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Experimental demonstration and analysis of random field effects in ferromagnet/antiferromagnet bilayers

More than 30 years ago, Malozemoff [Phys. Rev. B 35, 3679 (1987)] hypothesized that exchange interaction at the interface between a ferromagnet (F) and an antiferromagnet (AF) can act as an effective random field, which can profoundly affect the magnetic properties of the system. However, until now this hypothesis has not been directly experimentally tested. We utilize magnetoelectronic measurements to analyze the effective exchange fields at permalloy/CoO interface. Our results cannot be explained in terms of quasiuniform effective exchange fields but are in agreement with the random-field hypothesis of Malozemoff. Finally, the presented approach opens a new route for the quantitative analysis of effective exchange fields and anisotropies in magnetic heterostructures for memory, sensing and computing applications.

36 MATERIALS SCIENCE↗

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗

Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI

Primers were developed and published for the use of the KENO V.a and KENO-VI codes in 2005 and 2008, respectively. These primers were both developed for SCALE 5 using the GeeWiz graphical user interface (GUI). Many new capabilities have been added to the transport codes since the release of these primers. The GUI was also changed to Fulcrum with the release of SCALE 6.2. For these reasons, updated versions of both primers were developed for a planned released in September 2020. The KENO V.a and KENO-VI codes are almost always run within the associated CSAS5 and CSAS6 sequences within SCALE, so the primers use the sequences and do not address running the codes in stand-alone mode.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI [Slides]

Primers were developed and published for the use of the KENO V.a and KENO-VI codes in 2005 and 2008, respectively. These primers were both developed for SCALE 5 using the GeeWiz graphical user interface (GUI). Many new capabilities have been added to the transport codes since the release of these primers. The GUI was also changed to Fulcrum with the release of SCALE 6.2. For these reasons, updated versions of both primers were developed for a planned released in September 2020. The KENO V.a and KENO-VI codes are almost always run within the associated CSAS5 and CSAS6 sequences within SCALE, so the primers use the sequences and do not address running the codes in stand-alone mode.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗

Worldline approach for numerical computation of electromagnetic Casimir energies: Scalar field coupled to magnetodielectric media

Here, we present a worldline method for the calculation of Casimir energies for scalar fields coupled to magnetodielectric media. The scalar model we consider may be applied in arbitrary geometries, and it corresponds exactly to one polarization of the electromagnetic field in planar layered media. Starting from the field theory for electromagnetism, we work with the two decoupled polarizations in planar media and develop worldline path integrals, which represent the two polarizations separately, for computing both Casimir and Casimir-Polder potentials. We then show analytically that the path integrals for the transverse-electric polarization coupled to a dielectric medium converge to the proper solutions in certain special cases, including the Casimir-Polder potential of an atom near a planar interface, and the Casimir energy due to two planar interfaces. We also evaluate the path integrals numerically via Monte Carlo path-averaging for these cases, studying the convergence and performance of the resulting computational techniques. Lastly, while these scalar methods are only exact in particular geometries, they may serve as an approximation for Casimir energies for the vector electromagnetic field in other geometries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

59 BASIC BIOLOGICAL SCIENCES↗

Tensor integrand reduction via Laurent expansion

We introduce a new method for the application of one-loop integrand reduction via the Laurent expansion algorithm, as implemented in the public C++ library Ninja. We show how the coefficients of the Laurent expansion can be computed by suitable contractions of the loop numerator tensor with cut-dependent projectors, making it possible to interface Ninja to any one-loop matrix element generator that can provide the components of this tensor. We implemented this technique in the Ninja library and interfaced it to MadLoop, which is part of the public MadGraph5_aMC@NLO framework. We performed a detailed performance study, comparing against other public reduction tools, namely CutTools, Samurai, IREGI, PJFry++ and Golem95. We find that Ninja out-performs traditional integrand reduction in both speed and numerical stability, the latter being on par with that of the tensor integral reduction tool Golem95 which is however more limited and slower than Ninja. Lastly, we considered many benchmark multi-scale processes of increasing complexity, involving QCD and electro-weak corrections as well as effective non-renormalizable couplings, showing that Ninja’s performance scales well with both the rank and multiplicity of the considered process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Crystal and Electronic Structures of Complex Bismuth Iodides A 3 Bi 2 I 9 ( A = K, Rb, Cs) Related to Perovskite: Aiding the Rational Design of Photovoltaics

