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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.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗
DOE OSTI2025

Versatile system for ion energy measurements generated by pulsed laser ionization: Insights into electron-ion dynamics

Ion energy distributions generated by pulsed laser interactions with materials are essential for applications ranging from materials science to oncology. Ion energy characterization is particularly important for an emerging mass spectrometry technique called virtual-slit cycloidal mass spectrometry (VS-CMS). The ion energy distribution influences the design and performance of VS-CMS instruments, as well as the efficacy of laser-driven ionization methods in various fields. Several established techniques, including the retarding potential method, time-of-flight (TOF) analysis, and electrostatic energy analyzers, have been employed to measure ion energy distributions. The wide range of ion energies reported highlights the strong dependence of ion energy on laser parameters, target materials, and experimental conditions, as well as the necessity of making independent measurements of the ion energy distribution for specific laser systems and materials. This paper presents the design and characterization of a simple TOF-based apparatus for measuring ion energy distributions from pulsed laser ionization without external fields. This approach minimizes perturbation of electron-ion dynamics and enables simultaneous energy measurements at multiple spatial positions. Here, the apparatus was tested using a nanosecond pulsed Nd:YAG laser operating at 1064 nm, 532 nm, and 266 nm on solid copper sheets at various laser fluences. Simultaneous measurements at different distances provide new insights into ion-electron interactions post-ionization and demonstrate the influence of laser wavelength and fluence on ion energy distributions.

Ion energy↗
DOE OSTI2021

Cubic to hexagonal tuning in Fe 2 Mn(Si 1– x Ge x ) Heusler alloys

Here, the competition between the stability of the cubic and hexagonal full Heusler alloys and the implications concerning their magnetic properties were systematically studied through the detailed structural and magnetic characterization of the Fe 2 Mn(Si 1– x Ge x ) system. This system was specifically chosen as the parent compositions are cubic ( x = 0) and hexagonal ( x = 1). It is found that the formation of hexagonal phases occurs for the x ≥ 0.6 samples, whereas its phase fraction monotonically increases with x until the pure hexagonal Fe 2 MnGe is formed. The change in structure results in high sensitiveness of both the saturation of magnetization ($M_S$) and Curie temperature ($T_C$) with x values, related to a strong magnetocrystalline anisotropy of the hexagonal phase. Both cubic and hexagonal magnetic features were qualitatively reproduced by Density Functional Theory (DFT) calculations. This work provides an experimental and theoretical foundation for further design of Heusler systems with controlled structures and magnetic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

Addressing performance portability across diverse accelerator architectures has emerged as a major challenge in the development of application and programming systems for high-performance computing environments. Although recent programming systems that focus on performance portability have significantly improved productivity in an effort to meet this challenge, the problem becomes notably more complex when compute nodes are equipped with multiple accelerator types—each with unique performance attributes, optimal data layout, and binary formats. To navigate the intricacies of multi-accelerator programming, we propose CHARM-SYCL as an extension of our CHARM multi-accelerator execution environment [27]. This environment will combine our SYCL-based performance-portability programming front end with a back end for extremely heterogeneous architectures as implemented with the IRIS runtime from Oak Ridge National Laboratory. Our preliminary evaluation indicates potential productivity boost and reasonable performance compared to vendor-specific programming system and runtimes.

Fujita, Norihisa↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2022

Advancing Post-Combustion CO 2 Capture through Increased Mass Transfer and Lower Degradation

The over-arching goal of the proposed project is to develop three techniques to enable aqueous post-combustion CO 2 capture technologies to meet the DOE performance and cost targets of 90% CO 2 capture, 95% purity, at a cost of less than $30/tonne CO 2 captured. This will be accomplished by the development of materials and processes to increase mass transfer in the absorber and reduce the environmental impacts. While constantly working to reduce the cost of CO 2 capture via solvent development and process & heat integration, increasing CO 2 mass transfer through development of custom dynamic packing materials and tuning solvent physical properties may offer a route to increased solvent capacity, lower energy consumption and reduced aerosol formation. The environmental concerns that have been identified in amine-based CO 2 capture systems, nitrosamines specifically, are another critical element that will be addressed in this project. The specific objectives of the project were to: 1) conduct detailed studies to understand how solvent physical properties and aerosol formation are impacted by additives; 2) quantify the CO 2 mass transfer improvement from the dynamic polarity packing in the absorber and the additive-modified solvent using the existing UK bench-scale CO 2 capture unit; 3) quantify the energy consumption savings associated with enhanced mass transfer; 4) quantify the benefits of the UK’s electrochemical cell to decompose nitrosamines; and 5) collect the necessary information/data to conduct a high-level TEA assessment of the proposed technologies. The project involved the fabrication and installation of customized dynamic polarity packing and an investigation into the understanding of the impact of chemical additives on solvent properties to increase CO 2 mass transfer in the absorber column, and lastly the design of an electrochemical cell to decompose nitrosamines in a water wash. After both systems were fabricated, they were tested at UK facilities, including on the bench-scale CO 2 capture unit under parametric and long-term operation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Empirically verified analysis of dual pre-cooling system for hydrogen refuelling station

