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El objetivo de la investigación fue evaluar el rendimiento de tubérculos y las variables relacionadas de 17 cultivares de papa del grupo Phureja, de la región Cajamarca-Perú. El experimento se realizó en el valle de Cajamarca (2650 msnm) en diseño de bloques completamente randomizados, con 17 tratamientos (cultivares) y tres repeticiones, sembrados a 0,90 m entre surcos y 0,40 m entre plantas. Se evaluó altura de planta, número de tallos, número y peso total de tubérculos, número y peso de tubérculos comerciales, materia seca de tubérculos y follaje (%), índice de cosecha, gravedad específica y rendimiento de tubérculos por hectárea. Los datos fueron tratados mediante análisis de varianza y prueba de rango múltiple de Tukey (p ≤ 0,05). El rendimiento de tubérculos varió de 8,2 t∙ha-1 a 27,4 t∙ha-1 y el promedio fue de 15,5 t∙ha-1 . El índice de cosecha promedio fue de 65%. Los tubérculos comerciales representaron entre 49% y 97%. Los cultivares presentaron diferencias estadísticas altamente significativas en rendimiento por hectárea, altura de planta, número de tallos, número total de tubérculos, número de tubérculos comerciales y peso de tubérculos comerciales. Nueve cultivares fueron estadísticamente similares y superiores al resto, en rendimiento de tubérculos por hectárea. Un cultivar fue superior a todos los demás, en rendimiento de tubérculos comerciales.

Background & Aims: Malnutrition negatively affects the prognosis and quality of life of hospitalized patients. However, there are several gaps between evidence-based knowledge and current clinical practice. Our primary aim was to describe the prevalence of malnutrition risk in a cohort of in a cohort of older inpatients; secondly, we explored its predictors and its independent impact on 12-month survival., Methods: Prospective study focused on patients aged 65 years and older consecutively admitted for any reason to the acute geriatric and general medical units of an Italian university hospital. Comprehensive geriatric assessment data, including the short form of the Mini Nutritional Assessment (MNA-SF), were collected within 48 hours of admission. The prevalence of malnutrition and risk of malnutrition according to the MNA-SF represented the main outcome. Correlations among clinical variables, nutritional status, and one-year survival were analyzed using multivariable and Cox models., Results: Among 594 patients (median age: 84 years, 49.5 % female), mostly living at home with moderate functional autonomy, 82.3 % were identified as probably malnourished or at risk of malnutrition according to MNA-SF (39.9 % and 42.4 %, respectively). Malnutrition and the risk of malnutrition were positively associated with living alone at home (OR 2.803, 95%CI 1.567-5.177, p < 0.001), and negatively associated with autonomy in IADL (OR 0.765, 95%CI 0.688-0.846, p < 0.001) and the best performance at HST (OR 0.901, 95%CI 0.865-0.936; p < 0.001). After 12 months, 31.8 % of patients was dead and mortality was positively correlated with malnutrition according to MNA-SF (OR 2.493, 95%CI 1.345-4.751, p = 0.004), institutionalization (OR 2.815, 95%CI 1.423-5.693, p = 0.003) and severe cognitive impairment (OR 1.701, 95%CI 1.031-2.803, p = 0.036)., Conclusion: Malnutrition is common among older inpatients upon admission, primarily influenced by their functional and cognitive status, and it is linked to a worse prognosis. Early incorporation of thorough nutritional and functional assessments into clinical practice is crucial to improve prognosis prediction and enable timely, focused interventions targeting modifiable causal factors in a patient-centered approach., Competing Interests: Declaration of competing interest The Authors of this manuscript declare they have no conflict of interest to disclose., (Copyright © 2024 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.)

