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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Efficient and mechanically-robust organic solar cells based on vertical stratification modulation through sequential blade-coating

Mechanically durable organic solar cells (OSCs) with high efficiency are deemed as the ideal candidate for the power source of the next generation wearable electronic devices. However, the brittle nature of small molecules in most high-efficiency OSCs consisting of polymer and small molecule encourages easy formation of cracks in the photoactive film under deformation. Here, the vertical composition distribution of the active layer has been well optimized through sequential blade coating to realize highly deformable while efficient OSC. The optimized morphology exhibits distinct donor-rich and homogenous region distributed along the vertical direction in the bulk. The donor-rich region provides sufficient chain entanglements and strong interfaces beneficial for mechanical robustness of film, while homogeneously mixed region offers continuous interpenetrating network to maintain high device through-put, resulting in superior efficiency of 14.4% with high crack-onset strain (COS) of 30.5%. This efficiency versus COS combination is much higher than the best combination reported in all polymer systems (COS of 15.9% and efficiency of 11.1%). To the best of our knowledge, it is the highest COS value achieved in polymer-small molecule systems. As a result, the rational control over vertical stratification demonstrated here would guide researchers in the development of innovative wearable electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sequential Infiltration Synthesis of Multinary Metal Oxides: The Role of Precursor Diffusion and Reactivity

Understanding volatile metal–organic precursor transport in polymer matrices during sequential infiltration synthesis (SIS) is critical to the design of hybrid materials of tailored composition and uniform structure. Here, we investigate the diffusion and reaction behavior of diethylzinc (DEZ) in poly(methyl methacrylate) (PMMA) matrices with variable indium and zinc incorporation. Unlike conventional SIS where precursors adduct or react directly with the polymer backbone, DEZ shows minimal interaction with PMMA. However, DEZ may interact strongly with In–OH or Zn–OH moieties that are previously incorporated into a PMMA thick film. Using spectroscopic ellipsometry, X-ray photoelectron spectroscopy depth profiling, and EDX line scans, we quantify Zn incorporation as a function of exposure time, polymer thickness, and previous infiltration steps. The Zn distribution evolves from surface-localized to deep within the ∼1 μm thick film with increasing DEZ exposures up to 30 min. A reaction-diffusion model incorporating a hindering factor to capture diffusivity decay due to product accumulation reproduces the Zn depth profile and yields physically meaningful parameters to guide future growth. Furthermore, this study provides a framework for interpreting metal–organic precursor infiltration behavior and highlights the utility of model-guided SIS process design.

diethylzinc↗
DOE OSTI2020

Leveraging Sequential Doping of Semiconducting Polymers to Enable Functionally Graded Materials for Organic Thermoelectrics

With the ability to modulate electronic properties through molecular doping coupled with ease in processability, semiconducting polymers are at the forefront in enabling organic thermoelectric devices for thermal energy management. In contrast to uniform thermoelectric material properties, an alternative route focuses on functionally graded materials (FGMs) where one spatially controls and optimizes transport properties across the length of a thermoelectric material. While primarily studied in the context of inorganic materials, the concept of FGMs for organic thermoelectrics has not been explored. Herein, we introduce how molecular doping of semiconducting polymers enables spatial compositional control of thin-film FGMs. Specifically, we utilize sequential vapor doping of poly[2,5-bis(3-tetradecylthiophen-2-yl) thieno [3,2-b]thiophene] (PBTTT) with the small molecule acceptor 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) to fabricate the simplest form of FGMs – double- segmented thin films. The two thin-film segments are of equal length (7.5 mm), but each set to different doping levels. Our study focuses on understanding the thermoelectric properties (Seebeck coefficient, α, and electronic conductivity, σ) and structural properties (through X-ray scattering, UV-vis-NIR spectroscopy, and Raman spectroscopy) within and across the two segments. We observe the presence of a small diffuse interfacial region of 0.5 – 1 mm between the two segments where the doping level and transport properties vary continuously. Despite the diffuse interface, the measured effective Seebeck coefficient (αeff) across the two segments is simply the average of α within each segment. Importantly, this experimental result is consistent with reported mathematical models describing αeff in graded thermoelectric materials. Finally, our results demonstrate the facile fabrication and characterization of functionally graded organic thermoelectric materials, providing guidelines for further development on more complex FGMs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Swelling-Assisted Sequential Infiltration Synthesis of Nanoporous ZnO Films with Highly Accessible Pores and Their Sensing Potential for Ethanol

