Find research datasets worth reusing

opencc-by-4.0Jul 2024View details →

Socio - Economic Survey on Green Transition in Albania - Households

Socio-Economic Survey on Green Transition in Albania - Households The file contains the dataset (cleaned), the questionnaire in Albanian, the coding used for data processing in SPSS, and the detailed results for each question in the questionnaire (organised in sections).

opencc-by-4.0Jul 2024View details →

Socio-Economic Survey on Green Transition in Albania - Businesses

Socio-Economic Survey on Green Transition in Albania - Businesses The file contains the dataset (cleaned), the questionnaire in Albanian, the coding used for data processing in SPSS, and the detailed results for each question in the questionnaire (organised in sections).

opencc-by-4.0Sep 2018View details →

Direct observation of electron density reconstruction at the metal-insulator transition in NaOsO3

Open access data set for manuscript "Direct observation of electron density reconstruction at the metal- insulator transition in NaOsO3" published in Physical Review B, 98, 115116 (2018)

opencc-by-4.0Nov 2022View details →

PALEODEM/ What burned the forest? Wildfires, climate change and human activity during the Mesolithic – Neolithic transition in SE Iberian Peninsula

This repository contains new XRD data from the Villena paleolake, archaeological radiocarbon evidence from the Villena area and the R code used to produce Summed Probability distribution analyses.   They correspond to the following reference:   Sánchez-García, C., Revelles, J., Burjachs, F., Euba, I., Expósito, I., Ibáñez, J., Schulte, L., Fernández-López de Pablo, J. What burned the forest? Wildfires, climate change and human activity during the Mesolithic – Neolithic transition in SE Iberian Peninsula (submitted to Catena).  We specify the content of file further down: <ul> <li>Vinalopo.csv: the list of radiocarbon dates from Villena spanning ca.9500-5500 cal BP from the following sites: Arenal de la Virgen, Cueva del Lagrimal and Casa Corona. </li> <li>ngrip.csv: NGRIP GICC05 paleotemperature record based on oxygen isotope series from Rasmussen SO et al.2006 A new Greenland ice core chronology for the last glacial termination. J. Geophys. Res. Atmos.111. (doi:10.1029/2005JD006079) and Andersen KK et al.2006 The Greenland Ice Core Chronology 2005, 15–42ka. Part 1: constructing the time scale. Quat. Sci. Rev.25, 3246–3257.</li> <li>Char.csv:  Sedimentary charcoal data set from the Villena Paleolake (VL3 core) published by Jones, S.E., Burjachs, F., Fernández-López de Pablo (2018) DOI/10.5281/zenodo.1244003, according to the new Bacon chronological model of the Villena paleolake (Fernández-López de Pablo et al., 2022 . Impacts of Early Holocene environmental dynamics on open-air occupation patterns in the Western Mediterranean: insights from El Arenal de la Virgen (Alicante, Spain). <a href="https://doi.org/10.31235/osf.io/5yqsr">https://doi.org/10.31235/osf.io/5yqsr</a>)</li> <li>SPD_analysis.R: R script with the code to reproduce the SPD analysis presented in the manuscript. </li> <li>SupplMat1xlsl: an excel file This file is composed by 8 spreadsheets:</li> </ul> <ol> <li>‘Selected variables 12.6-5.5’: all the data included in the time frame 12600-5500 cal BP, interpolated to 50 yr time windows. These data have been used for the Spearmans’rs correlation analysis (see spreadsheet ‘Spearmans’rs 12.6-5.5’ to track the results), Detrended Correspondence Analysis (see spreadsheet ‘Figure 5_DCA 12.6-5.5’ to track the results) and have been plotted in Figure 3 and 7. </li> <li>'Selected variables 9.1-5.5’: data included in the analysis focused on the time period 9.1-5.5 cal BP, interpolated to 50 yr time windows. These data have been used for the Spearmans’rs correlation analysis (see spreadsheet ‘Spearmans’rs 9.1-5.5’ to track the results), Detrended Correspondence Analysis (see spreadsheet ‘Figure 6_DCA 9.1-5.5’ to track the results) and have been plotted in Figure 8.</li> <li>‘Spearmans’rs 12.6-5.5’: Spearmans’rs correlation analysis applied to the 12600-5500 cal BP dataset (data from ‘Selected variables 12.6-5.5’).</li> <li>‘Spearmans’rs 9.1-5.5 cal BP’ Spearmans’rs correlation analysis applied to the 9100-5500 cal BP dataset, including here high-resolution XRD data (data from ‘Selected variables 9.1-5.5’).</li> <li>‘Figure 2 charcoal results’: original sedimentary charcoal results provided in this work. Data plotted in Figure 2. </li> <li>‘Figure 4 XRD results’: original XRD results provided in this work. Data plotted in Figure 4.</li> <li>‘Figure 5 DCA 12.6-5.5’: results of Detrended Correspondence analysis focused on the time period from 12600 to 5500 cal BP. Data plotted in Figure 5.</li> <li>‘Figure 6 DCA 9.1-5.5’ results of Detrended Correspondence analysis focused on the time period from 9100 to 5500 cal BP, including here high-resolution XRD data. Data plotted in Figure 6.</li> </ol>