A structurally diverse family of 39 covalent triazine-based framework materials (CTFs) are synthesized by Suzuki-Miyaura polycondensation and tested as hydrogen evolution photocatalysts using a high-throughput workflow. The two best-performing CTFs are based on benzonitrile and dibenzo[ b , d ]thiophene sulfone linkers, respectively, with catalytic activities that are among the highest for this material class. The activities of the different CTFs are rationalized in terms of four variables: the predicted electron affinity, the predicted ionization potential, the optical gap, and the dispersibility of the CTFs particles in solution, as measured by optical transmittance. The electron affinity and dispersibility in solution are found to be the best predictors of photocatalytic hydrogen evolution activity., Competing Interests: The authors declare no competing financial interest., (Copyright © 2019 American Chemical Society.)

We propose a general high-throughput virtual screening approach for the optical and electronic properties of conjugated polymers. This approach makes use of the recently developed xTB family of low-computational-cost density functional tight-binding methods from Grimme and co-workers, calibrated here to (Time-Dependent) Density Functional Theory ((TD)DFT) data computed for a representative diverse set of (co)polymers. Parameters drawn from the resulting calibration using a linear model can then be applied to the xTB derived results for new polymers, thus generating near DFT-quality data with orders of magnitude reduction in computational cost. As a result, after an initial computational investment for calibration, this approach can be used to quickly and accurately screen on the order of thousands of polymers for target applications. We also demonstrate that the (opto)electronic properties of the conjugated polymers show only a very minor variation when considering different conformers and that the results of high-throughput screening are therefore expected to be relatively insensitive with respect to the conformer search methodology applied.

A completely unsymmetrical porous organic cage was synthesised from a C 2v symmetrical building block that was identified by a computational screen. The cage was formed through a 12-fold imine condensation of a tritopic C 2v symmetric trialdehyde with a ditopic C 2 symmetric diamine in a [4 + 6] reaction. The cage was rigid and microporous, as predicted by the simulations, with an apparent Brunauer-Emmett-Teller surface area of 578 m 2 g -1 . The reduced symmetry of the tritopic building block relative to its topicity meant there were 36 possible structural isomers of the cage. Experimental characterisation suggests a single isomer with 12 unique imine environments, but techniques such as NMR could not conclusively identify the isomer. Computational structural and electronic analysis of the possible isomers was used to identify the most likely candidates, and hence to construct a 3-dimensional model of the amorphous solid. The rational design of unsymmetrical cages using building blocks with reduced symmetry offers new possibilities in controlling the degree of crystallinity, porosity, and solubility, of self-assembled materials.

The chemical and structural space of possible molecular materials is enormous, as they can, in principle, be built from any combination of organic building blocks. Here we have developed an evolutionary algorithm (EA) that can assist in the efficient exploration of chemical space for molecular materials, helping to guide synthesis to materials with promising applications. We demonstrate the utility of our EA to porous organic cages, predicting both promising targets and identifying the chemical features that emerge as important for a cage to be shape persistent or to adopt a particular cavity size. We identify that shape persistent cages require a low percentage of rotatable bonds in their precursors (<20%) and that the higher topicity building block in particular should use double bonds for rigidity. We can use the EA to explore what size ranges for precursors are required for achieving a given pore size in a cage and show that 16 Å pores, which are absent in the literature, should be synthetically achievable. Our EA implementation is adaptable and easily extendable, not only to target specific properties of porous organic cages, such as optimal encapsulants or molecular separation materials, but also to any easily calculable property of other molecular materials.

A tool for the automated assembly, molecular optimization and property calculation of supramolecular materials is presented. stk is a modular, extensible and open-source Python library that provides a simple Python API and integration with third party computational codes. stk currently supports the construction of linear polymers, small linear oligomers, organic cages in multiple topologies and covalent organic frameworks (COFs) in multiple framework topologies, but is designed to be easy to extend to new, unrelated, supramolecules or new topologies. Extension to metal-organic frameworks (MOFs), metallocycles or supramolecules, such as catenanes, would be straightforward. Through integration with third party codes, stk offers the user the opportunity to explore the potential energy landscape of the assembled supramolecule and then calculate the supramolecule's structural features and properties. stk provides support for high-throughput screening of large batches of supramolecules at a time. The source code of the program can be found at https://github.com/supramolecular-toolkit/stk. © 2018 Wiley Periodicals, Inc., (© 2018 Wiley Periodicals, Inc.)

