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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 235 records · Page 13

Mimicking Natural Photosynthesis: Designing Ultrafast Photosensitized Electron Transfer into Multiheme Cytochrome Protein Nanowires

Efficient nanomaterials for artificial photosynthesis require fast and robust unidirectional electron transfer (ET) from photosensitizers through charge-separation and accumulation units to redox-active catalytic sites. We explored the ultrafast time-scale limits of photo-induced charge transfer between a Ru(II)tris(bipyridine) derivative photosensitizer and PpcA, a 3-heme c-type cytochrome serving as a nanoscale biological wire. Four covalent attachment sites (K28C, K29C, K52C, and G53C) were engineered in PpcA enabling site-specific covalent labeling with expected donor-acceptor (DA) distances of 4–8 Å. X-ray scattering results demonstrated that mutations and chemical labeling did not disrupt the structure of the proteins. Time-resolved spectroscopy revealed three orders of magnitude difference in charge transfer rates for the systems with otherwise similar DA distances and the same number of covalent bonds separating donors and acceptors. All-atom molecular dynamics simulations provided additional insight into the structure-function requirements for ultrafast charge transfer and the requirement of van der Waals contact between aromatic atoms of photosensitizers and hemes in order to observe sub-nanosecond ET. This work demonstrates opportunities to utilize multi-heme c-cytochromes as frameworks for designing ultrafast light-driven ET into charge-accumulating biohybrid model systems, and ultimately for mimicking the photosynthetic paradigm of efficiently coupling ultrafast, light-driven electron transfer chemistry to multi-step catalysis within small, experimentally versatile photosynthetic biohybrid assemblies.

36 MATERIALS SCIENCE↗

Coherent Phonon-Induced Modulation of Charge Transfer in 2D Hybrid Perovskites

Electron–phonon interactions play an essential role in charge transport and transfer processes in semiconductors. For most structures, tailoring electron–phonon interactions for specific functionality remains elusive. Here, it is shown that, in hybrid perovskites, coherent phonon modes can be used to manipulate charge transfer. In the 2D double perovskite, (AE2T) 2 AgBiI 8 (AE2T: 5,5“-diylbis(amino-ethyl)-(2,2”-(2)thiophene)), the valence band maximum derived from the [Ag 0.5 Bi 0.5 I4] 2– framework lies in close proximity to the AE2T-derived HOMO level, thereby forming a type-II heterostructure. During transient absorption spectroscopy, pulsed excitation creates sustained coherent phonon modes, which periodically modulate the associated electronic levels. Thus, the energy offset at the organic–inorganic interface also oscillates periodically, providing a unique opportunity for modulation of interfacial charge transfer. Density-functional theory corroborates the mechanism and identifies specific phonon modes as likely drivers of the coherent charge transfer. These observations are a striking example of how electron–phonon interactions can be used to manipulate fundamentally important charge and energy transfer processes in hybrid perovskites.

36 MATERIALS SCIENCE↗

Charge Transfer Properties of Heterostructures Formed by Bi 2 O 2 Se and Transition Metal Dichalcogenide Monolayers

Atomically thin bismuth oxyselenide (Bi 2 O 2 Se) exhibits attractive properties for electronic and optoelectronic applications, such as high charge-carrier mobility and good air stability. Recently, the development of Bi 2 O 2 Se-based heterostructures have attracted enormous interests with promising prospects for diverse device applications. Although the electrical properties of Bi 2 O 2 Se-based heterostructures have been widely studied, the interlayer charge transfer in these heterostructures remains elusive, despite its importance in harnessing their emergent functionalities. Here, a comprehensive experimental investigation on the interlayer charge transfer properties of two heterostructures formed by Bi 2 O 2 Se and representative transition metal dichalcogenides (namely, WS 2 /Bi 2 O 2 Se and MoS 2 /Bi 2 O 2 Se) is reported. In this work, Kelvin probe force microscopy is used to measure the work functions of the samples, which are further employed to establish type-II band alignment of both heterostructures. Photoluminescence quenching is observed in each heterostructure, suggesting high charge transfer efficiency. Time-resolved and layer-selective pump–probe measurements further prove the ultrafast interlayer charge transfer processes and formation of long-lived interlayer excitons. These results establish the feasibility of integrating 2D Bi 2 O 2 Se with other 2D semiconductors to fabricate heterostructures with novel charge transfer properties and provide insight for understanding the performance of optoelectronic devices based on such 2D heterostructures.

