Reactive Behavior Research Articles

Complexion-induced Cu2+ coordinated phase separation PBI membrane for lithium metal batteries

The uncontrolled dendritic lithium production issues and the highly reactive behavior of lithium with electrolytes has limited use of lithium metal batteries. Herein, we utilized a straightforward method of the Complexion-Induced Phase Separation (CIPS) to fabricate a Cu2+ coordinated polybenzimidazole (PBI) membrane for a lithium metal battery. CIPS offer improved control over the structure and composition of the membrane, potentially leading to improved selectivity in ion transport, enhancing the safety and longevity of the battery. The formation mechanism and influencing elements of PBI-Cu are analyzed through experimental analysis and density functional theory calculations (DFT). The PBI-Cu membrane is effective in facilitating reversible lithium stripping and plating processes, suppressing dendrite formation, and promoting stable long-term cycling. Notably, the PBI-Cu cell demonstrated stable cycling conditions for over 200 h at a very high current density of 4 mA cm−2. The impressive rate performance was also confirmed during Li//LiFePO4 full cell operation, where it maintained a stable capacity of 120 mAh g−1 for more than 300 cycles. This research provides an in-depth insight into membrane design and paves the way for its application in various other energy-related technologies.

Intermittent escitalopram treatment and reactive aggression in women with premenstrual irritability and anger: A crossover study

BackgroundSelective serotonin reuptake inhibitors (SSRI) are the primary treatment for premenstrual mood symptoms and particularly effective in reducing reactive aggression in the forms of irritability and anger.The present study examined whether behavioral responses in laboratory measures of reactive aggression are influenced by medication with the SSRI escitalopram in women reporting high levels of premenstrual irritability/anger. MethodsParticipants (N = 34) rated the cardinal mood symptoms of premenstrual dysphoric disorder over three menstrual cycles. During the second and third cycles, participants received escitalopram (20 mg) or placebo in a single-blind, cross-over design. In the luteal phase of the intervention cycles, participants completed two aggression tasks: The Anger-Infused Ultimatum Game (AI-UG) and the Point Subtraction Aggression Paradigm (PSAP). Additionally, they rated expression and control of anger using the State-Trait Anger Expression Inventory-2 (STAXI-2) once in the luteal phase and once in the follicular phase. ResultsWhile irritability/anger was reduced in the treatment (vs. placebo) cycle, no effect of escitalopram was detected in the PSAP. Escitalopram decreased reactive aggressive behavior in the AI-UG but only for a subset of participants who experienced a sharp premenstrual rise in outwardly expressed anger and/or did not experience a premenstrual rise in inwardly expressed anger. LimitationsThe participants' symptoms were based on the severity of only premenstrual irritability/anger, limiting the generalizability to the broader group of PMDD patients. ConclusionThe results suggest that the behavioral consequences of severe premenstrual irritability/anger are not easily captured by traditional measures of reactive aggression and underline the importance of considering individual differences in symptom expression.

Simulation of lithium hydroxide decomposition using deep potential molecular dynamics.

Chemical reactions and vapor-liquid equilibria for molten lithium hydroxide (LiOH) were studied using molecular dynamics simulations and a deep potential (DP) model. The neural network for the model was trained on quantum density functional theory data for a range of conditions. The DP model allows simulations over timescales of hundreds of ns, which provide equilibrium compositions for the systems of interest. Single-phase NPT simulations of the liquid show the decomposition of LiOH into lithium oxide (Li2O) and dissolved water (H2O). These DP results were validated by direct abinitio molecular dynamics simulations that confirmed the accuracy of the model with respect to reaction kinetics and equilibrium properties of the melt. The reactive vapor-liquid behavior of this system was subsequently studied using direct coexistence interfacial DP simulations. Partial pressures of H2O in the vapor are found to be in close agreement with available experimental measurements. By fitting temperature-dependent expressions for the reaction equilibrium and Henry's law constants, the equilibrium composition for any given initial composition and temperature can be quantitatively modeled. For high initial concentrations of Li2O or H2O, mixtures of LiOH + Li2O/H2O are found to undergo phase separation. The present study illustrates how DP-based molecular dynamics simulations can be used for quantitative modeling of multiphase reactive behavior with the accuracy of the underlying abinitio quantum chemical methods.