Ternary bismuth halides form an interesting functional materials class in the context of the closely related Pb halide perovskite photovoltaics, especially given the significantly reduced toxicity of Bi when compared with Pb. The compounds A 3 Bi 2 I 9 (A = K, Rb, Cs) examined here crystallize in two different structure types: the layered defect-perovskite K 3 Bi 2 I 9 type, and the Cs 3 Cr 2 Cl 9 type. The latter structure type features isolated Bi 2 I 9 3– anions. Here, the crystal structures of the ternary iodides are redetermined and a corrected structural model for Rb 3 Bi 2 I 9 , as established by single crystal X-ray diffraction and solid state 87Rb NMR spectroscopy and supported by density functional theory (DFT) calculations is presented. A variety of facile preparation techniques for single crystals, bulk materials, as well as solution-processed thin films are described. The optical properties and electronic structures are investigated experimentally by optical absorption and ultraviolet photoemission spectroscopy and computationally by DFT calculations. Absolute band positions of the valence and conduction bands of these semiconductors, with excellent agreement of experimental and calculated values, are reported, constituting a useful input for the rational interface design of efficient electronic and optoelectronic devices. The different structural connectivity in the two different structure types, somewhat surprisingly, appears to not impact band positions or band gaps in a significant manner. Computed dielectric properties, including the finding of anomalously large Born effective charge tensors on Bi 3+ , suggest proximal structural instabilities arising from the Bi 3+ 6s 2 lone pair. These anomalous Born effective charges are promising for defect screening and effective charge carrier transport. The structural, electronic, and optical properties of the complex bismuth iodides are to some extent similar to the related lead iodide perovskites. In conclusion, the deeper valence band positions in the complex bismuth iodides point to the need for different choices of hole transport materials for Bi-iodide based solar cell architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Resiliency in numerical algorithm design for extreme scale simulations

Here this work is based on the seminar titled ‘Resiliency in Numerical Algorithm Design for Extreme Scale Simulations’ held March 1–6, 2020, at Schloss Dagstuhl, that was attended by all the authors. Advanced supercomputing is characterized by very high computation speeds at the cost of involving an enormous amount of resources and costs. A typical large-scale computation running for 48 h on a system consuming 20 MW, as predicted for exascale systems, would consume a million kWh, corresponding to about 100k Euro in energy cost for executing 10 23 floating-point operations. It is clearly unacceptable to lose the whole computation if any of the several million parallel processes fails during the execution. Moreover, if a single operation suffers from a bit-flip error, should the whole computation be declared invalid? What about the notion of reproducibility itself: should this core paradigm of science be revised and refined for results that are obtained by large-scale simulation? Naive versions of conventional resilience techniques will not scale to the exascale regime: with a main memory footprint of tens of Petabytes, synchronously writing checkpoint data all the way to background storage at frequent intervals will create intolerable overheads in runtime and energy consumption. Forecasts show that the mean time between failures could be lower than the time to recover from such a checkpoint, so that large calculations at scale might not make any progress if robust alternatives are not investigated. More advanced resilience techniques must be devised. The key may lie in exploiting both advanced system features as well as specific application knowledge. Research will face two essential questions: (1) what are the reliability requirements for a particular computation and (2) how do we best design the algorithms and software to meet these requirements? While the analysis of use cases can help understand the particular reliability requirements, the construction of remedies is currently wide open. One avenue would be to refine and improve on system- or application-level checkpointing and rollback strategies in the case an error is detected. Developers might use fault notification interfaces and flexible runtime systems to respond to node failures in an application-dependent fashion. Novel numerical algorithms or more stochastic computational approaches may be required to meet accuracy requirements in the face of undetectable soft errors. These ideas constituted an essential topic of the seminar. The goal of this Dagstuhl Seminar was to bring together a diverse group of scientists with expertise in exascale computing to discuss novel ways to make applications resilient against detected and undetected faults. In particular, participants explored the role that algorithms and applications play in the holistic approach needed to tackle this challenge. This article gathers a broad range of perspectives on the role of algorithms, applications and systems in achieving resilience for extreme scale simulations. The ultimate goal is to spark novel ideas and encourage the development of concrete solutions for achieving such resilience holistically.

