Volatile Behavior Research Articles

Design and synthesis of pyridine-bridged benzothiazole-based D-A system for SRAM memory devices

This study focused on designing small donor-acceptor (D-A) frameworks for resistive memory devices. We synthesized five new organic molecules using pyridine bridged to benzothiazole and various donor moieties (triphenylamine, naphthalene, benzothiophene, t-butyl phenyl, and mesityl group) via Suzuki cross-coupling to study their memory performance. The compounds with triphenylamine and naphthalene exhibited good semiconductor behavior, with a band gap of 3.11 eV and 3.44 eV, respectively. The benzothiazole moiety, employed as a shallow trap in the acceptor segment, demonstrated the SRAM characteristics of all devices. This study examined how varying the potency of electron-donating substituents impacts charge transfer and volatile memory behavior in a small D-A system. Memory devices with triphenylamine and naphthalene donors showed binary SRAM behavior with high ON/OFF ratios of 2.82 × 103 and 2.36 × 103, while t-butylphenyl and mesityl donors exhibited lower ratios of 1.43 × 101 and 4.08 × 101, respectively. All the compounds exhibited switching characteristics at a low threshold voltage of −1 to −1.3 V. The analysis of HOMO, LUMO energy levels, and ESP images of all compounds from the DFT study, collectively indicate charge transfer and trapping are the operative mechanisms in volatile SRAM devices.

All-in-One Magneto-optical Memory Arrays Based on a Two-Dimensional Ferromagnetic Metal.

Two-dimensional (2D) van der Waals (vdW) magnetic materials with atomic-scale thickness and smooth interfaces promise the possibility of developing high-density, energy-efficient spintronic devices. However, it remains a challenge to effectively control the perpendicular magnetic anisotropy (PMA) of 2D vdW ferromagnetic materials, as well as the integration of multiple memory cells. Here, we report highly efficient magneto-optical memory arrays by utilizing the huge spin-orbit torques (SOT) induced by the in-plane current in Fe3GeTe2 (FGT) flake. The device is constructed from individual FGT flakes without heavy metal assistance and allows for a low current density. The magneto-optical memory arrays implement nonvolatile memories for three bits and can be repeatedly scrubbed for "writing" and "reading". Besides, we show that FGT nanoflakes possess current-controlled volatile switching behavior at zero magnetic field. These results provide a solution for the next generation of all-vdW-scalable, high-performance spintronic logic devices and SOT-Magnetic Random Access Memory (MRAM).

Accretion and Core Formation of Earth-like Planets: Insights from Metal–Silicate Partitioning of Siderophile and Volatile Elements

The origin of volatile elements, the timing of their accretion and their distribution during Earth’s differentiation are fundamental aspects of Earth’s early evolution. Here, we present the result of a newly developed accretion and core formation model, which features the results of high P–T metal–silicate partitioning experiments. The model includes well-studied reference elements (Fe, Ni, Ca, Al, Mg, Si) as well as trace elements (V, Ga, Ag, Au, S) covering a wide range from refractory to volatile behavior. The accretion model simulates the different steps of planet formation, such as the effects of continuous, heterogenous core formation at high P–T, the effect of the Moon-forming giant impact and the addition of matter after the core formation was completed, the so-called “late veneer”. To explore the “core formation signature” of the volatile depletion patterns and the quantitative influence of a late veneer, we modeled planets that would have formed from known materials, such as CI, CM, CV, CO, EH and EL meteorites, and from a hypothetical volatile depleted material, CI*. Some of the resulting planets are Earth-like in key properties, such as overall core size, major element composition, oxygen fugacity and trace element composition. The model predicts the chemical signatures of the main planetary reservoirs, the metallic core and bulk silicate planet (BSP) of the modeled planets, which we compare with the chemical signature of Earth derived previously from core formation models and mass balance-based approaches. We show that planets accreted from volatile depleted carbonaceous chondrites (CM, CV, CO and CI*) are closest in terms of major element (Si, Mg, Fe, Ca, Al, Ni) and also siderophile volatile element (Ge, Ga, Au) concentrations to the components from which Earth accreted. Chalcophile volatile elements (S, Ag), instead, require an additional process to lower their concentrations in the BSP to Earth-like concentrations, perhaps the late segregation of a sulfide melt.