36 MATERIALS SCIENCE↗

Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP

Large-scale scientific workflows rely heavily on high-performance file transfers. These transfers require strict quality parameters such as guaranteed bandwidth, no packet loss or data duplication. To have successful file transfers, methods such as predetermined thresholds and statistical analysis need to be done to determine abnormal patterns. Network administrators routinely monitor and analyze network data for diagnosing and alleviating these, making decisions based on their experience. However, as networks grow and become complex, monitoring large data files and quickly processing them, makes it improbable to identify errors and rectify these. Abnormal file transfers have been classified by simply setting alert thresholds, via tools such as PerfSonar and TCP statistics (Tstat). This paper investigates the feasibility of unsupervised feature extraction methods for identifying network anomaly patterns with three unsupervised classification methods—principal component analysis, autoencoder and isolation forest. Here, we collect file transfer statistics from two experiment sets—synthetic iPerf generated traffic and 1000 Genome workflow runs, with synthetically introduced anomalies. Our results show that while PCA and a simple autoencoder finds it difficult to detect clusters, the tree-variant isolation forest is able to identify anomalous packets by breaking down TCP traces into tree classes early.

97 MATHEMATICS AND COMPUTING↗

Structure-based mechanism and inhibition of cholesteryl ester transfer protein

Purpose of Review: Cholesteryl ester transfer proteins (CETP) regulate plasma cholesterol levels by transferring cholesteryl esters (CEs) among lipoproteins. Lipoprotein cholesterol levels correlate with the risk factors for atherosclerotic cardiovascular disease (ASCVD). This article reviews recent research on CETP structure, lipid transfer mechanism, and its inhibition. Recent Findings: Genetic deficiency in CETP is associated with a low plasma level of low-density lipoprotein cholesterol (LDL-C) and a profoundly elevated plasma level of high-density lipoprotein cholesterol (HDL-C), which correlates with a lower risk of atherosclerotic cardiovascular disease (ASCVD). However, a very high concentration of HDL-C also correlates with increased ASCVD mortality. Considering that the elevated CETP activity is a major determinant of the atherogenic dyslipidemia, i.e., pro-atherogenic reductions in HDL and LDL particle size, inhibition of CETP emerged as a promising pharmacological target during the past two decades. CETP inhibitors, including torcetrapib, dalcetrapib, evacetrapib, anacetrapib and obicetrapib, were designed and evaluated in phase III clinical trials for the treatment of ASCVD or dyslipidemia. Although these inhibitors increase in plasma HDL-C levels and/or reduce LDL-C levels, the poor efficacy against ASCVD ended interest in CETP as an anti-ASCVD target. Nevertheless, interest in CETP and the molecular mechanism by which it inhibits CE transfer among lipoproteins persisted. Insights into the structural-based CETP-lipoprotein interactions can unravel CETP inhibition machinery, which can hopefully guide the design of more effective CETP inhibitors that combat ASCVD. Summary: Individual-molecule 3D structures of CETP bound to lipoproteins provide a model for understanding the mechanism by which CETP mediates lipid transfer and which in turn, guide the rational design of new anti-ASCVD therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles is investigated using a novel transient three-dimensional computational fluid dynamics model. The model couples particle–gas hydrodynamics of solid–gas flows laden with polydisperse particles, radiative heat transfer in non-grey absorbing, emitting and anisotropically-scattering multi-component participating media, conduction heat transfer in the gas phase, and interfacial convection heat transfer. The multiphase particle-in-cell method is used to predict high-fidelity solid–gas flow characteristics, such as the local discrete particle size distribution, with increased computational efficiency by combining the advantages of both Eulerian and Lagrangian methods. The multi-component radiative transfer model is implemented using an advanced collision-based Monte Carlo ray-tracing method. The number of the prescribed discrete particle components is found to be the key parameter affecting the computational accuracy and efficiency, which primarily depends on the size distribution of the particles. For the model particle–gas flow featuring free-falling Gamma-distributed ceramic particles exposed to concentrated solar irradiation, the particle volume fraction, radiative, fluid flow and thermal characteristics appear to converge with the increasing number of the discrete particle components. Five particle components are sufficient to obtain physically meaningful results. A further increase in the number of the particle components only slightly increases the accuracy of the numerical predictions at the expense of a rapidly increasing computational time. For five particle components, the particle vertical velocity at the receiver exit for particles with the diameter of 43.4 μm is 57% of that for the particles with the diameter of 202.8 μm. The temperatures of these two particle components increase from the initial ambient values by factors of 2 and 1.2, respectively, during the simulation time. In conclusion, the model developed allows for increased fidelity of particle–gas flow simulations with significant radiative effects.