Nightmares in the elderly: Associations with self-reported executive functions

Study objectivesTo describe nightmare phenomenology among community dwelling elderly and to test the hypothesis that reduction in cognitive control is associated with nightmare-related phenomenology including nightmare frequency and severity, greater emotional reactivity, imagery immersion, and dream enactment behaviors (DEBs). MethodsStudy 1: Survey with multiple regression and ANOVAs on N = 56 people with frequent nightmares plus N = 62 age- and gender-matched controls to quantify the strength of the association between cognitive control variables and nightmare phenomenology. Study 2: Computational simulation of nightmare phenomenology in relation to cognitive control to simulate the empirical findings and to assess the underlying causal theory through computationally supported causal inference. ResultsStudy 1: Regressions demonstrated a strong association between reduction in cognitive control and more extreme nightmare phenomenology, including severity, frequency, daytime effects, and DEBs. Study 2: The computational simulation of nightmare phenomenology in relation to cognitive control is validated relative to regressions from study 1 and offers computational support for the causal theory explaining the associations in study 1. ConclusionsIn aging people, decline in executive cognitive functions, cognitive control, and inhibitory processes reduce cognitive control over emotions, thus contributing to unusual nightmare activity, including more extreme nightmare phenomenology such as more severe nightmares, greater emotional reactivity, deeper imagery immersion, and DEBs.

Cross-Market Volatility Dynamics Among Crude Oil and South Asian Emerging Markets During the COVID-19 Pandemic.

The COVID-19 pandemic had profound impacts on the global economy, initially triggering a severe economic downturn due to widespread lockdowns, this outbreak generated various economic shocks, a major one being the oil price crash. A brief understanding of how this pandemic is affecting the financial markets, empirical analysis is done on three financial markets. Three stock exchange markets are selected from emerging markets in South Asia (Pakistan, China, and India). The world crude oil market is selected as a reference, to how it transmits volatility to South Asian markets during the COVID-19 period. We employ a bivariate BEKK-GARCH model for analyzing the volatility spillover from November 19, 2019, to March 31, 2021. All markets show negative coefficients with the oil market, indicating that the previous day’s shocks in oil prices reduce today's stock market volatility, with significant values for India and Pakistan. China has a negative coefficient while the rest of the two markets show a positive and significant coefficient means past volatilities in the stock market decrease today’s oil market volatility, likely indicating a reactive or adaptive market behavior to stock volatility. Generally, oil price changes have a significant impact on these markets, with both immediate effects (via ARCH terms) and persistent effects (via GARCH terms). The study's findings offer valuable insights for policymakers, as they help identify the direction of spillovers among interconnected economies. Additionally, portfolio investors can use this information to effectively allocate weights to different asset classes when making investment decisions.

Detecting Agitated Behaviors in Nursing Home Residents With Dementia Using Electronic Medical Records

ObjectivesAgitated behaviors (behaviors) are common in nursing home (NH) residents with Alzheimer's disease and related dementias (ADRD). Pragmatic trials of behavior management interventions rely on routinely collected Minimum Data Set (MDS) data to evaluate study outcomes, despite known underreporting. We describe a method to augment MDS-based behavioral measures with structured and unstructured data from NH electronic medical records (EMR). DesignRepeated cross-sectional analyses of EMR data from a single multistate NH corporation. Setting and ParticipantsLong-stay residents (at least 90 days in NH) with ADRD from January 2020 through August 2022. MethodsQuarterly and annual assessments of NH residents with ADRD during the study period were identified. For MDS, any behavior was defined as a score of 1 or higher on the Agitated and Reactive Behavior Scale. For structured EMR data, any behavior was defined as increased resident agitation, verbal aggression, or physical aggression on the Interventions to Reduce Acute Care Transfers, Change in Condition form (INTERACT). For unstructured EMR data, any behavior was defined using keyword searches of free-text orders. ResultsA total of 77,936 MDS assessments for 19,705 long-stay residents with ADRD in 322 NHs were identified; 14.8% (SD 35.6) of residents had behaviors per month using MDS alone, 16.2% (SD 36.9) using MDS and INTERACT, and 18.6% (SD 38.9) using MDS, INTERACT, and orders. Supplementing MDS with EMR data increased behavior identification by 3.8 percentage points (a 25.7% relative increase). Less than 0.5% had behaviors noted in all 3 sources consistently across study months. Conclusions and ImplicationsUsing EMR data increased detectable behaviors vs the MDS alone. The 3 sources captured different types of behaviors and using them together may be a more comprehensive identification strategy. These results are important for better targeting of interventions and allocation of resources to improve the quality of life for NH residents with ADRD-related behaviors.