The dual cooling system at the California State University Los Angeles Hydrogen Research and Fueling Facility is analysed to predict the output hydrogen temperature in different ambient conditions. Initially, the facility was built with a coil chiller T20 cooling, sufficient for occasional fuelings. A flat plate evaporator system was added in series to resolve any issues for multiple fuelings even in the hottest weather. This study was commenced to verify the set points and determine the control requirements for the dual setup in order to inform future designs. A numerical-empirical model of the cooling system was developed by reverse engineering, using the station experimental measurements and database records. The subsystems are characterized separately but validated as a whole system imposing specific and standard operating conditions. The cooling model is tested with different inputs to validate the pre-set parameter variation of the cooling components. Ten scenarios were investigated to evaluate the fueling output parameters, testing two hydrogen temperature input trends (according to the facility initial conditions) and five ambient temperatures (from 15 °C to 35 °C). In closing, the simulation results have confirmed that the hydrogen output temperature remains within the range imposed by the SAE J2601 for each scenario studied, around -22 °C and -25 °C.

08 HYDROGEN↗
DOE OSTI2025

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗
DOE OSTI2022

Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys

We report Bayesian Optimization (BO) has emerged as a powerful framework to efficiently explore and exploit materials design spaces. To date, most BO approaches to materials design have focused on the materials discovery problem as if it were a single expensive-to-query ‘black box’ in which the target is to optimize a single objective (i.e., material property or performance metric). Also, such approaches tend to be constraint agnostic. Here, we present a novel multi-information BO framework capable of actively learning materials design as a multiple objectives and constraints problem. We demonstrate this framework by optimally exploring a Refractory Multi-Principal-Element Alloy (MPEA) space, here specifically, the system Mo-Nb-Ti-V-W. The MPEAs are explored to optimize two density-functional theory (DFT) derived ductility indicators (Pugh’s Ratio and Cauchy pressure) while learning design constraints relevant to the manufacturing of high-temperature gas-turbine components. Alloys in the BO Pareto-front are analyzed using DFT to gain an insight into fundamental atomic and electronic underpinning for their superior performance, as evaluated within this framework.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Heterogeneous fatigue damage in a nickel-based single-crystal superalloy unraveled using correlative 3D X-ray technology

Nickel-based single-crystal (Ni-SX) superalloys under cyclic stress are susceptible to cracking at stress-concentration sites, eventually leading to low-cycle fatigue (LCF) failure. LCF cracks typically originate from intrinsic defects (e.g., voids and carbides) within solidified dendrites. However, systematic quantitative experimental analyses of defect-mediated local damage remain limited. To thoroughly understand the microscopic origins and evolution of LCF damage, correlated 3D mapping of dendrites across various regions is essential. Here, in this study, macroscale micro-computed tomography (μ-CT) was initially used to capture internal interdendritic secondary cracks within bulk DD413 superalloy after LCF testing at 760 °C. Subsequently, a multimodal methodology combining synchrotron 3D microdiffraction (3D-μXRD), high-resolution μ-CT, and electron microscopy was established. This approach allowed precise localization of internal damage zones near interdendritic secondary cracks and detailed mapping of the 3D correlated distributions of dendrites, defects, and residual stress/strain fields within these zones at submicron spatial resolution. Finally, the same approach was applied to specimens subjected to interrupted loading at approximately 40 % of the fatigue life to uncover the early damage states of dendrites. The dendrite cores (DCs) and interdendritic regions (IDs) exhibit microscale heterogeneous mechanical responses: nearly defect-free DCs accumulate local irreversible slip along specific slip systems to generate slip bands, while the IDs containing various defects accommodate local microplasticity through the activation of multiple slip systems around these defects. The local tensile stress near defects in the IDs exceeds that in the DC slip band regions by more than threefold, leading to the generation of local damage zones within the IDs. Chain-like defect distributions facilitate the interconnection of these local zones into a continuous damage region, further elevating the overall tensile stress in the IDs. Additionally, geometrically necessary dislocations alone are insufficient as indicators of LCF damage; both the internal stress state and its magnitude must be considered. These experimental results provide critical data and insights for the development of multi-physics fatigue models.

