5´-dAdo• through homolysis of the Fe-C5´ bond, in analogy to Co-C5´ bond homolysis in B12, previously viewed as biology’s paradigmatic radical generator. The 5´-dAdo• has been trapped and characterized in radical SAM enzymes via a recently-discovered photoreactivity of the [4Fe- 4S] + /SAM complex, and has been confirmed as a catalytically active intermediate in enzyme catalysis. The regioselective SAM S-C bond cleavage to produce 5´-dAdo• originates in the JahnTeller effect. The simplicity of SAM as a radical precursor, and the exquisite control of 5´-dAdo• reactivity in radical SAM enzymes, may be why radical SAM enzymes pervade the tree of life, while B12 enzymes are only a few.

deoxyadenosyl radical↗
DOE OSTI2021

Biocatalytic Yarn for Peroxide Decomposition with Controlled Liquid Transport

In this study, a robust biocatalytic yarn with controllable liquid transport properties is created by coating thin layers of chitosan containing catalase onto a cellulosic yarn. The resulting material integrates enzyme catalytic functionality with protective coating properties of chitosan and structural functionality of the textile. Mild immobilization conditions and good affinity between the two polysaccharides minimize enzyme inactivation during the preparation steps and prevent enzyme from leaching during peroxide decomposition testing and washing, providing a novel and versatile enzyme immobilization strategy. The catalytic efficiency of enzymes in a reaction containing solid, liquid, and gas phases is facilitated when dissolved enzyme substrate is transported by liquid flowing through the coated textile structure. The flow-through configuration decomposes at least two times more peroxide in a twenty-times smaller reaction zone volume compared to a stirred tank configuration. Liquid transport through the yarn and liquid spatial distribution within the yarn are investigated by in situ neutron radiography and neutron computed tomography, revealing a constrained wicking mechanism that benefits biocatalytic yarn performance. This new class of sustainable and flexible biocatalytic textile matrices has beneficial multifunctional properties, not previously described, that are applicable for numerous small- and large-scale applications including controlled flow reactors and reactive filtration.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Metal-Centered Photoredox Catalysis using d 6 Transition Metal-based Chromophores

Controlling excited-state reactivity in transition metal chromophores is central to light-driven chemistry, with applications spanning from solar energy conversion to photoredox catalysis. Ru(II) and Ir(III) chromophores currently dominate applications within this field due to their long-lived charge-transfer (CT) excited states, which support bimolecular electron transfer chemistry. However, their elemental scarcity and relative lack of selectivity for differentiating oxidative versus reductive pathways has in part motivated the exploration of alternative platforms that could, in principle, offer distinct mechanistic opportunities. Earth-abundant, valence-isoelectronic 3d 6 complexes of Fe(II) and Co(III) have attracted significant attention due to their electronic similarity to Ru(II) and Ir(III), suggesting the potential for complementary photophysical behavior. In contrast to their heavier congeners, however, the weaker ligand fields of first-row transition metals promote rapid relaxation from initially populated CT states to low-lying metal-centered (MC) excited states, typically of 5 T 2 or 3 T 1 character. Because these MC states involve redistribution of electron density within MC d-orbitals rather than charge separation between metal and ligand orbitals, they were historically considered poor candidates for use in photochemical transformations.

Charge transfer↗
DOE OSTI2023

Quantitative Separation of Unknown Organic–Metal Complexes by Liquid Chromatography–Inductively Coupled Plasma-Mass Spectrometry

Dissolved organic matter (DOM) is widely recognized to control the solubility and reactivity of trace metals in the environment. However, the mechanisms that govern metal-DOM complexation remain elusive, primarily due to the analytical challenge of fractionating and quantifying metal–organic species within the complex mixture of organic compounds that comprise DOM. Here, we describe a quantitative method for fractionation and element-specific detection of organic–metal complexes using liquid chromatography with online inductively coupled plasma mass spectrometry (LC–ICP-MS). The method implements a post-column compensation gradient to stabilize ICP–MS elemental response across the LC solvent gradient, thereby overcoming a major barrier to achieving quantitative accuracy with LC–ICP-MS. With external calibration and internal standard correction, the method yields concentrations of organic–metal complexes that were consistently within 6% of their true values, regardless of the complex’s elution time. We used the method to evaluate the effects of four stationary phases (C18, phenyl, amide, and pentafluoroylphenyl propyl) on the recovery and separation of environmentally relevant trace metals (Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in Suwannee River Fulvic Acid and Suwannee River Natural Organic Matter. The C18, amide, and phenyl phases generally yielded optimal metal recoveries (>75% for all metals except Pb), with the phenyl phase separating polar species to a greater extent than C18 or amide. We also fractionated organic-bound Fe, Cu, and Ni in oxidized and reduced soils, revealing divergent metal-DOM speciation across soil redox environments. Finally, by enabling quantitative fractionation of DOM-bound metals, our method offers a means for advancing a mechanistic understanding of metal–organic complexation throughout the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Interaction of Anisole on Alumina-Supported Ni and Mo Oxide Hydrodeoxygenation Catalysts