Here, we report a swelling-assisted sequential infiltration synthesis (SIS) approach for the design of highly porous zinc oxide (ZnO) films by infiltration of block copolymer templates such as polystyrene-block- polyvinyl pyridine with inorganic precursors followed by UV ozone-assisted removal of the polymer template. We show that porous ZnO coatings with the thickness in the range between 140 and 420 nm can be obtained using only five cycles of SIS. The pores in ZnO fabricated via swelling-assisted SIS are highly accessible, and up to 98% of pores are available for solvent penetration. The XPS data indicate that the surface of nanoporous ZnO films is terminated with -OH groups. Density functional theory calculations show a lower energy barrier for ethanol-induced release of the oxygen restricted depletion layer in the case of the presence of -OH groups at the ZnO surface, and hence, it can lead to higher sensitivity in sensing of ethanol. We monitored the response of ZnO porous coatings with different thicknesses and porosities to ethanol vapors using combined mass-based and chemiresistive approaches at room temperature and 90 °C. The porous ZnO conformal coatings reveal a promising sensitivity toward detection of ethanol at low temperatures. In conclusion our results suggest the excellent potential of the SIS approach for the design of conformal ZnO coatings with controlled porosity, thickness, and composition that can be adapted for sensing applications.

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

Sequential Infiltration Synthesis (SIS) of In 2 O 3 -Based Porous Photoelectrodes for Molecular Sensitization

High-surface-area photoelectrodes are highly desirable for solar energy conversion applications, particularly in systems where surface-bound molecular chromophores are responsible for light absorption. To this end, porous Indium-Zinc-Oxide (IZO) frameworks are fabricated via Sequential Infiltration Synthesis (SIS) into poly(methyl methacrylate) (PMMA) films followed by air annealing. A more complete understanding of the multimetal infiltration process conditions and postannealing temperature allows for precise control of zinc (Zn) incorporation to afford porous, conductive, transparent, and amorphous photoelectrodes. Uniform incorporation of both indium (In) and Zn is found to require extended diethylzinc (DEZ) exposures to compensate for remarkably slow precursor diffusion in the presence of indium oxyhydroxide nuclei. SIS-fabricated IZO photoelectrodes are structurally robust, electrochemically active, and exhibit dye adsorption that suggest practical surface area enhancements greater than 100×. In conclusion, these attributes establish SIS as a rapid, scalable, and reproducible route to photoelectrodes for solar energy conversion and hybrid interface characterization.

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

Controlling Nanoscale Pore Size and Wall Composition in Polycarbonate Membranes via Atomic Layer Deposition and Sequential Infiltration Synthesis: Implications for High Water Permeance

Polymer membranes have a wide variety of applications, ranging from water treatment to energy storage. Many of these applications require precise control over the membrane porosity and surface chemistry. In this study, we explore the modification of isoporous polycarbonate (PC) track-etched membranes (PCTEs) by atomic layer deposition (ALD) and sequential infiltration synthesis (SIS) to tune the pore size and the pore wall surface chemistry. We first performed a detailed study of Al 2 O 3 ALD and SIS in PCTE using a variety of in situ and ex situ measurements. We discovered that short precursor exposure times are critical to achieve conformal Al 2 O 3 ALD in the PCTE nanopores, while longer precursor exposure times resulted in Al 2 O 3 SIS within the bulk of the PC leaving the membranes brittle. Next, we tuned the PCTE pore size via Al 2 O 3 ALD and studied its effect on the water contact angle and the water permeance. Here, we found that the membranes became more hydrophilic, and the permeance decreased with increasing ALD Al 2 O 3 cycles. Finally, we studied the effect of hydrophilic (SnO 2 )/hydrophobic (In 2 O 3 ) ALD metal oxide coatings on membrane properties. We found that the most hydrophilic SnO 2 showed the highest water flux and the least hydrophilic In 2 O 3 showed the lowest water flux through the PCTE membranes. Our results demonstrate that ALD is an effective method to tune the surface and transport properties of PCTE membranes, but care must be exercised to avoid SIS and bulk modification of the polymer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Polycaprolactone: A Promising Addition to the Sequential Infiltration Synthesis Polymer Family Identified through In Situ Infrared Spectroscopy