We study the vertical and adiabatic ionization potentials and electron affinities of bare and hydroxylated TiO 2 nanoclusters, as well as their fundamental gap and exciton binding energy values, to understand how the clusters' electronic properties change as a function of size and hydroxylation. In addition, we have employed a range of many-body methods; including G 0 W 0 , qsGW, EA/IP-EOM-CCSD, and DFT (B3LYP, PBE), to compare the performance and predictions of the different classes of methods. We demonstrate that, for bare clusters, all many-body methods predict the same trend with cluster size. The highest occupied and lowest unoccupied DFT orbitals follow the same trends as the electron affinity and ionization potentials predicted by the many-body methods, but are generally far too shallow and deep respectively in absolute terms. In contrast, the ΔDFT method is found to yield values in the correct energy window. However, its predictions depend upon the functional used and do not necessarily follow trends based on the many-body methods. Adiabatic potentials are predicted to be similar to their vertical counterparts and holes found to be trapped more strongly than excess electrons. The effect of hydroxylation on the clusters is to open up both the optical and fundamental gap. Finally, a simple microscopic explanation for the observed trends with cluster size and upon hydroxylation is proposed in terms of the onsite electrostatic potential.

We define a nomenclature for the classification of porous organic cage molecules, enumerating the 20 most probable topologies, 12 of which have been synthetically realised to date. We then discuss the computational challenges encountered when trying to predict the most likely topological outcomes from dynamic covalent chemistry (DCC) reactions of organic building blocks. This allows us to explore the extent to which comparing the internal energies of possible reaction outcomes is successful in predicting the topology for a series of 10 different building block combinations.

We present the first unconstrained nonadiabatic molecular dynamics (NAMD) simulations of photocatalytic water oxidation by small hydrated TiO 2 nanoparticles using Tully surface hopping and time-dependent density functional theory. The results indicate that ultrafast electron-proton transfer from physisorbed water to the photohole initiates the photo-oxidation on the S 1 potential energy surface. The new mechanism readily explains the observation of mobile hydroxyl radicals in recent experiments. Two key driving forces for the photo-oxidation reaction are identified: localization of the electron-hole pair and stabilization of the photohole by hydrogen bonding interaction. Our findings illustrate the scope of recent advances in NAMD methods and emphasize the importance of explicit simulation of electronic excitations.

We investigate using a computational approach the physical and chemical processes underlying the application of organic (macro)molecules as fluorescence quenching sensors for explosives sensing. We concentrate on the use of amine molecular cages to sense nitroaromatic analytes, such as picric acid and 2,4-dinitrophenol, through fluorescence quenching. Our observations for this model system hold for many related systems. We consider the different possible mechanisms of fluorescence quenching: Förster resonance energy transfer, Dexter energy transfer and photoinduced electron transfer, and show that in the case of our model system, the fluorescence quenching is driven by the latter and involves stable supramolecular sensor-analyte host-guest complexes. Furthermore, we demonstrate that the experimentally observed selectivity of amine molecular cages for different explosives can be explained by the stability of these host-guest complexes and discuss how this is related to the geometry of the binding site in the sensor. Finally, we discuss what our observations mean for explosive sensing by fluorescence quenching in general and how this can help in future rational design of new supramolecular detection systems.

In this mini-review, we discuss what insight computational modelling can provide into the working of photocatalysts for solar fuel synthesis and how calculations can be used to screen for new promising materials for photocatalytic water splitting and carbon dioxide reduction. We will extensively discuss the different relevant (material) properties and the computational approaches (DFT, TD-DFT, GW/BSE) available to model them. We illustrate this with examples from the literature, focussing on polymeric and nanoparticle photocatalysts. We finish with a perspective on the outstanding conceptual and computational challenges.