The conversion of biomass to transportation fuels and value-added chemicals is a promising method to reduce reliance on fossil fuels. Mo-based catalysts have been shown to be highly active in the hydrodeoxygenation of biomass-derived phenolic compounds. The catalyst active phase, surface species, and the effect of adding additional metals is not comprehensively understood. Here we compare the temperature-dependent adsorption behavior of the model compound anisole 2 on an alumina-supported mixed nickel molybdenum oxide catalyst with two reference catalysts of molybdenum oxide and nickel oxide. Raman spectroscopy showed that the catalysts contain significant amounts of molybdates and molybdoaluminates, in addition to NiMoO 4 in the nickel molybdenum catalyst and MoO 3 in the molybdenum-only catalyst. Using transmission infrared spectroscopy under a controlled environment, we find that anisole chemisorbed largely through the oxygen in the methoxy group to form surface-bound phenoxy and methoxy species on all the catalysts. Ambient pressure X-ray photoelectrons spectroscopy measurements of the catalysts in anisole vapor showed reduced Mo atoms are the binding sites. The surface interaction and removal temperature of these species varied with the metal composition. The MoO x component dominated the adsorption behavior in both MoO x and NiMoO x catalysts. The formation of new aromatics, including methylated rings, depended on Ni composition. Upon adding hydrogen to induce the hydrodeoxygenation of anisole, undesirable polynuclear aromatic species were quickly formed on the Mo-based catalysts. In conclusion, these results suggest that the molybdenum oxide controls the adsorption and reactivity of the surface species, with a cooperative effect by Ni.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Zeolitic Imidazole Framework Decorated Substrates for Lead Removal From Water

Lead contamination in water supplies necessitates efficient and mechanistically understood removal strategies. Zeolitic imidazole frameworks (ZIFs) are promising adsorbents; however, ZIF-67 (Co-based) is more susceptible to hydrolysis than its zinc analogue ZIF-8, raising questions about stability during metal uptake. In this study, we systematically compare ZIF-8 and ZIF-67 under controlled pH conditions and evaluate how substrate anchoring influences hydrolytic stability and Pb 2+ adsorption behavior. By integrating adsorption capacity measurements, kinetic analysis, metal-node leaching data, and structural characterization, we distinguish ion exchange from framework degradation and clarify the temporal interplay between adsorption and hydrolysis. Although ZIF-67 exhibits greater hydrolytic sensitivity, coordination with phosphoryl-bearing Mucor hiemalis membranes significantly reduces Co 2+ leaching and enhances structural retention. Under the optimized conditions (pH 5), ZIF-67@Mucor achieves a maximum Pb 2+ adsorption capacity of 867 mg g −1 . These findings demonstrate that substrate-dependent stabilization enables controlled exploitation of ZIF reactivity for aqueous metal remediation.

Adsorption↗
DOE OSTI2021

Spontaneous Reorganization of DNA-Based Polymers in Higher Ordered Structures Fueled by RNA

We demonstrate a strategy that allows for the spontaneous reconfiguration of self-assembled DNA polymers exploiting RNA as chemical fuel. To do this, we have rationally designed orthogonally addressable DNA building blocks that can be transiently deactivated by RNA fuels and subtracted temporarily from participation in the self-assembly process. Through a fine modulation of the rate at which the building blocks are reactivated we can carefully control the final composition of the polymer and convert a disordered polymer in a higher order polymer, which is disfavored from a thermodynamic point of view. We measure the dynamic reconfiguration via fluorescent signals and confocal microscopy, and we derive a kinetic model that captures the experimental results. Our approach suggests a novel route toward the development of biomolecular materials in which engineered chemical reactions support the autonomous spatial reorganization of multiple components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

pH-Driven Restructuring of Hydration Layers and Cation Adsorption at the Alumina–Water Interface

Oxide−water interfaces underpin ion separations, catalysis, and electrochemical energy technologies, where the electrical double layer (EDL) controls adsorption, transport, and reactivity. However, the molecular-scale links between pHdependent surface protonation, hydration-layer structure, and counterion adsorption remain poorly defined. Here, we combine in situ crystal truncation rod (CTR) and resonant anomalous X-ray reflectivity (RAXR) with streaming potential measurements and ab initio molecular dynamics (AIMD) simulations to resolve the chemical and structural evolution of the EDL at the single-crystal alumina (012)−water interface in 10 mM Rb + over pH 3−12. CTR measurements reveal two distinct adsorbed water layers at ∼2.2 and ∼3.5 Å above the surface. Each water layer shifts toward the substrate at transition pHs near 6.5 and 10.6, respectively, reflecting changes in primary hydration layer structure in response to the deprotonation of bridging and terminal aluminol groups. RAXR shows a 10-fold increase in Rb + coverage and a decrease in mean adsorption height from ∼3.5 to ∼2.7 Å with increasing pH, indicating enhanced counterion binding accompanied by Stern layer contraction. Streaming potential measurements demonstrate that the zeta potential, i.e., the potential at the hydrodynamic shear plane, is positive at pH 3 and becomes negative at pH ≥ 3.5. The negative charge magnitude increases with increasing pH, consistent with progressive surface deprotonation at higher pH. AIMD identifies inner- and outer-sphere Rb+ complexes whose adsorption heights and coordination geometries depend sensitively on the protonation state of surface oxygens, providing atomistic support for the experimentally inferred trends. These measurements establish two discrete, site-specific pH transitions in hydration-layer structure that track aluminol (de)protonation and quantitatively link them to a pH-driven contraction of the Stern layer (increasing Rb + coverage and decreasing adsorption height). This provides a direct structural basis for connecting surface acid−base chemistry to ion binding distances at an oxide−water interface.

Adsorption↗