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At least 55 records · Page 3

Fusion Intelligence: A Paradigm for Merging Natural and Artificial Intelligence

Here, this article presents fusion intelligence (FI), a bio-inspired paradigm that synergistically integrates the intrinsic capabilities of intelligent biological organisms with the advanced potential of artificial intelligence (AI)-driven systems. FI harnesses the unique intelligence, sensing, actuation, and mobility attributes of living organisms, such as honeybees, blending these with the sophisticated data-driven problem-solving functionalities of AI. By bridging the gap between natural intelligence (NI) and AI, FI can transform how humans interact with and harness the capabilities of both natural and artificial systems. This article presents the model of FI and its application to solve practical problems, discusses the challenges and future directions of FI research, emphasizing a generalized approach to solve complex problems, where AI can observe/control NI in a closed-loop system. We demonstrate the potential for FI to enhance the performance of an agricultural IoT system via a simulated case study, which achieves 50% improvement in the efficacy of insect pollination (entomophily).

47 OTHER INSTRUMENTATION↗

Facile microwave synthesis of zirconium metal-organic framework thin films on gold and silicon and application to sensor functionalization

Zirconium-based metal-organic frameworks, including UiO-66 and related frameworks, have become the focus of considerable research in the area of chemical warfare agent (CWA) decontamination. However, little work has been reported exploring these metal-organic frameworks (MOFs) for CWA sensing applications. For many sensing approaches, the growth of high-quality thin films of the active material is required, and thin film growth methods must be compatible with complex device architectures. Several approaches to synthesize thin films of UiO-66 have been described but many of these existing methods are complex or time consuming. In this work, we describe the development of a simple and rapid microwave assisted synthesis of oriented UiO-66 thin films on unmodified silicon (Si) and gold (Au) substrates. Thin films of UiO-66 and UiO-66-NH 2 can be grown in as little as 2 min on gold substrates and 30 min on Si substrates. The film morphology and orientation are characterized and the effects of reaction time and temperature on thin film growth on Au are investigated. Both reaction time and temperature impact the overgrowth of protruding discrete crystallites in the thin film layer but, surprisingly, no strong correlation is observed between film thickness and reaction time or temperature. We also briefly describe the synthesis of Zr/Ce solid solution thin films of UiO-66 on Au and report the first synthesis of a solid solution thin film MOF. Finally, we demonstrate the utility of the microwave method for the facile functionalization of two sensor architectures, plasmonic nanohole arrays and microresonators, with UiO-66 thin films.

36 MATERIALS SCIENCE↗

Enhancing the Optically Detected Magnetic Resonance Signal of Organic Molecular Qubits

In quantum information science and sensing, electron spins are often purified into a specific polarization through an optical-spin interface, a process known as optically detected magnetic resonance (ODMR). Diamond-NV centers and transition metals are both excellent platforms for these so-called color centers, while metal-free molecular analogues are also gaining popularity for their extended polarization lifetimes, milder environmental impacts, and reduced costs. In our earlier attempt at designing such organic high-spin π-diradicals, we proposed to spin-polarize by shelving triplet M S = ±1 populations as singlets. This was recently verified by experiments albeit with low ODMR contrasts of <1% at temperatures above 5 K. In this work, we propose to improve the ODMR signal by moving singlet populations back into the triplet M S = 0 sublevel, designing a true carbon-based molecular analogue to the NV center. Our proposal is based upon transition-orbital and group-theoretical analyses of beyond-nearest-neighbor spin–orbit couplings, which are further confirmed by ab initio calculations of a realistic trityl-based radical dimer. Microkinetic analyses point toward high ODMR contrasts of around 30% under experimentally feasible conditions, a stark improvement from previous works. Finally, in our quest toward ground-state optically addressable molecular spin qubits, we exemplify how our symmetry-based design avoids Zeeman-induced singlet–triplet mixings, setting the scene for realizing electron spin qubit gates.