COVID-19 and redemptions from Irish-resident bond funds

This paper examines net redemptions from bond funds domiciled in Ireland at the onset of the COVID-19 pandemic. We analyse various empirical specifications to determine whether factors such as fund leverage, measures of liquidity, portfolio risk and portfolio concentration, among others, explain outflows from Irish-domiciled bond funds in March 2020. The findings indicate that funds with a larger share of short-term securities and riskier bond portfolios experienced higher redemptions. Our analysis also suggests that fund size and age are significant factors affecting outflows. When examining various sub-samples, we find evidence of more reactive behaviour among investors in actively managed funds compared to passively managed funds. We also find that retail bond funds demonstrate greater sensitivity to risk and leverage, while professional funds show evidence of lower risk aversion. These results provide insights that can help inform policymakers’ view of regulatory tools for market-based finance, a key priority internationally.

Prospective associations of screen time at age 2 with specific behavioral subscales at age 3: a cohort study.

We aim to discover which, if any, of the subscales of internalizing and externalizing behavioral problems at age 3 are still associated with screen time (ST) at age 2 after adjusting for behavioral problems scores at age 2. This study was conducted under the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Information was gathered prospectively, with 7207 mother-child pairs included in the analysis. Children's ST was categorized in hours a day at age 2 (<1, 1-<2, 2-<4, ≥4). We assessed children's behavioral problems using the Child Behavior Checklist for Ages 1½-5 (CBCL) at ages 2 and 3. 'Having behavioral problems' was defined by them being within a clinical range for internalizing behaviors (withdrawn, somatic complaints, anxious/depressed and emotionally reactive) and externalizing behaviors (attention problems and aggressive behaviors) at age 3. Continuous scores on each of the behavioral problem scales at age 2 were used as covariates. Greater ST for children at age 2 was associated with specific subscales for emotionally reactive and aggressive behaviors at age 3. This study found that ST is prospectively associated with some behavioral scales but not others.

Reactive behaviors and mechanism of methane/coal dust hybrid explosions inhibited by NH4H2PO4 and (NH4)2HPO4: A combined ReaxFF-MD and DFT study

Understanding the explosion-inhibition mechanism of methane/coal dust mixtures at the atomic level is crucial. This study employed ReaxFF-MD and DFT calculations to investigate the inhibitory effects of NH4H2PO4 and (NH4)2HPO4 on methane/coal dust explosions. The research examined macroscopic products, chemical bonds, key reaction pathways, and intermediate products. Furthermore, the evolution mechanism of coal molecules involved in the explosion-inhibition reaction was elucidated. The results indicate that NH4H2PO4 inhibits CO2 generation, while (NH4)2HPO4 enhances H2O production. Additionally, the inhibitors affect not only the initial reaction steps of CH4 but also absorb reactive radicals (•H/•O/•OH) and intermediate products (•CH3/CH2O). Compared to NH4H2PO4, the inhibition cycling reactions of (NH4)2HPO4 exhibit greater diversity. Increasing inhibitors’ mass fraction promotes competing reactions among free radicals, which diminishes the inhibition effect on CH4 dehydrogenation, leading to oscillations in explosion-inhibition efficiency. The inhibitors also delay the bond-breaking time for both the aliphatic bond and the ether-oxygen bridge of coal molecules, thereby prolonging the ring-opening reaction time of these molecules.

