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At least 523 records · Page 29

Impact of Hydrogen on Methane and Pollutant Emissions over Three-Way Catalysts with Natural Gas–Hydrogen Blends

Blending natural gas (NG) with hydrogen (H₂) can improve combustion and engine performance while potentially facilitating the catalytic conversion of methane and other pollutants, resulting in cleaner tailpipe emissions. This study evaluates the impact of H2 on the conversion of methane, CO, and NOx emissions on a commercial three-way catalyst (TWC) in a flow reactor using synthetic gas mixtures that simulate stoichiometric engine exhausts with NG or NG+H₂ combustion. The work examines whether, and how, the additional amount of H₂ in the exhaust stream affects the conversion efficiency of methane and other pollutants. Experiments were conducted with both degreened and aged catalysts under controlled conditions, systematically varying temperature, the air-to-fuel equivalence ratio (λ), and λ modulation. Test conditions covered λ values from 0.996 to 1.000 to represent nominally stoichiometric engine operation with different λ modulation amplitudes, as well as a range of temperatures to inform control strategies for effective CH₄, CO, and NOₓ reduction. Overall, the results show that hydrogen addition significantly improves the conversion efficiency of CH₄ and NOₓ, particularly at temperatures below 500 °C. More significantly, this study highlights that exhaust gas composition, operating temperature, λ management, and the oxygen storage capacity of the TWC all play major roles in affecting the tailpipe emissions from NG and NG+H₂ combustion.

Prikhodko, Vitaly [ORNL] (ORCID:0000000244685836)↗

Physics potential of the IceCube Upgrade for atmospheric neutrino oscillations

The IceCube Upgrade is an extension of the existing IceCube Neutrino Observatory and will be deployed in the 2025–2026 austral summer. It will significantly improve the sensitivity of the detector to atmospheric neutrino oscillations. The existing 86-string IceCube array contains a dense in-fill known as DeepCore which is optimized to measure neutrinos with energies down to a few GeV. The IceCube Upgrade will consist of seven new densely instrumented strings placed within the DeepCore volume to further enhance the performance in the GeV energy range. The additional strings will feature new optical modules, each containing multiple photomultiplier tubes (PMTs), in contrast to the existing modules that each contain a single PMT. This will more than triple the number of PMT channels with respect to the current IceCube configuration, allowing for improved detection efficiency and reconstruction performance at GeV energies. We describe necessary updates to simulation, event selection, and reconstruction to accommodate the higher data rates observed by the upgraded detector and the addition of multi-PMT modules. We determine the expected sensitivity of the IceCube Upgrade to the atmospheric neutrino oscillation parameters sin 2 ⁡𝜃 23 and Δ⁢𝑚$^{2}_{32}$, the appearance of tau neutrinos and the neutrino mass ordering. The IceCube Upgrade will provide neutrino oscillation measurements that are of similar precision to those from accelerator experiments, while providing complementarity by probing higher energies and longer baselines, and with different sources of systematic uncertainties.

artificial neural networks↗

Crystal Structure and Characterization of Human Heavy-Chain Only Antibodies Reveals a Novel, Stable Dimeric Structure Similar to Monoclonal Antibodies

We report the novel crystal structure and characterization of symmetrical, homodimeric humanized heavy-chain-only antibodies or dimers (HC2s). HC2s were found to be significantly coexpressed and secreted along with mAbs from transient CHO HC/LC cotransfection, resulting in an unacceptable mAb developability attribute. Expression of full-length HC2s in the absence of LC followed by purification resulted in HC2s with high purity and thermal stability similar to conventional mAbs. The V H and C H 1 portion of the heavy chain (or Fd) was also efficiently expressed and yielded a stable, covalent, and reducible dimer (Fd2). Mutagenesis of all heavy chain cysteines involved in disulfide bond formation revealed that Fd2 intermolecular disulfide formation was similar to Fabs and elucidated requirements for Fd2 folding and expression. For one HC2, we solved the crystal structure of the Fd2 domain to 2.9 Å, revealing a highly symmetrical homodimer that is structurally similar to Fabs and is mediated by conserved (C H 1) and variable (V H ) contacts with all CDRs positioned outward for target binding. Interfacial dimer contacts revealed by the crystal structure were mutated for two HC2s and were found to dramatically affect HC2 formation while maintaining mAb bioactivity, offering a potential means to modulate novel HC2 formation through engineering. These findings indicate that human heavy-chain dimers can be secreted efficiently in the absence of light chains, may show good physicochemical properties and stability, are structurally similar to Fabs, offer insights into their mechanism of formation, and may be amenable as a novel therapeutic modality.