We have investigated the description of excited state relaxation in naked and hydrated TiO2 nanoparticles using Time-Dependent Density Functional Theory (TD-DFT) with three common hybrid exchange-correlation (XC) potentials: B3LYP, CAM-B3LYP and BHLYP. Use of TD-CAM-B3LYP and TD-BHLYP yields qualitatively similar results for all structures, which are also consistent with predictions of coupled-cluster theory for small particles. TD-B3LYP, in contrast, is found to make rather different predictions; including apparent conical intersections for certain particles that are not observed with TD-CAM-B3LYP nor with TD-BHLYP. In line with our previous observations for vertical excitations, the issue with TD-B3LYP appears to be the inherent tendency of TD-B3LYP, and other XC potentials with no or a low percentage of Hartree-Fock like exchange, to spuriously stabilize the energy of charge-transfer (CT) states. Even in the case of hydrated particles, for which vertical excitations are generally well described with all XC potentials, the use of TD-B3LYP appears to result in CT problems during excited state relaxation for certain particles. We hypothesize that the spurious stabilization of CT states by TD-B3LYP even may drive the excited state optimizations to different excited state geometries from those obtained using TD-CAM-B3LYP or TD-BHLYP. Finally, focusing on the TD-CAM-B3LYP and TD-BHLYP results, excited state relaxation in small naked and hydrated TiO2 nanoparticles is predicted to be associated with a large Stokes' shift.

We have investigated the suitability of Time-Dependent Density Functional Theory (TD-DFT) to describe vertical low-energy excitations in naked and hydrated titanium dioxide nanoparticles. Specifically, we compared TD-DFT results obtained using different exchange-correlation (XC) potentials with those calculated using Equation-of-Motion Coupled Cluster (EOM-CC) quantum chemistry methods. We demonstrate that TD-DFT calculations with commonly used XC potentials (e.g., B3LYP) and EOM-CC methods give qualitatively similar results for most TiO 2 nanoparticles investigated. More importantly, however, we also show that, for a significant subset of structures, TD-DFT gives qualitatively different results depending upon the XC potential used and that only TD-CAM-B3LYP and TD-BHLYP calculations yield results that are consistent with those obtained using EOM-CC theory. Moreover, we demonstrate that the discrepancies for such structures originate from a particular combination of defects that give rise to charge-transfer excitations, which are poorly described by XC potentials that do not contain sufficient Hartree-Fock like exchange. Finally, we consider that such defects are readily healed in the presence of ubiquitously present water and that, as a result, the description of vertical low-energy excitations for hydrated TiO 2 nanoparticles is nonproblematic.

The excitation energies of the four lowest-lying singlet excited states of the TiO2, Ti2O4, and Ti3O6 clusters are calculated by a variety of different Equation-of-Motion Coupled Cluster (EOM-CC) approaches in order to obtain benchmark values for the optical excitations of titanium dioxide clusters. More specifically we investigate what the effect is of the inclusion of triple excitations "triples" in the (EOM-)CC scheme on the calculated excited states of the clusters. While for the monomer and dimer the inclusion of triples is found to only cause a rigid shift in the excitation energies, in the case of the trimer the crossing of the excited states is observed. Coupled cluster approaches where triples are treated perturbatively were found to offer no advantage over EOM-CCSD, whereas the active-space methods (EOM-CCSDt(II/I)) were demonstrated to yield results very close to full EOM-CCSDT, but at a much reduced computational cost.

The reactivity of bioglasses, which is related to the dissolution of cations and orthosilicate groups in the physiological fluid, strongly depends on the key structural features present at the glass surfaces. On the basis of the composition and the synthetic routes employed to make the glass, surfaces with very different characteristics and thus presenting different mechanisms of dissolution can be observed. In this paper, the surface structures of two very different bioglass compositions, namely 45S5 (46.1 SiO2, 24.4 Na2O, 26.9 CaO, and 2.6 P2O5 mol %) and 77S (80.0 SiO2, 16.0 CaO, and 4.0 P2O5 mol %), have been investigated by means of periodic DFT calculations based on a PBE functional and localized Gaussian basis set as encoded in the CRYSTAL code. Our calculations show that the two glass surfaces differ by the relative amount of key structural sites such as NBOs, exposed ions, orthosilicate units, and small rings. We have demonstrated how the number of these sites affects the surface stability and reactivity (bioactivity).