Soil ammonia volatilization after fertilization using antibiotic-contaminated swine wastewater

The application of wastewater from pig farming is an alternative to fertilize crops using the effluent produced in the activity. However, in addition to nutrients capable of meeting the needs of crops, this effluent also has residues of antibiotics for livestock use in its composition, which can interfere with the activity of soil microorganisms and reduce the enzymatic activity, leading to nitrogen losses into the atmosphere. Hence, this study evaluated ammonia volatilization behavior after adding swine wastewater with tetracycline-class antibiotics. Pots containing soil received doses of raw and digested wastewater (0.06 and 0.09 L), combined or not with doses of tetracycline (35 µg L-1), chlortetracycline (40.9 µg L-1), and doxycycline (14.9 µg L-1 volatilized NH3 was collected by foam absorbers containing phosphoric acid solution on the soil, which were changed every 48 h, totaling 11 collections at a time. The NH3 volatilization significantly increased when the swine wastewater (raw or digested) was added. The presence of antibiotics reduced NH3 losses, showing that they can inhibit urease activity. Our findings showed that tetracycline-class antibiotics can inhibit urease activity, contributing to the continuity of nitrogen in the soil.

Enhanced analog switching and neuromorphic performance of ZnO-based memristors with indium tin oxide electrodes for high-accuracy pattern recognition.

This study systematically investigates analog switching and neuromorphic characteristics in a ZnO-based memristor by varying the anodic top electrode (TE) materials [indium tin oxide (ITO), Ti, and Ta]. Compared with the TE materials (Ti and Ta), memristive devices with TEs made of ITO exhibit dual volatile and nonvolatile switching behavior and multistate switching characteristics assessed based on reset-stop voltage and current compliance (ICC) responses. The polycrystalline structure of the ZnO functional layer sandwiched between ITO electrodes was confirmed by high-resolution transmission electron microscopy analysis. The current transport mechanism in the ZnO-based memristor was dominated by Schottky emission, with the Schottky barrier height modulated from 0.26 to 0.4V by varying the reset-stop voltage under different ICC conditions. The long-term potentiation and long-term depression synaptic characteristics were successfully mimicked by modulating the pulse amplitudes. Furthermore, a 90.84% accuracy was achieved using a convolutional neural network architecture for Modified National Institute of Standards and Technology pattern categorization, as demonstrated by the confusion matrix. The results demonstrated that the ITO/ZnO/ITO/Si memristor device holds promise for high-performance electronic applications and effective ITO electrode modeling.

Mapping Risk–Return Linkages and Volatility Spillover in BRICS Stock Markets through the Lens of Linear and Non-Linear GARCH Models

This paper explores the influence of the risk–return relationship and volatility spillover on stock market returns of emerging economies, with a particular focus on the BRICS countries. This research is undertaken in a context where discussions on de-dollarization and the expansion of BRICS membership are gaining momentum, making it a novel and distinct exercise compared to prior studies. Utilizing econometric techniques to investigate daily market returns from 1 April 2008 to 31 March 2023, a period that witnessed major events like the global financial crisis, the COVID-19 pandemic, and the Russia–Ukraine conflict, linear and non-linear models like ARCH, GARCH, GARCH-M, EGARCH, and TGARCH, are employed to assess stock return volatility behaviour, assuming a Gaussian distribution of error terms. The diagnostic test confirms that the distribution is non-normal, stationary, and heteroscedastic. The key findings indicate a lack of the risk–return relationship across all BRICS stock markets, except for South Africa; a more pronounced effect of unpleasant news over pleasant news; a slow mean-reverting process in volatility; the EGARCH model is the best fit model as evidenced by a higher log likelihood and lower Akaike information criterion and Schwardz information criterion parameters; and finally, the presence of significant bidirectional and unidirectional spillover effects in the majority of instances. These findings are valuable for investors, regulators, and policymakers in enhancing returns and mitigating risk through portfolio diversification and informed decision making.