Infiltration of inorganic oxides inside polymers using sequential infiltration synthesis (SIS) is an effective method for creating materials for a broad range of applications. The reactions between various polymer functional groups and organometallic/inorganic precursors are unique, which makes it essential to understand the specific interactions for a range of precursors and polymers to enable predictive process design and to extend the utility of SIS to applications. In this paper, in situ Fourier transform infrared spectroscopy (FTIR) measurements have been performed during Al 2 O 3 and TiO 2 SIS in three different homopolymers: poly(methyl methacrylate) (PMMA), poly(epsilon-caprolactone) (PCL), and poly(2-vinylpyridine) (P2VP). From the FTIR intensity changes after precursor exposure and during the subsequent purge times, it is demonstrated quantitatively that the interaction dynamics and the stability of the intermediate complexes of these polymers with the metal precursors are substantially different. A key finding from this comparative study is that PCL interacts far more strongly with metal precursors, even though its carbonyl (C=O) and ester (C-O-R) functional groups are similar to those of the more weakly interacting PMMA. This behavior suggests that additional factors beyond the identity of the functional groups dictate how polymers interact with metal compounds in SIS. PCL, which has not previously been reported in SIS processes, may be an attractive polymeric template for implementing SIS with improved uniformity and cost-effectiveness.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of Sequentially Extracted Soil Organic Matter by Electrospray Ionization and Atmospheric Pressure Photoionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Soil organic matter (SOM) is a complex mixture of small molecules and biopolymers that are active in various biogeochemical processes. However, the chemical diversity of biopolymer-derived SOM remains poorly explored. Identifying this diversity is important because global environmental changes may well alter SOM chemistry, as field experiments are beginning to show. Here, organic solvent-extractable (DcMe-SOM), base-hydrolyzable (KOH Hy -SOM), and CuO-oxidizable (CuO Ox -SOM) SOM fractions from a forest with a long-term nitrogen addition experiment were sequentially extracted and characterized by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) coupled with negative-ion electrospray ionization (ESI) or atmospheric pressure photoionization (APPI). From DcMe-SOM to CuO Ox -SOM, the total number of assigned formulas, average O/C ratio, aromaticity, and unsaturation degree of SOM continuously increased, while the average m/z and H/C ratio decreased. Moreover, the dominant chemical category shifted from lipid-like components to phytochemical- and protein-like components. Complementary to ESI, APPI effectively facilitated detection of additional compounds with low polarity. With long-term nitrogen addition, the average m/z, unsaturation degree, aromaticity, and oxidation state of SOM increased, and more aromatic nitrogen-containing formulas were detected in CuOOx-SOM. Our study demonstrates that chronic nitrogen deposition in forests alters both the small molecules and biopolymers of SOM fundamentally.

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

Nanoporous Dielectric Resistive Memories Using Sequential Infiltration Synthesis

Resistance switching in metal–insulator–metal structures has been extensively studied in recent years for use as synaptic elements for neuromorphic computing and as nonvolatile memory elements. However, high switching power requirements, device variabilities, and considerable trade-offs between low operating voltages, high on/off ratios, and low leakage have limited their utility. Here, we have addressed these issues by demonstrating the use of ultraporous dielectrics as a pathway for high-performance resistive memory devices. Using a modified atomic layer deposition based technique known as sequential infiltration synthesis, which was developed originally for improving polymer properties such as enhanced etch resistance of electron-beam resists and for the creation of films for filtration and oleophilic applications, we are able to create ~15 nm thick ultraporous (pore size ~5 nm) oxide dielectrics with up to 73% porosity as the medium for filament formation. We show, using the Ag/Al 2 O 3 system, that the ultraporous films result in ultrahigh on/off ratio (>10 9 ) at ultralow switching voltages (~±600 mV) that are 10× smaller than those for the bulk case. In addition, the devices demonstrate fast switching, pulsed endurance up to 1 million cycles. and high temperature (125 °C) retention up to 10 4 s, making this approach highly promising for large-scale neuromorphic and memory applications. Additionally, this synthesis methodology provides a compatible, inexpensive route that is scalable and compatible with existing semiconductor nanofabrication methods and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Resolving the Atomic Structure of Sequential Infiltration Synthesis Derived Inorganic Clusters