60 APPLIED LIFE SCIENCES↗

Collisional simulations of the modulator section in coherent electron cooling

The first section of any coherent electron cooling (CeC) system is the modulator, where the density of the electron beam is modulated by the copropagating ion beam. This density modulation is a result of Coulomb collisions between the individual particles of the two beams. The pairwise, stochastic part of the interactions impacts the overall performance of the CeC process. We present the first simulations of the density modulations of the electron beams from a collisional picture of the dynamics, considering the proof-of-principle CeC experiments at Brookhaven National Laboratory. These simulations were performed using PHAD, which is the first efficient, large-scale collisional numerical method in beam physics that we have previously developed and benchmarked. Realistic beam distributions and external fields have been optimized to provide strong modulation signals necessary for variations of coherent electron cooling systems. Cooling performance limits and potential collisionless simulation pitfalls are pointed out. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Dynamic Electric Field Assisted CO 2 Methanation

Energy-efficient advanced chemical reactions are essential for accelerating the growth of hydrocarbon economy. Sabatier reaction stands out for its potential to effectively transform carbon dioxide into valuable hydrocarbons and is an asset for long-duration Mars missions. This study explores a novel catalytic approach that harnesses electric field-assisted catalysis to substantially enhance the efficiency of the Sabatier reaction. Application of a dynamically perturbed electric field at 1000 Hz resulted in remarkable enhancements, increasing methane formation rates by over 100% at 350 °C and by 74% at 400 °C. Post-reaction catalyst characterization further revealed reduced blockage of active catalytic surface area under the applied electric field, emphasizing improved catalytic longevity and sustained activity. These results underscore the potential of tailored electric field waveforms to dynamically modulate elementary reaction kinetics and surface processes, positioning electric field-assisted catalysis as a transformative strategy for energy-efficient, cost-effective chemical manufacturing and energy conversion technologies.

42 - ENGINEERING↗

SiC-Based 5-kV Universal Modular Soft-Switching Solid-State Transformer (M-S4T) for Medium-Voltage DC Microgrids and Distribution Grids

Medium-voltage DC (MVDC) grids are attractive for electric aircraft and ship power systems, battery energy storage system (BESS), fast charging electric vehicle (EV), etc. Such EV or BESS applications need isolated bidirectional MVDC to LVDC or LVAC converters. However, the existing Si-based solutions cannot fulfill the requirements of a high-efficiency and robust converter for MVDC grids. This paper presents a 5 kV SiC-based universal modular solid-state transformer (SST). This universal current-source SST can interface either a LVAC or LVDC grid with a MVDC grid in single-stage power conversion, while the conventional dual active bridge (DAB) converter needs an additional inverter. The proposed SST module using 3.3 kV SiC MOSFETs and diodes is bidirectional and can serve as a building block in series or parallel for higher-voltage higher-power systems. The topology of each module is based on the soft-switching solid-state transformer (S4T) with reduced conduction loss, which features reduced EMI through controlled dv/dt, and high efficiency with full-range ZVS for main devices and ZCS for auxiliary devices. Operation principle of the modular S4T (M-S4T), capacitor voltage balancing control between the cascaded modules, design of components including a medium-voltage (MV) medium-frequency transformer (MFT) to realize a 50 kVA 5 kV DC to 600 V DC or 480 V AC M-S4T are presented. Importantly, the MV MFT prototype achieves very low leakage inductance (0.13%) and 15 kV insulation with coaxial cables and nanocrystalline cores. Here, the proposed universal modular SST is compared against the DAB solution and verified with DC-DC and DC-AC simulation and 4 kV experimental results. Significantly, the MV experimental results of a modular DC transformer with each module at MVDC are rarely covered in the literature and reported for the first time.