Effects of the Characterization Methods of Heptane Plus Components (C7+) on the Phase Behavior of Volatile Fluids

For reservoir fluids with strong volatile tendencies, such as gas condensate and volatile oil, the determination of the characteristic parameters of the equation of state has a great influence on the fluid phase behavior and subsequent reservoir engineering, production engineering, and surface facilities design calculations. However, the process of characterizing reservoir fluid lacks a unified and standardized procedure, and the methods are largely empirical and rather complicated. In this paper, three main stages are defined for the characterization of the equation of state parameters for these volatile reservoir fluids, including (1) determining the C7+ distribution, (2) calculating the equation of state parameters for the C7+ single-carbon component, and (3) lump components. The typical calculation methods in each step and their effects on the fluid phase behavior calculations are quantitatively analyzed and compared. Finally, the workflow and the suitable characterization methods for gas condensate and volatile oil phase behavior calculations are selected. The results show that C7+ distribution and C7+ single carbon component properties have a greater influence on the phase behavior prediction of condensate gas and volatile oil, while the lumping of C7+ single carbon component has relatively little influence.

Seasonality Effects, Stock Exchange and Foreign Exchange Markets: Comparative Analysis of Volatility Behavior During Covid-19

This study investigated the effects of seasonality on stock exchange and foreign exchange markets of two WAMZ and two BRICS countries which include Nigeria, Ghana, and Brazil and China. The Auto Regressive Integrated Moving Average (ARIMA) regression approach and the Markov-regime switching methodologies were executed. The parsimonious ARIMA estimates reported Nigeria’s stock returns demonstrated lower volatility (SIGMASQ = 0.000141) than Ghana’s stock returns (SIGMASQ = 0.004003). Similarly, Nigeria had a lower returns volatility than Ghana (SIGMASQ = 0.001829 < 0.07727) in the foreign exchange market of their respective local currencies in relation to the US dollar during the covid-19 era. Comparatively, Nigeria’s stock and foreign exchange market performance showed lower returns volatility behaviour than Ghana’s markets during the covid-19 period. Brazil’s stock returns and the foreign exchange market return on the Brazilian Real had higher volatility compared to the Chinese stock market returns and the return on the Chinese Yuan exchange rate vis-à-vis the US dollar during the covid-19 era. Comparatively, Brazil’s stock and foreign exchange performance showed higher returns volatility behaviour than China during the covid-19 period. The ARIMA estimates were upheld by the Markov-switching regression results which reveal highest volatility effect of the foreign exchange market in Ghana and Brazil. Ghana's stock market volatility reverted more quickly than that of Nigeria, while in the second and third regimes, volatility of the Nigeria's stock exchange reverted more speedily than that of Ghana. The Markov estimates also reveals that China had more time than Brazil for stock market volatility to be repaired in the first regime, 40.43 months as against 36.77 months but a much lower time for China’s stock volatility to be restored in the second and third regimes, during and after the covid-19 pandemic. The expected durations in the regimes for the Brazilian forex market are 40.96, 47.98, and 33.99 months compared to 29.78, 27.55, and 21.65 months in the first, second, and third regimes. The study thus established that volatility on the returns of the Brazilian foreign exchange market before, during, and after the covid-19 pandemic takes longer time to die off unlike in the case of China’s forex market. The empirical findings validate the significance of the business cycle theory in these markets. Accordingly, our findings explicate the presence of sizable effects of cyclical swings on the stock and foreign exchange markets of Ghana, and Brazil compared to that of Nigeria and China respectively.

The Impact of COVID-19 Pandemic on the Jordanian Stock Market Returns Volatility: Evidence from ASE20

This research examines the impact of the COVID-19 pandemic on the volatility behavior of Amman Stock Exchange (ASE) returns using ARMA–GARCH-type models for three sub-periods: pre-COVID-19, during COVID-19, and post-COVID-19. The research finds that volatility persistence is significant across all periods, with the pandemic period showing the highest impact of shocks. Bad news has no statistically significant impact on volatility in the pre-COVID-19 period or during the pandemic, while in the post-pandemic period, good news significantly influences volatility. Additionally, there exist notable changes in the autocorrelation and the shock structure of the AR and MA components. Considering these alterations in the asymmetric effects, the AR and MA components suggest significant shifts in market dynamics, investor sentiments, and economic policies in response to pandemic experiences.