Sequential infiltration synthesis (SIS) is a route to the precision deposition of inorganic solids in analogy to atomic layer deposition but occurs within (vs upon) a soft material template. SIS has enabled exquisite nanoscale morphological complexity in various oxides through selective nucleation in block copolymers templates. However, the earliest stages of SIS growth remain unresolved, including the atomic structure of nuclei and the evolution of local coordination environments, before and after polymer template removal. We employed In K-edge extended X-ray absorption fine structure and atomic pair distribution function analysis of high-energy X-ray scattering to unravel (1) the structural evolution of InO x H y clusters inside a poly(methyl methacrylate) (PMMA) host matrix and (2) the formation of porous In 2 O 3 solids (obtained after annealing) as a function of SIS cycle number. Early SIS cycles result in InO x H y cluster growth with high aspect ratio, followed by the formation of a three-dimensional network with additional SIS cycles. That the atomic structures of the InO x H y clusters can be modeled as multinuclear clusters with bonding patterns related to those in In 2 O 3 and In(OH) 3 crystal structures suggests that SIS may be an efficient route to 3D arrays of discrete-atom-number clusters. As a result, annealing the mixed inorganic/polymer films in air removes the PMMA template and consolidates the as-grown clusters into cubic In 2 O 3 nanocrystals with structural details that also depend on SIS cycle number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Selective sequential infiltration synthesis of ZnO in the liquid crystalline phase of silicon-containing rod-coil block copolymers

The combination of block copolymer (BCP) thin film self-assembly and selective infiltration synthesis of inorganic materials into one BCP block provides access to various organic–inorganic hybrids. Here, we apply sequential infiltration synthesis, a vapor-phase hybridization technique, to selectively introduce ZnO into the organic microdomains of silicon-containing rod-coil diblock copolymers and a triblock terpolymer, polydimethylsiloxane (PDMS)-b-poly{2,5-bis[(4-methoxyphenyl)-oxycarbonyl]styrene} (PDMS-b-PMPCS) and PDMS-b-polystyrene-b-PMPCS (PDMS-b-PS-b-PMPCS), in which the PMPCS rod block is a liquid crystalline polymer. The in-plane cylindrical PDMS-b-PMPCS and core–shell cylindrical and hexagonally perforated lamellar PDMS-b-PS-b-PMPCS films were infiltrated with ZnO with high selectivity to the PMPCS. The etching contrast between PDMS, PS and the ZnO-infused PMPCS enables the fabrication of ZnO/SiO x binary composites by plasma etching and reveals the core–shell morphology of the triblock terpolymer.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sequential Kalman tuning of the t -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. Here, in this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Multi-Armed Bayesian Ordinal Outcome Utility-Based Sequential Trial with a Pairwise Null Clustering Prior

A multi-armed trial based on ordinal outcomes is proposed that leverages a flexible non-proportional odds cumulative logit model and numerical utility scores for each outcome to determine treatment optimality. This trial design uses a Bayesian clustering prior on the treatment effects that encourages the pairwise null hypothesis of no differences between treatments. A group sequential design is proposed to determine which treatments are clinically different with an adaptive decision boundary that becomes more aggressive as the sample size or clinical significance grows, or the number of active treatments decreases. A simulation study is conducted for 3 and 5 treatment arms, which shows that the design has superior operating characteristics (family wise error rate, generalized power, average sample size) compared to utility designs that do not allow clustering, a frequentist proportional odds model, or a permutation test based on empirical mean utilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of a framework for sequential Bayesian design of experiments: Application to a pilot-scale solvent-based CO 2 capture process

In this paper, a methodology is developed for sequential design of experiments (SDoE) for process systems and applied to a solvent-based CO 2 capture system. In this approach, the prior knowledge of the system is used to prioritize process data collection at specific operating conditions. These data are then incorporated into a Bayesian inference methodology for updating a stochastic model by refining estimations of its underlying parameters, and the updated model is then used to generate the next set of test runs. Thus, the new knowledge obtained from the data is used to guide subsequent iterations of the experimental runs, ensuring that the overall data collection is maximally informative given that most experimental campaigns, especially at pilot or higher-scale plants, are costly, time-consuming, and resource-limited. The test run objective for this work was to minimize the maximum model prediction uncertainty for key output variables, but the methodology is generic and can be readily applied to other test run objectives. This methodology is applied to an aqueous monoethanolamine (MEA) pilot plant campaign at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama, USA. The SDoE framework was utilized for two iterations, while collecting 18 sets of data representing different process conditions, and this resulted in an overall average reduction in uncertainty of approximately 50% in the prediction of CO 2 capture percentage. Moreover, 11 additional data sets were obtained with variation of absorber packing height for further model validation. This work shows the capability of the SDoE framework to maximize learning given limited resources, allowing for the reduction of model uncertainty, which is of great importance for many applications including reduction of technical risk associated with scale-up and economic analysis.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Sequential Infiltration Synthesis of Cadmium Sulfide Discrete Atom Clusters