97 MATHEMATICS AND COMPUTING↗

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Exploratory analysis and performance prediction of big data transfer in High-performance Networks

Big data transfer in large-scale scientific and business applications is increasingly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) via advance bandwidth reservation. Provisioning agents need to carefully schedule data transfer requests, compute network paths, and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized, could be simply wasted due to the exclusive access during the approved time window, and cause extra overhead and complexity for resource management. This calls for accurate performance prediction to reserve bandwidths that match actual needs and avoid over-provisioning. We employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements collected in the past several years from data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated testbeds. We first analyze the performance patterns in response to a comprehensive list of parameters in end-host systems, network connections, and data transfer applications, which motivate the use of machine learning and also help us identify the effects of latent factors. We then propose threshold- and clustering-based methods to eliminate negative effects of latent factors in data preprocessing and build a robust performance predictor based on customized domain-oriented loss functions. The performance of the proposed methods is verified by extensive experiments using SVR and RFR as well as theoretical analysis of the general performance bound.

97 MATHEMATICS AND COMPUTING↗

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗

Experimental investigation of Multi-Mode heat transfer to a Free-Falling dilute particle cloud in a heated vertical tube

The development of dilute particle heat exchangers and reactors for advanced energy systems requires an understanding of the multi-mode heat transfer from a heated wall to falling particles. This study presents experimental results of the overall heat transfer coefficient for a free-falling, dilute flow of particles with solid volume fraction from 0.0005 to 0.006 corresponding to feed rates from 3.7 kg s -1 m -2 to 44 kg s -1 m -2 in a vertical, heated tube containing quiescent air at atmospheric pressure. Tube wall temperatures are varied between 300°C to 900°C while keeping the particle inlet temperature constant. The experimental results show that the overall heat transfer coefficient is a strong function of particle feed rate and surface temperature. Good agreement was obtained with prior studies conducted at comparable temperatures but lower particle feed rates (< 4 kg m -2 s -1 ). The established correlations for particle-to-wall radiation and particle-to-gas convection were used to estimate the wall-to-gas convective contribution from the measured overall heat transfer coefficient. The experimental results indicated a 4 to 6 times improvement in the wall convection in the solid-gas mixture compared to that expected from natural convection in a single-phase gas. Furthermore, the data presented here are applicable to characterize heat transfer in dilute particle heat exchangers, furnaces, and solar receivers.

14 SOLAR ENERGY↗

Electron transfer calculations between edge sharing octahedra in hematite, goethite, and annite

A key reaction underlying the charge transport in iron containing oxides, clays, micas is the Fe$^{2+}$-Fe$^{3+}$ exchange reaction between edge-sharing iron octahedra. These reactions facilitate conduction in these minerals by the thermally-activated hopping of small polarons across the lattice. Depending on the mineral and local charge state the small polaron can either encase an electron or hole. The probability for conduction of small polarons depends strongly on the height and adiabicity of the reaction barrier, with larger and more diabatic barriers yielding slow conduction associated with either weak coupling or a large prerequisite rearrangement of the lattice during charge transport. To model these reactions, a first principle electron transfer (ET) method was developed to model the small polaron hopping between the edge-sharing octahedra sites in hematite ($e^{-}$ polaron), goethite ($e^{-}$ polaron), and annite ($h^{+}$ polaron) bulk structures. The ET method is based on electronic structure methods (i.e., plane-wave Density Functional Theory) capable of performing calculations with periodic cells and large size systems efficiently while at the same time being accurate enough to be used in the estimation of the electron-transfer coupling matrix element, $V_{AB}$, and the electron transfer transmission factor, $\kappa_{el}$. Additionally, the calculations confirmed the existence of small polarons in all three minerals, and the reactions were predicted to be strongly adiabatic. It was found that transfer of a hole in the octahedral layer of annite had an adiabatic barrier of $0.311$ eV, and the transfer of an extra electron in hematite and goethite had adiabatic barriers of $0.242$ eV and $0.232$ eV respectively. The electronic coupling parameters,$V_{AB}$, were found to be $0.188$ eV, $0.196$ eV, and $0.102$ eV respectively for hematite, goethite, and annite. While similar bonding topologies pertain, the underlying basis for the differences is the subtle differences in local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Convective heat transfer enhancement through additively built multiscale micro-tetrahedron features