Electrically-driven IMT and volatile memristor behavior in NdNiO3 films

Abstract Transition metal oxides with insulator-metal transitions (IMTs) are uniquely suited for volatile memristor devices that mimic the spiking of biological neurons. Unlike most non-volatile memristors, which often operate via ion migration into filaments, volatile devices utilize a reversible phase change that returns to a ground state in the absence of applied stimulus. In these devices, Joule heating triggers the IMT and changes the bulk resistivity rather than influencing conduction through defects, as in previous studies. This volatile resistive switching behavior has previous been leveraged in niobium and vanadium oxides, but not in rare-earth nickelates, despite their tunable transition temperatures. This study demonstrates an electrically driven IMT in the prototypical rare-earth nickelate, NdNiO3, in large area devices. While previous work examining the electrically-driven IMT in NdNiO3 suggests defect-dominated conduction, this study shows clear s-type negative differential resistance (NDR) consistent with temperature-dependent resistivity measurements. The NDR peak-to-valley voltage scales linearly with temperature as expected for conductivity pathways dominated by bulk IMT behavior. Unlike other transition metal oxides, which are modeled using the insulator-metal phase fraction as the internal state variable, a thermoelectric model with temperature as the internal state variable is found to more accurately describe the current–voltage characteristic of NdNiO3 volatile memristors. Overall, we report the synthesis, fabrication, and characterization of NdNiO3 volatile memristors with resistivity dominated by bulk-like IMT behavior which is scalable and not dependent upon oxygen vacancy migration or defect mediated conduction pathways.

Synthesis and Anisotropic Memristive Behavior of Borophene Nanosheets

Neuromorphic computing, marked by its parallel computational abilities and low power usage, has become pivotal in advancing artificial intelligence. However, the advancement of neuromorphic computing has faced significant obstacles due to the performance limitations of traditional memory devices struggling with high power consumption and limited reliability. Two‐dimensional (2D) materials have been extensively investigated as high‐performance memristive materials, but they are often restricted by fixed memristive properties, which complicate circuit design and limit flexibility. Here, we report that multilayer borophene nanosheets represent a breakthrough material, displaying anisotropic variable memristive properties. The nanosheets, comprising semiconductor α’‐4H‐borophene sheets and metal β12‐borophene sheets, have been synthesized on aluminum foil surface through chemical vapor deposition (CVD) method. The multilayer borophene nanosheets exhibit volatile memory behavior in the vertical direction and non‐volatile memory behavior in the planar direction. This innovative class of 2D nanosheets not only overcomes the limitations of conventional memory devices but also expands the potential applications of borophene‐based memories in information storage and in‐memory computing.

Synthesis and Anisotropic Memristive Behavior of Borophene Nanosheets.

Neuromorphic computing, marked by its parallel computational abilities and low power usage, has become pivotal in advancing artificial intelligence. However, the advancement of neuromorphic computing has faced significant obstacles due to the performance limitations of traditional memory devices struggling with high power consumption and limited reliability. Two-dimensional (2D) materials have been extensively investigated as high-performance memristive materials, but they are often restricted by fixed memristive properties, which complicate circuit design and limit flexibility. Here, we report that multilayer borophene nanosheets represent a breakthrough material, displaying anisotropic variable memristive properties. The nanosheets, comprising semiconductor α'-4H-borophene sheets and metal β12-borophene sheets, have been synthesized on aluminum foil surface through chemical vapor deposition (CVD) method. The multilayer borophene nanosheets exhibit volatile memory behavior in the vertical direction and non-volatile memory behavior in the planar direction. This innovative class of 2D nanosheets not only overcomes the limitations of conventional memory devices but also expands the potential applications of borophene-based memories in information storage and in-memory computing.