14 SOLAR ENERGY↗

Design and experimental testing of a 150 kWh thermal battery using thermosiphons embedded in a concrete matrix for power plant flexible operation

One of the options for achieving the global temperature limitation of 1.5 °C target, for the mitigation of global warming, is based on the better penetration of renewables into the electrical grid. This has imposed a burden to fossil fuel fired power plants since they are required to operate away from their baseload mode to compensate for the inherent intermittence of the renewable power. Integrating energy storage with fossil plants is an option to achieve their needed flexibility. A cost competitive energy storage option for the solution is based on storing sensible heat in concrete. Here, this paper reports research results and development of a thermal battery cell (TBC) capable of operating at temperatures up to 425 °C. A novel concept consisting of a concrete matrix for sensible heat storage, engineered to provide enhanced thermal and mechanical properties, and twenty-two thermosiphon elements, engineered for dual action were designed and fabricated into a single thermal energy storage (TES) module. Research for the development of the components for the TBC was performed in the laboratory. Efficient heat transfer, to/from the storage media, was demonstrated under several charging and discharging conditions with a thermal storage capacity of 150 kWh th and a rapid discharge, making the TBC suitable for fast ramping when integrated with a fossil fuel fired power plant. Efficient radial heat transfer to the concrete was observed due to the well designed spacing and location of thermosiphons in the radial direction. A minimal temperature difference of 2 °C, between the thermosiphons bottom and top was obtained, demonstrating the isothermicity of those elements. An overall end-to-end TBC energy-to-energy round trip efficiency of 70% was achieved.

25 ENERGY STORAGE↗

Modular performance prediction for scientific workflows using Machine Learning

Scientific workflows provide an opportunity for declarative computational experiment design in an intuitive and efficient way. A distributed workflow is typically executed on a variety of resources, and it uses a variety of computational algorithms or tools to achieve the desired outcomes. Such a variety imposes additional complexity in scheduling these workflows on large scale computers. As computation becomes more distributed, insights into expected workload that a workflow presents become critical for effective resource allocation. In this paper, we present a modular framework that leverages Machine Learning for creating precise performance predictions of a workflow. The central idea is to partition a workflow in such a way that makes the task of forecasting each atomic unit manageable and gives us a way to combine the individual predictions efficiently. We recognize a combination of an executable and a specific physical resource as a single module. This gives us a handle to characterize workload and machine power as a single unit of prediction. Overall, our modular technique of creating atomic modules and deployment of longest-path approach to estimate workflow performance, allows the framework to adapt to highly complex nested directed acyclic workflows and scale to new scenarios, since it does not make assumptions of underlying workflow structure. We present performance estimation results of independent workflow modules executed on the XSEDE SDSC Comet cluster using various Machine Learning algorithms. The results provide insights into the behavior and effectiveness of different algorithms in the context of scientific workflow performance prediction.

97 MATHEMATICS AND COMPUTING↗

GENESIS: Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering

Improved neutron inelastic scattering cross section data are needed to inform integral benchmark studies and advance applications in a wide variety of areas including nuclear energy, stockpile stewardship, nonproliferation, and space exploration. Neutron inelastic scattering also serves as a non-selective probe of low-lying nuclear structure. To help meet these needs, the Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) was constructed at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. This array couples high-resolution γ-ray detectors and fast neutron detectors to achieve single and coincident n/γ detection over a broad energy range. The current configuration of the array includes 26 organic liquid scintillators and four high-purity germanium detectors (two single-crystal and two four-crystal CLOVER detectors with two-fold segmentation). The array was constructed with minimal supporting material and designed to cover a wide range of secondary particle angles and energies with limited inter-element scattering. Data acquisition is accomplished using Mesytec MDPP-16 multi-channel high-resolution digital pulse processing modules. The array characteristics, including γ-ray and neutron energy resolution, timing resolution, and detection efficiency were measured and used to validate a Geant4 model of the array. Furthermore, the primary sources of neutron background and the uncertainties in the determination of incident and secondary neutron energy were assessed. GENESIS provides a new capability to address nuclear data needs and facilitates the advancement of a wide range of nuclear applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermal analyses of high-power advanced thermoacoustic radioisotope power system for future space exploration missions