Use of Additive Manufacturing (AM) to improve the heat transfer characteristics of tip shrouds in high-pressure turbines is being considered by industries. Existing designs of these components integrate micro-cooling channels to reduce the bulk temperature for improved life. In this research, closely packed micro tetrahedron features in addition to AM roughness has been considered. Further, this multiscale surface characteristics increased surface area per unit volume available for heat exchange. Micro-tet features were designed, manufactured, characterized, and evaluated systematically while increasing their height. An enormous increase in the overall wetted surface area by 200 % was measured. The convective heat transfer enhancement was ~3.72 times EDM rough coupon, and friction factor enhancement was ~5.5 times EDM rough coupon. Furthermore, the proposed design offers 2.5 times enhanced heat transfer for a given 2 W pumping power compared to our EDM rough coupon. Heat transfer enhancement was observed to not vary strongly with increased Reynolds number. Such complex designs are only possible through additive manufacturing for increased heat transfer with little pressure penalty. Finally, increasing the micro-tet height for increased surface area and improved heat exchange beyond an upper limit might not be a significant benefit as it gets compensated by increasing skin friction.

42 ENGINEERING↗

New frontiers in atom probe tomography: a review of research enabled by cryo and/or vacuum transfer systems

There has been a recent surge in the use of cryo and/or vacuum specimen preparation and transfer systems that are broadening the scope of research enabled by the microscopy technique of atom probe tomography. This is driven by the fact that, like for many microscopes, the application of atom probe to air and temperature sensitive materials or wet biological specimens has previously been limited by through-air-transfer and through-vacuum-transfer at room temperature. Here we provide an overview of the critical areas of research that require these new transfer and analysis protocols, as well as a review of current advances in transfer devices, environmental cells and glove boxes for controlled sample manipulation. This includes the study of catalysis and corrosion, the application of atom probe to biological samples, the study of liquid-solid interfaces, natural ageing investigations and the analysis of hydrogen in metals.

36 MATERIALS SCIENCE↗

Enhanced pool boiling heat transfer using novel inverted trapezoid microgroove structures

Pool boiling heat transfer improvements with enhanced surfaces have been extensively studied for various hydrofluorocarbon (HFC) refrigerants. However, there is a limited number of studies in the open literature that focus on the pool boiling heat transfer characteristics of hydrofluoroolefin (HFO) refrigerants on enhanced surfaces. This study aims to address this gap by analyzing the pool boiling behavior of HFO refrigerants, specifically R1234yf and R1234ze(E). Experiments were conducted on both plain surfaces and novel inverted trapezoid microgroove structures. Further, the experimental results indicate that the microgroove structures can improve heat transfer coefficients by up to 80% compared to plain surfaces. Additionally, the performance of R1234yf and R1234ze(E) was compared to that of R134. It was observed that R1234yf exhibited comparable performance to R134a, while R1234ze(E) showed slightly lower performance. To assess the influence of saturation temperature on pool boiling heat transfer, tests were conducted at different saturation temperatures of 15℃, 25℃, and 35℃. The findings revealed that the pool boiling heat transfer coefficient increases with rising saturation temperature.

42 ENGINEERING↗

Changing Directions: Influence of Ligand Electronics on the Directionality and Kinetics of Photoinduced Charge Transfer in Cu(I)Diimine Complexes

A key challenge to the effective utilization of solar energy is to promote efficient photoinduced charge transfer, specifically avoiding unproductive, circuitous electron-transfer pathways and optimizing the kinetics of charge separation and recombination. We hypothesize that one way to address this challenge is to develop a fundamental understanding of how to initiate and control directional photoinduced charge transfer, particularly for earth-abundant first-row transition-metal coordination complexes, which typically suffer from relatively short excited-state lifetimes. Here, in this paper, we report a series of functionalized heteroleptic copper(I)bis(phenanthroline) complexes, which have allowed us to investigate the directionality of intramolecular photoinduced metal-to-ligand charge transfer (MLCT) as a function of the substituent Hammett parameter. Ultrafast transient absorption suggests a complicated interplay of MLCT localization and solvent interaction with the Cu(II) center of the MLCT state. This work provides a set of design principles for directional charge transfer in earth-abundant complexes and can be used to efficiently design pathways for connecting the molecular modules to catalysts or electrodes and integration into systems for light-driven catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Permittivity Threshold and Thermodynamics of Integer Charge-Transfer Complexation for an Organic Donor–Acceptor Pair