Quantification of evaporative loss of volatile metals from planetary cores and metal-rich planetesimals

The processes responsible for the isotopic compositions and abundances of volatile elements in the early solar system remain highly debated. Orders of magnitude variation of (highly) volatile elements exist between different magmatic iron meteorite groups, but it is unclear to what extent their depletions can be explained by evaporation from metal melts during parent body accretion and/or subsequent break up. To this end, we present 86 new evaporation experiments with the aim of constraining the volatility of most volatile metals from metallic melts. The results confirm the previously proposed important effects of S in metal melt on the volatility of the elements of interest governed by their S-loving or S-phobic behavior. Nominally S-loving elements In, Sn, Te, Pb and Bi are significantly more volatile in Fe melt relative to FeS liquid, whereas nominally S-avoiding elements Ga and Sb are more volatile in FeS liquid relative to Fe melt, at a given pressure and temperature. The newly derived volatility sequences for S-free/poor and S-rich metallic melts were also compared with commonly used volatility models based on condensation temperatures. The results indicate significant differences between the latter, including the much more volatile behavior of Te, relative to Se, in both explored bulk compositions, which are traditionally assumed to be equally volatile. The (minimum) degree of volatile element depletion due to evaporation was quantified using the new experimental results and models. A comparison between the volatile element depletions in magmatic iron meteorites and the predicted depletions appropriate for evaporation from Fe melts shows that the latter depletions can be easily reconciled with (an) evaporation event(s). Altogether, the new data and models will provide an important framework when more accurate and precise estimates of magmatic iron meteorite bulk volatile element contents are available.

Artificial optoelectronic synapse based on CdSe nanobelt photosensitized MoS2 transistor with long retention time for neuromorphic application

Abstract Optoelectronic synaptic devices have been regarded as the key component in constructing neuromorphic computing systems. However, the optoelectronic synapses based on conventional 2D transistor are still suffering low photosensitivity and volatile retention behavior, which can affect the recognition accuracy and long-term memory. Here, a novel optoelectronic synaptic device based on surface-state-rich CdSe nanobelt photosensitized 2D MoS2 transistor is demonstrated. Benefiting from the excellent light absorption of CdSe and effective charge trapping at the hetero-interface, the device exhibits not only high photosensitivity but also long retention time (>1,500 s). In addition, typical synaptic functions including the excitatory postsynaptic current, paired-pulse facilitation, the transformation from short-term to long-term plasticity, the transformation from short-term to long-term plasticity, spike-amplitude-dependent plasticity, and learning-forgetting-relearning process are successfully simulated and modulated by light stimulation. Most importantly, an artificial neural network is simulated based on the optical potentiation and electrical habituation characteristics of the synaptic devices, with recognition accuracy rates of 89.2, 93.8, and 91.9 % for file type datasets, small digits, and large digits are achieved. This study demonstrates a simple and efficient way to fabricate highly photosensitive optoelectronic synapse for artificial neural networks by combining the merits of specific materials and device architecture.

Lignin pyrolysis assisted by molten salt medium: Evolution behavior of volatiles and biochar structure

This study focuses on the use of a molten salt reaction medium (NaCl-KCl-LiCl) in the lignin pyrolysis process to modify the pyrolysis volatiles and biochar structure. The effect of pyrolysis reaction temperature (300°C, 400°C, 500°C, and 600°C) and lignin/molten salt mass ratios (3:1, 1:1, 1:3 and 1:5) on the evolution behavior of volatiles and biochar structure was explored. The pyrolysis products were determined using GS-MS, CO2 adsorption-desorption analyses, SEM, elemental analysis, proximate analysis, Raman, XRD, and TG/DTG analysis. Results indicated that the introduction of molten salt can enhance the lignin depolymerization, leading to the production of phenolic precursors. Moreover, the metal cation (Na+, K+ and Li+) of molten salt can in-situ induce the modification of biochar structure with high porosity. The lower sulfur content in biochar was attributed to the immobilize function of molten salt. The evolution behaviour of volatiles and biochar structure during molten salt-assisted lignin pyrolysis was proposed. This study can serve as a benchmark for the high-value recycling of industrial lignin waste.