Localized deformation↗
DOE OSTI2022

Design and evaluation of novel analogs of 2-amino-4-boronobutanoic acid (ABBA) as inhibitors of human gamma-glutamyl transpeptidase

Inhibitors of gamma-glutamyl transpeptidase (GGT1, aka gamma-glutamyl transferase) are needed for the treatment of cancer, cardiovascular illness and other diseases. Compounds that inhibit GGT1 have been evaluated in the clinic, but no inhibitor has successfully demonstrated specific and systemic GGT1 inhibition. All have severe side effects. L-2-amino-4-boronobutanoic acid (l-ABBA), a glutamate analog, is the most potent GGT1 inhibitor in vitro. In this study, we have solved the crystal structure of human GGT1 (hGGT1) with ABBA bound in the active site. The structure was interrogated to identify interactions between the enzyme and the inhibitor. Based on these data, a series of novel ABBA analogs were designed and synthesized. Their inhibitory activity against the hydrolysis and transpeptidation activities of hGGT1 were determined. The lead compounds were crystalized with hGGT1 and the structures solved. The kinetic data and structures of the complexes provide new insights into the critical role of protein structure dynamics in developing compounds for inhibition of hGGT1.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Who is marginalized in energy justice? Amplifying community leader perspectives of energy transitions in Ghana

There is a divide in energy access studies, between technologically-focused modeling papers in engineering and economics, and energy justice frameworks and principles grounded in social sciences. Quantitative computational models are necessary when analyzing energy, and more specifically electricity, systems, as they are technologically-complex systems that can diverge from intuitive patterns. To assure energy justice, these models must be reflective of, and informative to, a wide range of stakeholders, including households and communities alongside utilities, governments, and others. Yet, moving from a qualitative understanding of preferences to quantitative modeling is challenging. In this perspective piece, we pilot the use of the value-focused thinking framework to inform stakeholder engagement. The result is a strategic objective hierarchy that highlights the tradeoffs and the social, economic and technological factors that need to be measured in models. We apply the process in Ghana, using a survey, stakeholder workshops, and follow-up interviews to uncover key tradeoffs and stakeholder-derived objectives. We discuss three key areas that have been rarely, if ever, well-represented in energy models: (1) the relationship between the dynamics of electricity end-use and the technology and economic structure of the system; (2) explicit tradeoffs between electricity access, cost, and reliability as defined by stakeholders; and (3) the definition of new objectives, such as minimizing hazards related to theft. We conclude that this model of engagement provides an opportunity to tie together rigorous qualitative analysis and stakeholder engagement with crucial quantitative models of the electricity system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

On the broadband vibration isolation performance of nonlocal total-internal-reflection metasurfaces

The concept of a nonlocal elastic metasurface has been recently proposed and experimentally demonstrated in Zhu et al. (2020). When implemented in the form of a total-internal-reflection (TIR) interface, the metasurface can act as an elastic wave barrier that is impenetrable to deep subwavelength waves over an exceptionally wide frequency band. The underlying physical mechanism capable of delivering this broadband subwavelength performance relies on an intentionally nonlocal design that leverages long-range connections between the units forming the fundamental supercell. This paper explores the design and application of a nonlocal TIR metasurface to achieve broadband passive vibration isolation in a structural assembly made of multiple dissimilar elastic waveguides. The specific structural system comprises shell, plate, and beam waveguides, and can be seen as a prototypical structure emulating mechanical assemblies of practical interest for many engineering applications. The study also reports the results of an experimental investigation that confirms the significant vibration isolation capabilities afforded by the embedded nonlocal TIR metasurface. We report these results are particularly remarkable because they show that the performance of the nonlocal metasurface is preserved when applied to a complex structural assembly and under non-ideal incidence conditions of the incoming wave, hence significantly extending the validity of the results presented in Zhu et al. (2020). Results also confirm that, under proper conditions, the original concept of a planar metasurface can be morphed into a curved interface while still preserving full wave control capabilities.