The influence of toxic leadership on emotional exhaust and reactive work behavior

Companies are impacted by toxic leadership phenomena, resulting in many dissatisfied employees, low morale, and reduced progress. The fundamental mismatch between good leadership and harmful actions of toxic leaders is the primary cause of the problem. Toxic leadership can also be developed from narcissistic behavior of considering personal interests or using humiliation to maintain power. In this context, employees are negatively affected, resulting in higher stress levels, poorer job satisfaction, and a significant decrease in trust. Therefore, this research aims to explore the impact of toxic leadership and other factors on companies. The sample consists of 187 senior employees in the accounting department who worked in manufacturing companies. The results showed that toxic leadership influences role stress, while role stress affects emotional exhaustion and reactive work behavior. Moreover, future research should be conducted using other samples such as hospital employees or pay attention to other aspects related to role stress.

Integration of memory systems supporting non-symbolic representations in an architecture for lifelong development of artificial agents

Compared to autonomous agent learning, lifelong agent learning tackles the additional challenge of accumulating skills in a way favourable to long term development. What an agent learns at a given moment can be an element for the future creation of behaviours of greater complexity, whose purpose cannot be anticipated.Beyond its initial low-level sensorimotor development phase, the agent is expected to acquire, in the same manner as skills, values and goals which support the development of complex behaviours beyond the reactive level. To do so, it must have a way to represent and memorize such information.In this article, we identify the properties suitable for a representation system supporting the lifelong development of agents through a review of a wide range of memory systems and related literature. Following this analysis, our second contribution is the proposition and implementation of such a representation system in MIND, a modular architecture for lifelong development. The new variable module acts as a simple memory system which is strongly integrated to the hierarchies of skill modules of MIND, and allows for the progressive structuration of behaviour around persistent non-symbolic representations. Variable modules have many applications for the development and structuration of complex behaviours, but also offer designers and operators explicit models of values and goals facilitating human interaction, control and explainability.We show through experiments two possible uses of variable modules. In the first experiment, skills exchange information by using a variable representing the concept of “target”, which allows the generalization of navigation behaviours. In the second experiment, we show how a non-symbolic representation can be learned and memorized to develop beyond simple reactive behaviour, and keep track of the steps of a process whose state cannot be inferred by observing the environment.

Diorganotin(IV) derivatives of ONO tridentate Schiff bases: Synthesis, spectroscopic characterization, DFT studies, CT-DNA binding, and plasmid-DNA cleavage studies

Two Schiff bases 2-amino-N'-(5‑bromo-2-hydroxybenzylidene)-3-(4-hydroxyphenyl)propanehydrazide (H2L1) and 2-amino-N'-(5‑chloro-2-hydroxybenzylidene)-3-(4-hydroxyphenyl)propanehydrazide (H2L2) and their six diorganotin(IV) complexes (R = C4H9 (1, 4), CH3 (2, 5), and C8H17 (3, 6)) have been synthesized. Schiff bases (H2L1–2) and their R2SnL1–2 complexes (1–6) have been characterized by CHNS analysis, IR spectroscopy, 1H, 13C, 119Sn NMR, and ES-MS. Schiff bases (H2L1–2) act as a dianionic tridentate ligand coordinated to Sn through phenolic and enolic oxygen and azomethine nitrogen in R2SnL1–2 complexes (1–6). A density functional theory (DFT)-based quantum chemical calculation validated the structures of R2SnL1 (1–3) and R2SnL2 (4–6) at the B3LYP/6‐311G(df,pd)/Def2‐SVP(Sn) and B3LYP/6‐31G(d,p)/Def2‐SVP(Sn) levels of theory, respectively. At these levels of theories, comprehensive electronic structure calculations determined atomic charges at selected atoms. Additionally, a molecular electrostatic potential (MEP) map identified electrostatic potential-varying sites on the molecule's surface, and MEP maps used to identify regions where other molecules might interact or react with the molecules on them. Furthermore, a conceptual-DFT-based global reactivity descriptor determined the stability and reactivity behaviour of R2SnL1–2 complexes (1–6). H2L1–2 and R2SnL1–2 complexes (1–6) have binding constants in the range ∼105 M-1 with CT-DNA, as revealed by UV–visible and fluorescence spectral titrations. UV-visible, fluorescence spectroscopy, and CD studies suggested that H2L1–2 and their R2SnL1–2 complexes (1–6) interact with CT-DNA electrostatically or groove-bound. DNA cleavage studies reveal that H2L1–2 and their R2SnL1–2 complexes (1–6) have ability to cleave the plasmid-DNA from its supercoiled form (SC, I) to nicked form (NC, II). However, n-Bu2SnL2 (4) and n-Oct2SnL2 complex (6) have higher cleavage activity than Schiff bases and other R2SnL1–2 complexes (1–6).

