Pressure-induced two-color photoluminescence in MnF(2) at room temperature

A novel two-color photoluminescence (PL) is found in MnF(2) at room temperature under high pressure. Contrary to low-temperature PL, PL at room temperature is unusual in transition-metal concentrated materials like MnF(2), since the deexcitation process at room temperature is fully governed by energy transfer to nonradiative centers. We show that room-temperature PL in MnF(2) originates from two distinct Mn(2+) emissions in the high-pressure cotunnite phase. The electronic structure and the excited-state dynamics are investigated by time-resolved emission and excitation spectroscopy at high pressure.     

Particle multiplicities in lead-lead collisions at the CERN large hadron collider from nonlinear evolution with running coupling corrections

We present predictions for the pseudorapidity density of charged particles produced in central Pb-Pb collisions at the LHC. Particle production in such collisions is calculated in the framework of k(t) factorization. The nuclear unintegrated gluon distributions at LHC energies are determined from numerical solutions of the Balitsky-Kovchegov equation including recently calculated running coupling corrections. The initial conditions for the evolution are fixed by fitting Relativistic Heavy Ion Collider data at collision energies square root[sNN]=130 and 200 GeV per nucleon. We obtain dNch(Pb-Pb)/deta(square root[sNN]=5.5 TeV)/eta=0 approximately 1290-1480.     

Organozinc Pivalate Reagents: Segregation,Solubility, Stabilization,and Structural Insights

The pivalates RZnOPiv?Mg(OPiv)X?n LiCl (OPiv=pivalate; R=aryl; X=Cl, Br, I) stand out amongst salt‐supported organometallic reagents, because apart from their effectiveness in Negishi cross‐coupling reactions, they show more resistance to attack by moist air than conventional organometallic compounds. Herein a combination of synthesis, coupling applications, X‐ray crystallographic studies, NMR (including DOSY) studies, and ESI mass spectrometric studies provide details of these pivalate reagents in their own right. A p‐tolyl case system shows that in [D₈]THF solution these reagents exist as separated Me(p‐C₆H₄)ZnCl and Mg(OPiv)₂ species. Air exposure tests and X‐ray crystallographic studies indicate that Mg(OPiv)₂ enhances the air stability of aryl zinc species by sequestering H₂O contaminants. Coupling reactions of Me(p‐C₆H₄)ZnX (where X=different salts) with 4‐bromoanisole highlight the importance of the presence of Mg(OPiv)₂. Insight into the role of LiCl in these multicomponent mixtures is provided by the molecular structure of [(THF)₂Li₂(Cl)₂(OPiv)₂Zn].     

Electro-Mechanochemical Atom Transfer Radical Cyclizations using Piezoelectric BaTiO3

The formation and regeneration of active Cu^I species is a fundamental mechanistic step in copper-catalyzed atom transfer radical cyclizations (ATRC). Typically, the presence of the catalytically active Cu^I species in the reaction mixture is secured by using high Cu^I catalyst loadings or the addition of complementary reducing agents. In this study it is demonstrated how the piezoelectric properties of barium titanate (BaTiO₃) can be harnessed by mechanical ball milling to induce electrical polarization in the strained piezomaterial. This strategy enables the conversion of mechanical energy into electrical energy, leading to the reduction of a Cu^II precatalyst into the active Cu^I species in copper-catalyzed mechanochemical solvent-free ATRC reactions.     

Diels-Alder reaction mechanisms of substituted chiral anthracene: A theoretical study based on the reaction force and reaction electronic flux

Quantum chemical calculations were used to study the mechanism of Diels-Alder reactions involving chiral anthracenes as dienes and a series of dienophiles. The reaction force analysis was employed to obtain a detailed scrutiny of the reaction mechanisms, it has been found that thermodynamics and kinetics of the reactions are quite consistent: the lower the activation energy, the lower the reaction energy, thus following the Bell-Evans-Polanyi principle. It has been found that activation energies are mostly due to structural rearrangements that in most cases represented more than 70% of the activation energy. Electronic activity mostly due to changes in σ and π bonding were revealed by the reaction electronic flux (REF), this property helps identify whether changes on σ or π bonding drive the reaction. Additionally, new global indexes describing the behavior of the electronic activity were introduced and then used to classify the reactions in terms of the spontaneity of their electronic activity. Local natural bond order electronic population analysis was used to check consistency with global REF through the characterization of specific changes in the electronic density that might be responsible for the activity already detected by the REF. Results show that reactions involving acetoxy lactones are driven by spontaneous electronic activity coming from bond forming/strengthening processes; in the case of maleic anhydrides and maleimides it appears that both spontaneous and non-spontaneous electronic activity are quite active in driving the reactions.     

A Promising Thermodynamic Study of Hole Transport Materials to Develop Solar Cells: 1,3-Bis(N-carbazolyl)benzene and 1,4-Bis(diphenylamino)benzene

The thermochemical study of the 1,3-bis(N-carbazolyl)benzene (NCB) and 1,4-bis(diphenylamino)benzene (DAB) involved the combination of combustion calorimetric (CC) and thermogravimetric techniques. The molar heat capacities over the temperature range of (274.15 to 332.15) K, as well as the melting temperatures and enthalpies of fusion were measured for both compounds by differential scanning calorimetry (DSC). The standard molar enthalpies of formation in the crystalline phase were calculated from the values of combustion energy, which in turn were measured using a semi-micro combustion calorimeter. From the thermogravimetric analysis (TGA), the rate of mass loss as a function of the temperature was measured, which was then correlated with Langmuir’s equation to derive the vaporization enthalpies for both compounds. From the combination of experimental thermodynamic parameters, it was possible to derive the enthalpy of formation in the gaseous state of each of the title compounds. This parameter was also estimated from computational studies using the G3MP2B3 composite method. To prove the identity of the compounds, the ¹H and ¹³C spectra were determined by nuclear magnetic resonance (NMR), and the Raman spectra of the study compounds of this work were obtained.     

A Comparative Analysis of Machine Learning Techniques for Muon Count in UHECR Extensive Air-Showers

The main goal of this work is to adapt a Physics problem to the Machine Learning (ML) domain and to compare several techniques to solve it. The problem consists of how to perform muon count from the signal registered by particle detectors which record a mix of electromagnetic and muonic signals. Finding a good solution could be a building block on future experiments. After proposing an approach to solve the problem, the experiments show a performance comparison of some popular ML models using two different hadronic models for the test data. The results show that the problem is suitable to be solved using ML as well as how critical the feature selection stage is regarding precision and model complexity.     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.