Group theory↗

Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including: - Land Surface Temperature K-Means classifier - Labeling AI using Self Organizing Maps (SOM) - Post-processing for Permanent Scatterer InSAR (PSInSAR) analysis with SOM - Mineral marker summarizing - Artificial Intelligence (AI) Data splitting: creates data set from a single raster file - Artificial Intelligence Model: creates AI from a single data set, after splitting in Train, Validation and Test subsets - AI Mapper: creates a classification map based on a raster file

15 GEOTHERMAL ENERGY↗

Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation inland-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine)rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover

58 GEOSCIENCES↗

Photometric sensing of heavy metal ions using a naphthoquinodimethyl- bis -thioamide dye: Selectivity & photophysics of the metal organic complexes

As Mother Nature is experiencing catastrophic environmental pollutions from both natural sources and anthropogenic activities, many scientists have been working around the clock to develop environmentally benign and cost-effective, yet sensitive, detection techniques for pollutants, especially heavy metal species (e.g. lead, cadmium, mercury, among others) that are deleterious to human health. Herein, we report a novel sulfur-containing small organic dye/sensor naphthoquinodimethyl-bis-thioamide (QDM), which was found to be particularly selective toward mercury ion (Hg 2+ ). Using a combination of UV-vis absorption, photoluminescence, and time-resolved pump-probe techniques, we established that QDM and Hg 2+ can form stable complex(es) due to the strong affinity of sulfur toward mercury. In this investigation, while a higher ratio of QDM:Hg 2+ was necessary to fully quench the fluorescence emission of QDM, only 1 equiv of the Hg 2+ ion was necessary to observe the sensing effect on the excited state photo-behavior(s) of QDM. Furthermore, the present results highlight a synergy between molecular sensors' selectivity/sensitivity and sensor-analytes dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and Characterization of Pd-based Nanomaterials

Bimetallic nanoparticles (BNPs) consist of two different types of metals or alloys that are bonded together. Unique properties such as optical, electronic, thermal, and catalytic effects differ for each type of BNP. Important BNPs range from Au-Pd, Ag- Pt, Au-Pt, and Ag-Ni. Pd bimetallic nanoparticles are of interest due to their many applications such as catalysis and sensing. Bimetallic catalysts have increase reaction rates and have improved catalyst stability through the geometry and ligand distribution. Pd nanoparticles are considered to be a strong catalyst due to their high activity at low temperatures and high tolerance to moisture. The catalytic properties of bimetallic nanoparticles depend on the structural properties such as size and shape. Core-shell, hollow structure, and multi-shell alloy are three possible structures nanoparticles can form as bimetallic catalysts. BNPs can be synthesized through different methods to control the size, shape, and structure. To obtain different morphologies, a variety of methods can be performed. Different methods can range from the usage of the glancing angle deposition (GLAD) to the galvanic replacement reaction, but the methods all depend on the properties of the metals. The galvanic displacement reaction was the method used to obtain Pd-based nanoparticles. This reaction is best know for obtaining hollow shaped NPs. To determine what redox process was preformed, the activity series of metals was used. From the activity series of metals, silver (Ag) was selected to preform Pd-based nanoparticles. Objectives: Synthesize Ag nanoparticles and Ag-Pd nanoparticles to understand the morphology. Characterize the synthesized nanoparticles using scanning electron microscopy (SEM), phase analysis light scattering (PALS), dynamic light scattering (DLS), energy dispersive X-ray spectroscopy (EDS), and UV-Vis spectroscopy. Results: In the UV-Vis spectrum, the Ag-Pd bimetallic NP's plasmon band decreased as the volume of palladium increased. The surface charge increases as the concentration of palladium increases. The Pd{sup 2+} ions interact with the sodium citrate surface, and decrease the negative charge. Conclusion: Ag-Pd nanoparticles were successfully created and stabilized with sodium citrate. The addition of Pd decreased the prominent plasmon band of the Ag nanoparticles. The SEM analysis showed that Ag nanoparticles had a well-defined structure, while the Ag-Pd nanoparticles showed hollow and rough structure. The EDX analysis confirmed the presence of silver and palladium. This material can be used in many industrial and research fields such as organic synthesis, fuel cells, and environmental sensing and remediation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Semiconducting Two‐Dimensional Polymer as an Organic Electrochemical Transistor Active Layer

Abstract Organic electrochemical transistors (OECTs) are devices with broad potential in bioelectronic sensing, circuits, and neuromorphic hardware. Their unique properties arise from the use of organic mixed ionic/electronic conductors (OMIECs) as the active channel. Typical OMIECs are linear polymers, where defined and controlled microstructure/morphology, and reliable characterization of transport and charging can be elusive. Semiconducting two‐dimensional polymers (2DPs) present a new avenue in OMIEC materials development, enabling electronic transport along with precise control of well‐defined channels ideal for ion transport/intercalation. To this end, a recently reported 2DP, TIIP, is synthesized and patterned at 10 µm resolution as the channel of a transistor. The TIIP films demonstrate textured microstructure and show semiconducting properties with accessible oxidation states. Operating in an aqueous electrolyte, the 2DP‐OECT exhibits a device‐scale hole mobility of 0.05 cm 2 V –1 s –1 and a µ C * figure of merit of 1.75 F cm –1 V –1 s –1 . 2DP OMIECs thus offer new synthetic degrees of freedom to control OECT performance and may enable additional opportunities such as ion selectivity or improved stability through reduced morphological modulation during device operation.