Dutch adaptation of the Prosocial Behavior Questionnaire (PBQ-NL): a validity and reliability study in adolescents and young adults

ABSTRACT This study assessed the psychometric properties of the Dutch translation of the Prosocial Behavior Questionnaire (PBQ-NL), a self-report questionnaire that distinguishes altruistic, reactive, and proactive prosocial behaviours. Participants were 381 Dutch adolescents and young adults aged 13–30 (M age = 18.62, SD = 2.59, 65.1% female). Test-retest reliability data were available for 199 participants. A Confirmatory Factor Analyses supported the three-factor structure of the questionnaire, with adequate six-month test-retest reliability. Altruistic and reactive prosocial behaviours correlated significantly and positively with prosocial behaviours directed at family/peers and the larger society, but not with depression or aggression. Conversely, proactively motivated prosocial behaviour correlated significantly and negatively with prosocial behaviour directed at family and positively with experienced opportunities for contribution to the larger society, aggression, and depression. These findings show that the PBQ-NL is a reliable measure to disentangle self- and other-serving motivations that underly prosociality during adolescence and young adulthood.

From d8 to d1: Iron(0) and Iron(I) Complexes Complete the Series of Eight Fe Oxidation States within the TIMMNMes Ligand Framework.

Reduction of the ferrous precursor [(TIMMNMes)Fe(Cl)]+ (1) (TIMMNMes = tris-[(3-mesitylimidazol-2-ylidene)methyl]amine) to the low-valent iron(0) complex [(TIMMNMes)Fe(CO)3] (2) is presented, where the tris(N-heterocyclic carbene) (NHC) ligand framework remains intact, yet the coordination mode changed from 3-fold to 2-fold coordination of the carbene arms. Further, the corresponding iron(I) complexes [(TIMMNMes)Fe(L)]+ (L = free site, η1-N2, CO, py) (3) are synthesized and fully characterized. Complexes 1-3 demonstrate the notable steric and electronic flexibility of the TIMMNMes ligand framework by variation of the Fe-N anchor and Fe-carbene distances and the variable size of the axial cavity occupation. This is further underpinned by the oxidation of 3-N2 in a reaction with benzophenone to yield the corresponding, charge-separated iron(II) radical complex [(TIMMNMes)Fe(OCPh2)]+ (4). We found rather surprising similarities in the reactivity behavior when going to low- or high-valent oxidation states of the central iron ion. This is demonstrated by the closely related reactivity of 3-N2, where H atom abstraction with TEMPO triggers the formation of the metallacycle [(TIMMNMes*)Fe(py)]+ (5), and the reactivity of the highly unstable Fe(VII) nitride complex [(TIMMNMes)Fe(N)(F)]3+ to give the metallacyclic Fe(V) imido complex [(TIMMNMesN)Fe(NMes)(MeCN)]3+ (6) upon warming. Thus, the employed tris(carbene) chelate is not only capable of stabilizing the superoxidized Fe(VI) and Fe(VII) nitrides but equally supports the iron center in its low oxidation states 0 and +1. Isolation and characterization of these zero- and monovalent iron complexes demonstrate the extraordinary capability of the tris(carbene) chelate TIMMN to support iron in eight different oxidation states within the very same ligand platform.