79 ASTRONOMY AND ASTROPHYSICS↗

A moving control volume approach to computing hydrodynamic forces and torques on immersed bodies

Here, we present a moving control volume (CV) approach to computing hydrodynamic forces and torques on complex geometries. The method requires surface and volumetric integrals over a simple and regular Cartesian box that moves with an arbitrary velocity to enclose the body at all times. The moving box is aligned with Cartesian grid faces, which makes the integral evaluation straightforward in an immersed boundary (IB) framework. Discontinuous and noisy derivatives of velocity and pressure at the fluid–structure interface are avoided and far-field (smooth) velo city and pressure information is used. We re-visit the approach to compute hydrodynamic forces and torques through force/torque balance equations in a Lagrangian frame that some of us took in a prior work (Bhalla et al., 2013 [13]). We prove the equivalence of the two approaches for IB methods, thanks to the use of Peskin's delta functions. Both approaches are able to suppress spurious force oscillations and are in excellent agreement, as expected theoretically. Test cases ranging from Stokes to high Reynolds number regimes are considered. We discuss regridding issues for the moving CV method in an adaptive mesh refinement (AMR) context. The proposed moving CV method is not limited to a specific IB method and can also be used, for example, with embedded boundary methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Algorithms and data structure↗

Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration

Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies.

97 MATHEMATICS AND COMPUTING↗

A new database website for nuclear level densities

We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. Here, this platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations. These simulations have often been tied to one platform and restricted in generality by the interface provided to the user. The expanding prevalence of accelerators and researcher demands necessitate a more general approach which is not tied to specific hardware or requires contortion of algorithms to specific hardware platforms. In this paper we present COMET, a domain-specific programming language and compiler infrastructure for tensor contractions targeting heterogeneous accelerators. We present a system of progressive lowering through multiple layers of abstraction and optimization that achieves up to 1.98×speedup for 30 tensor contractions commonly used in computational chemistry and beyond.

Mutlu, Erdal↗

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗

Adsorption, Orientation, and Speciation of Amino Acids at Air–Aqueous Interfaces for the Direct Air Capture of CO 2

Amino acids make up a promising family of molecules capable of direct air capture (DAC) of CO 2 from the atmosphere. Under alkaline conditions, CO 2 reacts with the anionic form of an amino acid to produce carbamates and deactivated zwitterionic amino acids. The presence of the various species of amino acids and reactive intermediates can have a significant effect on DAC chemistry, the role of which is poorly understood. In this study, all-atom molecular dynamics (MD) based computational simulations and vibrational sum frequency generation (vSFG) spectroscopy studies were conducted to understand the role of competitive interactions at the air–aqueous interface in the context of DAC. We find that the presence of potassium bicarbonate ions, in combination with the anionic and zwitterionic forms of amino acids, induces concentration and charge gradients at the interface, generating a layered molecular arrangement that changes under pre- and post-DAC conditions. In parallel, an enhancement in the surface activity of both anionic and zwitterionic forms of amino acids is observed, which is attributed to enhanced interfacial stability and favorable intermolecular interactions between the adsorbed amino acids in their anionic and zwitterionic forms. The collective influence of these competitive interactions, along with the resulting interfacial heterogeneity, may in turn affect subsequent capture reactions and associated rates. Finally, these effects underscore the need to consider dynamic changes in interfacial chemical makeup to enhance DAC efficiency and to develop successful negative emission and storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