2D-polymer↗

Significance of the organic aerosol driven climate feedback in the boreal area

Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism.

54 ENVIRONMENTAL SCIENCES↗

Putting the brakes on chloroplast stress signaling

As sessile organisms, plants must be able to sense their surroundings and adjust. One way plants do this is by using their energy-producing organelles (chloroplasts and mitochondria). During environmental stress, these organelles experience metabolic changes that induce signals for acclimation. While many metabolites have been proposed as signaling factors, reactive oxygen species (ROS) are known to play prominent roles. In the chloroplast, the ROS singlet oxygen ( 1 O 2 ) is naturally produced during impaired photosynthesis and can lead to retrograde signaling to the nucleus (to control the expression of hundreds of genes), chloroplast degradation, and cell death. The mechanisms controlling these pathways have mostly remained obscure. Recently, Dogra et al. (2022) reported a new role for EXECUTER2 (EX2) in these chloroplast 1 O 2 signaling pathways, demonstrating that EX2 acts as a buffer to prevent premature activation of 1 O 2 signaling. Furthermore, these exciting findings reveal an unexpected complexity to chloroplast stress signaling, and identify a decoy mechanism to prevent early activation of cell death.

59 BASIC BIOLOGICAL SCIENCES↗

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗

Polymer-Based Thermally Stable Chemiresistive Sensor for Real-Time Monitoring of NO 2 Gas Emission

Here, we present a thermally stable, mechanically compliant, and sensitive polymer-based NO 2 gas sensor design. Interconnected nanoscale morphology driven from spinodal decomposition between conjugated polymers tethered with polar side chains and thermally stable matrix polymers offers judicious design of NO 2 -sensitive and thermally tolerant thin films. The resulting chemiresitive sensors exhibit stable NO 2 sensing even at 170 °C over 6 h. Controlling the density of polar side chains along conjugated polymer backbone enables optimal design for coupling high NO 2 sensitivity, selectivity, and thermal stability of polymer sensors. Lastly, thermally stable films are used to implement chemiresistive sensors onto flexible and heat-resistant substrates and demonstrate a reliable gas sensing response even after 500 bending cycles at 170 °C. Such unprecedented sensor performance as well as environmental stability are promising for real-time monitoring of gas emission from vehicles and industrial chemical processes.

47 OTHER INSTRUMENTATION↗

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Benzenesulfonamide Derivatives as Complexants and Extractants for Addressing the Mercury Problem at the Savannah River Site