Exploring the Premelting Transition through Molecular Simulations Powered by Neural Network Potentials

The premelting layer on crystal surfaces significantly affects the stability, surface reactivity, and phase transition behaviors of crystals. Traditional methods for studying this layer—experimental techniques, classical simulations, and even first-principle simulations—have significant limitations in accuracy and scalability. To overcome these challenges, we employ molecular dynamic simulations based on neural network potentials to investigate the structural and dynamic behavior of the premelting layer on ice. This approach matches the accuracy of first-principle calculations while greatly improving computational efficiency, allowing us to simulate the ice–vapor interface on a much larger scale. In this study, we conducted a one-nanosecond simulation of the ice–vapor interface involving 1024 water molecules. This significantly exceeds the time and size scales of previous first-principle studies. Our simulation results indicate complete surface melting. Furthermore, our simulation results reveal dynamic heterogeneity within the premelting layer, with molecules segregated into clusters of low and high mobility.

2D hydrogen bonded organic framework (2D-HOF) in benzodioxane-coupled-pyridine as a charge carrier: Synthesis, structural, quantum computational investigation

This research presents a comprehensive investigation into the synthesis, structural features, and charge carrier properties of a novel 2D Hydrogen-Bonded Organic Framework (2D-HOF) formed by Benzodioxane-Coupled-Pyridine. The synthesis involves the reaction of 2,3-dihydrobenzo[b][1,4]dioxin-6-carbaldehyde with pyridine-2-carbohydrazide in the presence of acetic acid and ethanol solvent, leading to the formation of (E)-2-(2-((2,3-dihydrobenzo[b][1,4]dioxin-6-yl)methylene)hydrazinyl)pyridine (DDMP). Single crystal X-ray diffraction analysis reveals the monoclinic crystal system with the P21/n space group, showcasing a non-planar structure due to a distinctive twisting motion in the dioxane ring. The crystal packing is governed by a complex network of intermolecular interactions, including hydrogen bonds, short contacts, and π-stacking, ultimately forming a stable 2D-HOF. Hirshfeld Surface (HS) analysis provides insights into key interactions, emphasizing the significance of hydrogen bonding, short contacts, and stacking interactions in molecular packing. The 2D fingerprint (FP) plots quantitatively highlight crucial interatomic contacts, with hydrogen bonding, CH…H, and O…H interactions dominating. Molecular Electrostatic Potential (MEP) analysis reveals potential sites for electrophilic and nucleophilic attacks, aiding in predicting reactive sites and charge carrier behavior. Energy framework analysis sheds light on the pairwise interaction energies within the crystal structure, emphasizing the role of dispersive forces in stabilizing the crystal lattice. Density functional theory calculations indicate the molecule's charge transfer capabilities, suggesting its suitability for applications such as batteries, supercapacitors, and solar cells. Additionally, global reactivity parameters suggest that the 2D HOF material has electron and proton conduction capabilities, making it versatile for various applications. Atoms-in-molecules (AIM) topology analysis, particularly non-covalent interaction (NCI) analysis, provides a detailed understanding of intra and intermolecular interactions, highlighting hydrogen bonding and π…π interactions. H-bond binding energy analysis confirms the non-covalent nature of identified interactions, emphasizing their strength and significance.

CFD modeling using reactions kinetics for selective hydrogenation for acetylene in a fixed-bed reactor

Selective hydrogenation of acetylene (SHA) reactions is usually performed in fixed-bed reactors (FBR). The traditional SHA kinetics, when coupled with a three-dimensional computational fluid dynamics (CFD) model, requires improvement to accurately predict SHA reaction outcomes. The SHA microdynamics, when integrated with a three-dimensional CFD model, have not been comprehensively examined. In this paper, a mathematical model based on CFD was developed to simulate the reactive flow behavior of SHA in FBR using a novel OleMax100 catalyst. In this study, a 3D catalyst bed numerical simulation of FBR with coupled microdynamics description of conjugate heat transfer and surface catalytic reaction was carried out, and the accuracy of CFD at different Reynolds numbers (Re) was verified by experimental results, which showed a high degree of agreement between the model and experimental results. The effect of the ratio of tube to pellet diameter (D/d=N) on the fluid flow characteristics and SHA reaction in the bed was investigated, and the catalyst shape was considered. The simulation results show that an increase in N significantly improves the homogeneity of the flow field and the heat and mass transfer between the phases in the FBR, which leads to an increase in the conversion efficiency of acetylene. When N was increased from 4.00 to 6.67, the conversion was enhanced by 6.7 %. Increasing the Re value affects the reactivity, and the SHA reaction exists in a reaction zone where excessive residence time exacerbates the decrease in selectivity. The adopted and novel catalyst microkinetic models can provide some theoretical guidance for the optimal design of the SHA reaction and process improvement in FBR.