This paper presents the results of 3-D thermal analyses of the heat source assembly of a 440 We advanced radioisotope power system (RPS) for future space exploration missions. This high thermal efficiency RPS employs a heat source assembly of eight Step 2 General Purpose Heat Source (GPHS) modules and four Thermoacoustic Power Converter (TAPC) units. Each unit is thermally coupled to two GPHS modules. Here, the analyses investigated the temperatures of the Iridium (Ir) alloy cladding of the 238 PuO 2 fuel pellets and the surface of the Fine Weave Pierced Fabric (FWPF) aeroshell in the GPHS modules to ensure reliable operation and safety in case of an unlikely reentry. Conductive coupling of the GPHS modules to the heater heads of the TAPC units produces relatively uniform axial and azimuthal distributions of heat flux and temperature. However, for this case the temperature of the Ir alloy cladding is lower than the desired values of 1173 K to maintain sufficient ductility. Adding a 5 mm wide He filled gap and decreasing the thickness of the graphite sleeve to 10 mm increased Ir cladding temperature to 1197–1174 K, which are in the desired range. The maximum surface temperatures of the FWPF graphite aeroshell of 1022–1131 K is well below the NASA specified limit of 1373 K. In addition, the total mass of the heat source assembly decreased by 19.6 kg, ~43% saving compared to original design.

42 ENGINEERING↗

PySpawn: Software for Nonadiabatic Quantum Molecular Dynamics

The ab initio multiple spawning (AIMS) method enables nonadiabatic quantum molecular dynamics simulations in an arbitrary number of dimensions, with potential energy surfaces provided by electronic structure calculations performed on-the-fly. However, the intricacy of the AIMS algorithm complicates software development, deployment on modern shared computer resources, and post-simulation data analysis. PySpawn is a nonadiabatic molecular dynamics software package that addresses these issues. Here, the program is designed to be easily interfaced with electronic structure software, and an interface to the TeraChem software package is described here. PySpawn introduces a task-based reorganization of the AIMS algorithm, allowing fine-grained restart capability and setting the stage for efficient parallelization in a future release. PySpawn includes a user-friendly and interactive Python analysis module that will enable novice users to painlessly adopt AIMS. As a demonstration of PySpawn’s simulation capability and analysis module, we report complete active space self-consistent field–based AIMS simulations of the 1,2- dithienyl-1,2-dicyanoethene molecule, a promising molecular photoswitch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An unprecedented quinoid–donor–acceptor strategy to boost the carrier mobilities of semiconducting polymers for organic field-effect transistors

Quinoidal–aromatic conjugated polymers hold great application potential in organic field-effect transistors (OFETs). However, the development of high mobility quinoidal–aromatic conjugated polymers still lags behind the more popular donor–acceptor (D–A) conjugated polymers, mainly owing to the lack of a rational design strategy and efficient building block. Herein, a novel quinoid–donor–acceptor (Q–D–A) strategy is demonstrated to modulate the energy-level and boost the charge carrier transport mobility of conjugated polymers as opposed to the D–A system. On the basis of this strategy, a quinoidal–aromatic conjugated polymer, namely PAQM-BT, is designed and synthesized. With the combined use of quinoid, donor and acceptor units in the backbone, the resulting Q–D–A polymer PAQM-BT displays the narrowest bandgap with the deepest-lying lowest unoccupied molecular orbital (LUMO) energy level, highest backbone coplanarity, enhanced thin-film crystallinity and smallest effective hole mass ($m^*_h$) in comparison with the corresponding D–A polymer PT3B1 and quinoid–donor (Q–D) polymer PAQM-3T. Benefitting from the more effective intra- and inter-chain charge transport, as corroborated by experiment and theoretical calculations, OFET devices based on PAQM-BT exhibit a highly boosted hole mobility of up to 5.10 cm 2 V -1 s -1 , which is one and four orders of magnitude higher than that of PAQM-3T and PT3B1, respectively, and is among the highest for quinoidal–aromatic conjugated polymers. Finally, the potent Q–D–A strategy not only allows the energy level to be modulated but also leads to effective charge carrier transport, opening up possibilities to the development of high mobility quinoidal–aromatic conjugated polymers based on a variety of quinoids, donors, and acceptors.

36 MATERIALS SCIENCE↗

Measurements of Six-Junction Concentrator Solar Cells

Accurate measurements of six-junction inverted metamorphic concentrator solar cells under AM1.5 direct spectrum are obtained by adjusting the spectrum of a tunable high-intensity solar simulator with custom mirrors. Isotype reference cells and broadband InGaAs QE calibration cells were developed for accurate measurements. Modeling and varying the illumination show that an unavoidable 15% - 17% overillumination on the sixth junction does not result in significant error of these 6J IMM devices. Spectrally adjusted flash measurements are independently confirmed by NREL's Cell and Module Performance team. Concentration measurements of a 6J IMM solar cell resulted in 47.1 ± 3.2% (absolute) efficiency at 143 suns.