Abstract Exposure of soft material templates to alternating volatile chemical precursors can produce inorganic deposition within the permeable template (e.g. a polymer thin film) in a process akin to atomic layer deposition (ALD). While such sequential infiltration synthesis (SIS) processes have now been demonstrated for many metal oxides, we report an SIS process for a transition metal sulfide – CdS. Gas phase dimethyl cadmium and hydrogen sulfide precursors infiltrated into poly(4‐vinylpyridine) thin films result in the 3D‐nucleation of clusters consistent with a cubane‐type Cd 4 S 4 core that are variably terminated with methyl, thiol and hydroxy capping ligands. First principles models and simulation of few‐atom Cd‐based clusters are consistent with electronic and vibrational spectroscopy and grazing‐incidence total X‐ray scattering measurements of 3D‐cluster‐arrays synthesized at 80 °C. The direct synthesis of few‐atom transition metal sulfide clusters within polymer thin films will provide a versatile new route to precision architectures for light‐absorbing materials including solar energy harvesting and conversion applications.

Jayaweera, Nuwanthaka P. [Material Science Divisio↗
DOE OSTI2026

Selective Sequential Depolymerization of Mixed Plastics Mediated by Photothermal Conversion

Chemical recycling of plastics into monomers is a promising strategy to achieve a circular economy. However, selective depolymerization methods for mixed plastics are still underdeveloped. Herein, we report a selective and sequential depolymerization strategy for mixed plastics, including poly(L-lactide) (PLLA), polystyrene (PS), and poly(ethylene terephthalate) (PET), using photothermal conversion. We were able to selectively depolymerize PLLA into L-lactide in the presence of PS and PET. Then, PS was selectively depolymerized to styrene, followed by the depolymerization of PET into its monomer. Our protocol was carried out in one pot without any additional purification of the unreacted plastics at each stage. This method was successfully applied to mixtures of post-consumer waste plastic.

carbon black↗
DOE OSTI2023

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography ( MSOT ) imaging

Abstract Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through‐plane resolution volumetric MSOT is time‐consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross‐sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG‐conjugated nanoworms particles (NWs‐ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

Juhong, Aniwat↗
DOE OSTI2022

Tailoring compatibilization potential of maleic anhydride–grafted polypropylene by sequential rheochemical processing of polypropylene and polyamide 66 blends

Reactive compatibilization of immiscible polymer blends using a preferred compatibilizer leaves the following question: How much loading of a compatibilizer is good enough and what maximum properties can be achieved? A good understanding of the process can help solve the reutilization of mixed waste plastics. Here, the reactive compatibilization of polypropylene-graft-maleic anhydride (PP-g-MAH) on polypropylene/polyamide 66 (PP/PA66) blends is quantitatively assessed using thermorheological, microoptical, spectroscopic, and x-ray scattering-based characterization tools. The overall compositions of all PP(60%)/PA66(30%)/PP-g-MAH(10%) blends are kept constant while systematically controlling the degree of the chemical reaction by varying the sequential addition of PP-g-MAH to the melt mixture. The first feeding of PP-g-MAH (x%, 0 ≤ x ≤ 10) is conducted at 280°C and the second feeding of (10–x)% is at 200°C. During the first step, a larger amount of chemical activity is observed up to 4%–6% addition of PP-g-MAH. Furthermore, the constant chemical composition allows a systematic comparison of the compatibilizer-dependent thermal, rheological, morphological, and mechanical properties. With an increased degree of interfacial reaction, the size of dispersed PA66 domains decreases to register improved interfacial adhesion with the PP matrix, yielding enhanced Young's modulus and absolute failure strength of the isotropic matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