42 ENGINEERING↗
DOE OSTI2022

A systematic study and framework of fringe projection profilometry with improved measurement performance for in-situ LPBF process monitoring

Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. Here, in this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM.

42 ENGINEERING↗
DOE OSTI2020

Combining Computational Modeling with Reaction Kinetics Experiments for Elucidating the In Situ Nature of the Active Site in Catalysis

Microkinetic modeling based on density functional theory (DFT) derived energetics is important for addressing fundamental questions in catalysis. The quantitative fidelity of microkinetic models (MKMs), however, is often insufficient to conclusively infer the mechanistic details of a specific catalytic system. Here, this can be attributed to a number of factors such as an incorrect model of the active site for which DFT calculations are performed, deficiencies in the hypothesized reaction mechanism, inadequate consideration of the surface environment under reaction conditions, and intrinsic errors in the DFT exchange-correlation functional. Despite these limitations, we aim at developing a rigorous understanding of the reaction mechanism and of the nature of the active site for heterogeneous catalytic chemistries under reaction conditions. By achieving parity between experimental and modeling outcomes through robust parameter estimation and by ensuring coverage-consistency between DFT calculations and MKM predictions, it is possible to systematically refine the mechanistic model and, thereby, our understanding of the catalytic active site in situ.

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

Understanding Gas Solubility of Pure Component and Binary Mixtures within Multivalent Ionic Liquids from Molecular Simulations

Understanding the molecular-level solubility of CO 2 and its mixtures is essential to the progress of gas treating technologies. Herein, we use grand canonical Monte Carlo simulations to study the single component gas absorption of SO 2 , N 2 , CH 4 , and H 2 , and binary mixtures of CO 2 /SO 2 , CO 2 /N 2 , CO 2 /CH 4 , and CO 2 /H 2 of varying mole fractions within multivalent ionic liquids (ILs). Our results highlight the importance of the free volume effect and the anion effect when interpreting the absorption behavior of these mixtures, similar to the behavior of CO 2 found in our previous study. The deviation of the gas solubility between the pure component absorption versus the binary absorption, as well as the solubility selectivity, highlight the importance of the relative affinity of gas species within a mixture to the different anions. Further, the absorption selectivity within a specific IL system can be predicted based on the relative gas affinity to the anion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗
DOE OSTI2025

Doping Effects on Multivalence States, Electronic Structure, and Optical Band Gap in LaCrO 3 under Varied Atmospheres: An Integrated Experimental and Density Functional Theory Study

Doping effects on the valence state, electronic structure, and optical band and the effects on electrical conductivity were studied on the doped lanthanum chromite (LaCrO 3 ) system. The specific compositions studied were La 1–x Ca x CrO 3 (LCCx), La 1–x Sr x CrO 3 (LSCx), and La 0.8 Sr 0.2 Cr 1–x Mn x O 3 (LSCMx) (0.1 ≤ x ≤ 0.4). The powders were synthesized using a modified Pechini sol–gel method, and the ceramic samples were densified using a reactive sintering method resulting in densities >96% theoretical. X-ray photoelectron spectroscopy (XPS) was completed to characterize the defect states and cationic valence compensation as a result of divalent (Ca 2+ or Sr 2+ ) and trivalent (Mn 3+ ) substitutions. XPS was completed for samples tested in oxidizing and reducing atmospheres (up to 1500 °C), which provided insights into the oxidation state transitions induced by the Ca 2+ and Sr 2+ dopants. The work notably demonstrated, for the first time, the oxidation/reduction transitions of Cr 4+ to Cr 3+ in Sr 2+ /Mn 3+ co-doped samples under reducing atmospheres. Reflectance UV–vis spectrophotometry optical band gap measurements were also completed for the same materials; a decrease in the optical band gap (2.81–3.12 eV) was shown with increased substitution, suggesting electronic structure modifications in the LaCrO 3 perovskite. Density functional theory calculations validated experimental trends, predicting a diminishing band gap with a rising dopant concentration. The transition in Cr oxidation states was attributed to the presence of divalent/trivalent cations. These findings contribute some insights into methods to tune the LaCrO 3 electrical properties for various low- and high-temperature applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