41 EE - Solar Energy Technologies Office (EE-4S)↗

A Molten Salt Electrochemical Process for the Preparation of Cost-Effective p-Block (Coating) Materials

Solar energy applications rely heavily on p-block elements and transition metals. Silicon is, by far, the most commonly used material in photovoltaic cells and accounts for about 85% of modules sold presently. Of late, thin film photovoltaic cells have gained momentum because of their higher efficiencies. Most of these thin film devices are made out of just five elements, namely, cadmium, tellurium, selenium, indium, gallium and copper. The present manuscript describes an elegant and inexpensive molten salt-based electrolytic process for fabricating a tellurium-coated metallic substrate. A three-electrode set up was employed to coat iridium with tellurium from a molten bath containing lithium chloride, lithium oxide and tellurium tetrachloride (LiCl-Li 2 O-TeCl 4 ) at 650 °C for a duration ranging from 30 to 120 min under a galvanostatic mode. The tellurium coating was observed to be thick, uniform, smooth and homogeneous. Additionally, the deposited tellurium did not chemically react with the iridium substrate to form intermetallic compounds, which is a good feature from the standpoint of the device’s performance characteristics. The present process, being generic in nature, shows the potential for the manufacture of both the coated substates and high-purity elements not just for tellurium but also for other p-block elements.

36 MATERIALS SCIENCE↗

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Recycling the Energy of Indoor Light: Highly Efficient Organic Photovoltaics via a Ternary Strategy

A ternary approach in organic photovoltaics (OPV) is simple and reliable to effectively tune the optical, electrical and morphological properties of the photoactive layer for high efficiency as well as long-term stability under 1 sun. However, there have been few papers reporting spectra and weak illumination compared to outdoor light. In this study, by using two compatible 16 structures, we demonstrate a simultaneous modulation of light absorption and molecular donor polymers (PM7 and PM7 D1) with slightly-different band gaps and similar chemical packing under ambient conditions, which resulted in efficient indoor OPVs exhibiting power conversion efficiency (PCE) over 20% under 1000 lux of warm white light-emitting diode (2900 K). From morphological analysis, we infer that PM7 serves to seed nucleation of PM7 D1 in the ternary blend, templating its crystallization and alignment along the PM7 backbone. Such templating effect leads to increased domain spacing and relative degree of crystallinity (rDoC) compared to those of each binary system. We further show that higher rDoC helps suppress both bimolecular and trap-assisted recombination of photogenerated charges in the ternary devices. As a result, the complementary absorption and synergistic molecular assembly of the two donor polymers enhance the short-circuit current density as to increase the average PCEs from 9.6 to 10.3% under 1 sun and from 18.7 to 20.0% under 1000 lux. We envision that our strategy of incorporating both a planar and a flexible donor polymer with similar chemical structures can be generally applicable to attain a high performance ternary OPV under both 1 sun and indoor light.

14 SOLAR ENERGY↗

Maximizing selectivity: An analysis of isoporous membranes

Membranes are compelling candidates for many separation-based industrial processes. However, all synthetic membranes are subject to well-recognized permeability-selectivity trade-offs that hinder their use in advanced applications. Having uniform nanoscale pore size, isoporous nanofiltration and ultrafiltration membranes have attracted wide research interest. However, quantitative analysis of isoporous membrane performance is lacking - particularly at module and system-level scales. In this study, an analytical model is built to investigate how membrane pore-size distribution affects the solute separation efficiency (i.e., rejection and selectivity). The model accounts for convective hindrance as well as concentration polarization and explores effects on separation from the solute-to-pore-size ratio and percent recovery (i.e., fraction of feed flow that passes through the membrane). At the module level, our analysis suggests that a notably sharper rejection vs. solute size curve can be obtained as the pore-size distribution becomes narrower. Additionally, as the recovery increases, the rejection of a solute is maintained at a high level using isoporous membranes while the rejection drops rapidly for membranes that possess a disperse pore-size distribution. Furthermore, in the separation of mixed solutes, isoporous membranes achieve a large selectivity with a modest loss of permeability. Overall, this study elaborates the unique role that isoporous membranes play within the permeability-selectivity trade-off relations and identifies the most exciting opportunities for their future applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