Mercury (Hg) is a major global pollutant arising from both natural and anthropogenic sources. Its widespread use in medicinal and industrial applications makes it a common chemical exposure and environmental pollutant. It can exist in several forms which include: Metallic mercury (Hg{sup 0}), mercurous (Hg{sub 2}{sup 2+}), mercuric salts (Hg{sup 2+}), and organic mercury (e.g. CH{sub 3}Hg{sup +}), with the latter being the most toxic of all the species. Due to mercury's high toxicity, new approaches towards its detection has received significant attention in the scientific community. Mercury exposure at the Savannah River Site (SRS) has been a recent concern especially with increasing amounts of organic mercury in the saltstone. It originates mainly from its use as an acidic dissolution catalyst of aluminum cladding from target fuels within the uranium and plutonium processing operations [1]. It is present to an amount of about 60 metric tons in the high-level waste (HLW) tanks. Organic Mercury species have been found in low activity waste (LAW) at the site that eventually ends up in the saltstone. Therefore, there is a need for: i) Converting organic mercury to other less toxic forms and ii) Complexation and removal of Hg prior of disposal of LAW in saltstone. Various methods have been developed for selective sensing of mercury in the presence of other toxic metals. These methods include using ligands that can form organo-soluble metal complexes with different optical and spectroscopic properties that can be used for toxic metal sensing. In 2005, our group pioneered an ion-exchange extraction method, in which o-phenylenediamine-derived disulfonamides were used to complex and selectively extract and sense Pb{sup 2+} from aqueous solutions into an organic phase [2,3]. Herein, a disulfonamide and a bis-dansylamide have been shown to extract, complex and sense Hg(II). Ligand 1: The crystal structure of the disulfonamide-Hg complex confirms the complexation of Hg(II) with the ligand. Complexation was corroborated by the {sup 1}H-NMR spectra obtained after contacting solutions of various concentrations of Hg{sup 2+} with 2 mM ligand in chloroform. Distinct resonances are observed at Hg/L ratio of 0.5 that are also observed for the isolated 1:2 complex. In the presence of excess mercury, new resonances, as well as the movement of Et{sub 3}N resonances indicate the formation of a different Hg-sulfonamide-triethylamine complex, presumably having 1:1 Hg:L stoichiometry. The electronic spectra of aqueous phases after extraction show that there was no free ligand absorption at 0.5 eq of Hg, indicating a complete complexation. Complexation was also confirmed by the UV-visible titrations with Hg{sup 2+} at constant ligand concentration. pH-dependent extraction carried out shows that extraction of Hg(II) by ligand 1 was over 90% for most alkaline pHs. Ligand 2: The crystal structure of the Ligand 2 complex formed with Hg(OAc){sub 2} shows a remarkable coordination pattern with 4:2 metal:ligand stoichiometry. The fluorescent bis-dansyl disulfonamide derivative was found to complex and sense HgCl{sub 2} and Hg(OAc){sub 2} by demonstrating fluorescence quenching upon Hg(II) addition in comparison with other metals (Zn(II), Cd(II), Pb(II)). No were observed for Cu(II), Ag(I) and Co(II). We have shown the complexation of Hg(II) by a disulfonamide and a bis-dansyl disulfonamide ligand using several spectroscopic methods. Ligand 1 was able to extract mercury into chloroform and form a complex in the presence of excess mercury by synergistic complexation with triethylamine acting as a co-ligand. X-ray and NMR both confirm a 1:2 HgL{sub 2} stoichiometry. Ligand 2 can be used for sensing of Hg(II) as fluorescence quenching was observed after addition of Hg(II)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ion Exchange Gels Allow Organic Electrochemical Transistor Operation with Hydrophobic Polymers in Aqueous Solution

Conjugated-polymer-based organic electrochemical transistors (OECTs) are being studied for applications ranging from biochemical sensing to neural interfaces. While new polymers that interface digital electronics with the aqueous chemistry of life are being developed, the majority of high-performance organic transistor materials are poor at transporting biologically relevant ions. Here, the operating mode of an organic transistor is changed from that of an electrolyte-gated organic field-effect transistor (EGOFET) to that of an OECT by incorporating an ion exchange gel between the active layer and the aqueous electrolyte. This device works by taking up biologically relevant ions from solution and injecting more hydrophobic ions into the active layer. Using poly[2,5-bis(3-tetradecylthiophen-2-yl) thieno[3,2-b]thiophene] as the active layer and a blend of an ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, and poly(vinylidene fluoride-co-hexafluoropropylene) as the ion exchange gel, four orders of magnitude improvement in device transconductance and a 100-fold increase in kinetics are demonstrated. The ability of the ion-exchange-gel OECT to record biological signals by measuring the action potentials of a Venus flytrap is demonstrated. These results show the possibility of using interface engineering to open up a wider palette of organic semiconductors as OECTs that can be gated by aqueous solutions.

Bischak, Connor G.↗

Membrane potential sensing: Material design and method development for single particle optical electrophysiology

We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.

59 BASIC BIOLOGICAL SCIENCES↗

Pressure–Modulated Luminescence Enhancement and Quenching in a Hydrogen–Bonded Organic Framework

Light emission in the solid state is central for illumination, sensing, and imaging applications. Unlike luminescence in dilute solutions, where the excited states are unimolecular in nature, intermolecular interaction plays a significant role in the quantum yield of solid-state luminophores, manifested as competing aggregation-caused quenching (ACQ) and aggregation-induced enhancement (AIE). Both effects are extensively studied in various systems; however, it remains unclear how their competition depends on molecular conformation and intermolecular stacking. Here the direct observation of pressure-modulated AIE-ACQ competition in a crystalline hydrogen-bonded organic framework (HOF) is reported. Using in situ spectroscopies and computational modeling, the intramolecular vibration and intermolecular π–π stacking directly responsible for the non-radiative decay of the excited state are identified. The extent of these two contributions is modulated by hydrostatic pressure and guest molecules in the HOF pores. Furthermore, this work demonstrates a physically neat model system to understand and control solid-state luminescence, and a potential material platform for piezoluminescent sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