DISAPPEARING THE DAY OF THE WEEK EFFECT ON RETURN TO INVESTORS: NOVEL EVIDENCE FROM INDIAN STOCK MARKET

The efficiency in emerging markets is becoming more important as the trend of investment in these markets is accelerating nowadays. The level of market efficiency influences an investor's investment strategy because of its improper valuation. The improper valuation of securities may lead to abnormal gains for the investor. On the other hand, abnormal gain in a perfectly efficient market is impossible as the share price absorbs all the information available in the public domain. However, efficiency in its finest sense is a distant reality. Many researchers have pointed out different levels of efficiencies, including the presence of calendar anomalies. The purpose of the study is to capture the effect of the day of the week on the stock return and volatility in India. Daily time series data of Sensex and Nifty were collected from the two prominent exchanges of India, i.e. Bombay Stock Exchange and National Stock Exchange websites, for a period of four years. After validating stationarity with ADF and Phillip-Perron tests, the study used GARCH, EGARCH and TGARCH models to capture day impacts on stock return and volatility. The study reveals that the Tuesday effect persisted in the Indian stock market during the study period. Moreover, the TGARCH model was found to be the most suitable model for describing volatility behaviour in the Indian stock market. As other days in the week were less significant, the study's findings suggest that the gradual disappearance of day affects the Indian capital market. Another study finding is the significance of the leverage effect, which implies the increased role of bad news over good news while capturing the day-of-the-week effect. Considering the above facts, the present study's findings contribute to a deeper understanding of stock market dynamics and the challenge of the day-of-the-week effect on market efficiency.

Volatility Behaviour of Currency Exchange Rates in Selected Countries: Long Memory Effect

Volatility Behaviour of Currency Exchange Rates in Selected Countries: Long Memory Effect

Sectoral Volatility in Borsa Istanbul: A GARCH-based Comparative Analysis

This study delved into the complex landscape of sectoral volatility dynamics within Borsa Istanbul, a dynamic emerging market, using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. By analyzing a dataset spanning from March 1, 2013, to August 16, 2023, the research examined how different sectors respond to market shocks and how these responses vary across sectors. The findings revealed distinct volatility behaviors among sectors, with the BIST Financial Leasing Index (FINK) displaying heightened vulnerability to external shocks, while the BIST Banking Index (BNK) and BIST Financial Index (MALI) exhibited comparatively milder volatility responses. Policymakers, regulators, and investors can utilize these insights to tailor risk management strategies, enhance market stability, and construct portfolios that align with risk preferences. This research enriches the understanding of sectoral dynamics in emerging markets, offering a foundation for future investigations into the intricate interplay between sectors, shocks, and volatility patterns.

The Effects of Bitcoin ETFs on Traditional Markets: A Focus on Liquidity, Volatility, and Investor Behavior

The Effects of Bitcoin ETFs on Traditional Markets: A Focus on Liquidity, Volatility, and Investor Behavior

High performances of cellulose nanocrystal based bicomponent supramolecular hydrogel lubricant

To improve the limitations of water-based lubricants, a novel cellulose nanocrystal based supramolecular hydrogel (CNC/x-DG/y) was prepared by mixing cellulose nanocrystal (CNC) and diglycerol (DG) into deionized water (DW). The hydrogel was characterized to determine its material ratio and gelation mechanism. When DW was fixed at 1 mL, CNC content should be no <2.4 wt% and DG content 0.1–1.3 mL. The gelification was driven by the multiple H-bond network between CNC and DG, which immobilized water molecules. The rheological performances, the anti-rust property and the volatilization behaviour of the hydrogel were further studied. The results showed that the hydrogel had satisfactory viscoelasticity, excellent thermal stability, strong creep recovery, high anti-rust performance and low volatilization rate, which were exactly its advantages for use as lubricant. A typical representative of the hydrogel, namely CNC/2.4-DG/0.1, was selected to evaluate the tribological performances, and the resulting worn surfaces were analyzed. CNC/2.4-DG/0.1 exhibited a lower friction coefficient of 0.059 and a smaller wear volume of 0.81 × 10−3 mm3, compared to DW(1 mL) + CNC(2.4 wt%) and DW(1 mL) + DG(0.1 mL). The outstanding tribological performances of CNC/2.4-DG/0.1 were reasonably attributed to the synergistic mending effect of CNC and DG and the dissipative effect of H-bonds between the two.