Molecular or chemical-based charge doping provides a means to change the properties (e.g. conductivity) of a material through a complete or partial transfer of charge between its constituents. Understanding how local material environment impacts this process is thus important for controlling the properties of organic materials. This paper presents spectroscopic investigations of molecular charge transfer interactions between a pair of common charge-doping and -transporting materials (2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane, F4TCNQ, and N,N’-Diphenyl-N-N’-di-p-tolylbenzene-1,4-diamine, MPDA). Equilibrium constants associated with charge transfer were determined for donor-acceptor pairs dissolved in a series of solvents covering a range of values of permittivity. A threshold for highly favorable charge separation was observed to occur at a permittivity of ~8-9, with more and less favorable charge separation observed in solvents of higher and lower permittivity, respectively, but with chloroform (permittivity=4.81) exhibiting an anomalously favorable charge separation. Temperature-dependent studies were undertaken to assess the thermodynamics of charge separation. In 1,2- dichloroethane (permittivity=10.36) and chlorobenzene (permittivity=5.62), charge transfer was observed to be both enthalpically and entropically favorable. Charge separation in chloroform is exothermic and entropically disfavored, indicating that specific, inner-shell solvent-solute interactions stabilize the charge-separated complex and result in a net increase in local solution structure. Furthermore, our results provide insight on how modification to the chemical environment may be utilized to support stable charge transfer for molecular doping applications and requiring only modest changes in local permittivity.

36 MATERIALS SCIENCE↗

Efficient Size-Dependent Hot Electron Transfer from Au to TiO 2 Nanoparticles

Harvesting of plasmon-induced hot carriers at the metal/semiconductor interface offers a promising and innovative avenue for solar energy conversion. However, their practical implementation is often hampered by their limited efficiencies. Herein, we have demonstrated a highly efficient plasmonic hot electron transfer with a quantum efficiency (QE) of up to 57 ± 4% from 5.25 nm Au nanoparticles (NPs) to TiO 2 films under 400 nm ultrafast laser excitation. The observed hot electron transfer QEs decrease at larger particle sizes, to 20% for 9.1 nm Au, and show negligible changes with excitation wavelengths at 400, 500, and 600 nm. Analysis of the size and excitation wavelength dependent hot electron transfer QEs suggests they contain contributions of interband absorption, indirect plasmon-induced hot electron transfer (PHET), and direct plasmon-induced interfacial charge transfer transition (PICTT) pathways, and QEs of all three pathways increase at smaller Au size. Our result suggests that reducing plasmon particle sizes is a promising approach for efficient plasmonic hot-carrier extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolution from Tunneling to Hopping Mediated Triplet Energy Transfer from Quantum Dots to Molecules

Efficient energy transfer is particularly important for multiexcitonic processes like singlet fission and photon upconversion. Observation of the transition from short-range tunneling to long-range hopping during triplet exciton transfer from CdSe nanocrystals to anthracene is reported here. This is firmly supported by steady- state photon upconversion measurements, a direct proxy for the efficiency of triplet energy transfer (TET), as well as transient absorption measurements. When phenylene bridges are initially inserted between a CdSe nanocrystal donor and anthracene acceptor, the rate of TET decreases exponentially, commensurate with a decrease in the photon upconversion quantum efficiency from 11.6% to 4.51% to 0.284%, as expected from a tunneling mechanism. However, as the rigid bridge is increased in length to 4 and 5 phenylene units, photon upconversion quantum efficiencies increase again to 0.468% and 0.413%, 1.5–1.6 fold higher than that with 3 phenylene units (using the convention where the maximum upconversion quantum efficiency is 100%). This suggests a transition from exciton tunneling to hopping, resulting in relatively efficient and distance-independent TET beyond the traditional 1 nm Dexter distance. Transient absorption spectroscopy is used to confirm triplet energy transfer from CdSe to transmitter, and the formation of a bridge triplet state as an intermediate for the hopping mechanism. Lastly, this first observation of the tunneling-to-hopping transition for long-range triplet energy transfer between nanocrystal light absorbers and molecular acceptors suggests that these hybrid materials should further be explored in the context of artificial photosynthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