Understanding Organic Components of Solid Electrolyte Interphase on the Lithium Metal Anode

Lithium ion batteries have become the dominant form of energy storage used in consumer electronics and, recently, electric vehicles. However, high costs have prevented widespread deployment of lithium ion batteries for applications other than portable electronics, and the safety issues associated with liquid organic electrolytes remain to be addressed. In order to enable the greater utilization of electric vehicles, allow for grid scale energy storage, and meet the demands of new electronic applications, new materials for high energy density batteries must be developed. High capacity electrode materials like lithium metal have the potential to facilitate these technologies, but lithium metal electrodes are presently limited by significant side reactions, poor quality deposition, and the potential to form hazardous dendrites. Therefore, it is important to develop a clear understanding of the surface reactivity and growth behavior of the lithium metal at the interface with the electrolyte in order to enable stable long-term cycling.The products that form as a result of electrolyte decomposition reactions at the electrode interface are known to be extremely important in determining the final cell performance, yet characterizing the organic components of the solid electrolyte interphase (SEI) proves to be challenging with typical techniques. In this presentation we will discuss a combination of in operando and ex situ techniques developed in efforts to more comprehensively characterize the reaction intermediates and organic SEI products of electrolyte reduction reactions. Specifically, we employ electron paramagnetic resonance (EPR) spectroscopy to identify radical intermediates and clarify electrolyte reduction mechanisms. Furthermore, SEI product formation with respect to electrochemical potential and time will be described using data obtained from in operando ATR-FTIR. ATR-FTIR is a powerful method for characterizing organic species, but typical materials such as Ge, Si, and ZnSe react with lithium metal during deposition. In this talk, the development of a diamond based operando cell and its application to the characterization of organosulfur and fluorinated electrolytes will be discussed. With the understanding developed from these two techniques we provide new insights into the formation and chemical nature of SEI components that promote stable cycling of lithium metal electrodes.

The Strategy to Tune Li Stripping/Plating Behavior in Li Alloy Anode

Li metal anode is the most promising anode for high-energy-density batteries due to its high specific capacity (3860 mAh/g) and highest oxidation potential. However, the high reactivity of Li metal with electrolytes and the resultant formation of Li dendrites restrict its practical applications. To tune the reactivity and Li deposition behavior, Li alloys were widely studied and demonstrated to perform better than Li in Li metal batteries.1-4 Here, we studied the electrochemical behavior of one solid-solution phase Li alloy. In this work, the phase transition in the Li stripping process and phase separation after Li plating were observed, which can be attributed to the sluggish Li diffusion in the solid-solution phase of the alloy. To unlock the Li stripping capacity without phase transition, we designed a bi-phase Li composite anode by introducing Li+ conductive materials. Due to the reduced diffusion length, Li can diffuse into the Li solid-solution phase after plating back on the bi-phase Li composite anode, resulting in uniform Li deposition morphology. Accordingly, the bi-phase Li composite anodes showed much better rate performance than the Li alloy or pristine Li. With these findings, it is expected that the new bi-phase Li composite anodes are a promising direction for long-life, high-power, and high-energy Li metal batteries, including Li-S batteries.

(Invited) Mapping the Nanoscale Photochemical Activity of Photonic Nanostructures

In order to build reliable structure-activity relationships for the design of more efficient photocatalysts, it is crucial to progress the fundamental understanding of nanosystems interacting with light. Their photochemical reactivity is dictated by the nanoscale behavior. In this contribution, I will show our recent efforts to delve in this exciting field by leveraging a scanning photoelectrochemical microscope. The nanoscale detection of the molecular products generated by the photocatalysts unlocks the visualization of unexpected reactivity behavior and aid to the design of new materials.