opencc-by-4.0Feb 2023View details →

LTER-Italy marine and transitional sites map

Map of Italy where the Italian Long-Term Ecological Research (LTER-Italy) sites are evidenced. The colours of the dots correspond to the main ecosystem typologies: Dark blue = marine, green = transitional water. The main features of the sites can be found on DEIMS-SDR, the LTER-Europe repository for research sites and datasets (<a href="https://deims.org">https://deims.org</a>).

opencc-by-4.0Mar 2023View details →

Experimental determination of the gadolinium L subshells fluorescence yields and Coster-Kronig transition probabilities

Data associated with the two main tables of the publication "Experimental determination of the gadolinium L subshells fluorescence yields and Coster-Kronig transition probabilities". There are two .txt files containing tabulator-separated values: tabl01_ck.txt: Data associated with Table 1 of the publication. This file contains the L subshell Coster-Kronig (CK) factors and their respective uncertainties. tabl02_fy.txt: Data associated with Table 2 of the publication. This file contains the experimentally determined Gd L subshell fluorescence yields in comparison to available literature sources and their respective uncertainties. For more details see the original Open Access publication: Kayser, Y., Hönicke, P., Wansleben, M., Wählisch, A., Beckhoff, B., X-Ray Spectrom 2022, 1. <a href="https://doi.org/10.1002/xrs.3313">https://doi.org/10.1002/xrs.3313</a>

opencc-by-4.0Jul 2023View details →

An annotated compilation of chronometric dates for the Middle-Upper Palaeolithic Transition (45-30 ka BP) in northern Iberia (Spain). Source Data.

This repository contains the files of the chronometric dates framed between 45-30 ka BP in Northern Iberia.

opencc-by-4.0Oct 2023View details →

High-Throughput Density Functional Theory Screening of Double Transition Metal MXene Precursors

This dataset contains density functional theory results on a set of double-transition metal MXene precursors

opencc-by-4.0Nov 2022View details →

Characterization of investments profiles on the energy transition for european citizens

<ul> <li>Name: Characterization of investments profiles on the energy transition for european citizens</li> <li>Summary: The dataset contains: (1) surveyee consent form for the study, (2) different scenarios about the energy transition, (3) determinant factors about those scenarios, (4) socioeconomic description of the surveyee, (5) investment decisions, (6) and household characterization/description. </li> <li>License: cc-BY-SA</li> <li>Acknowledge: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943.</li> <li>Disclaimer: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European commission (Ec). EASME or the Ec are not responsible for any use that may be made of the information contained therein.</li> <li>Collection Date: 22/07/2022</li> <li>Publication Date: 15/10/2023</li> <li>DOI: 10.5281/zenodo.4455198</li> <li>Other repositories:</li> <li>Author: University of Deusto</li> <li>Objective of collection: This data was originally collected to analyze quantitatively the decisions of everyday people in relation to their energy consumption and their reactions to specific political interventions.</li> <li>Description: The dataset contains a CSV file file containing data collected from a survey about energy consumption investments. The fields that can be found for each entry are (1) Different scenarios about the energy transition and reactions to those scenarios, (money spent on energy investments, decisions about scenarios, actions taken under a blackout, etc.) (2) Determinant factors about the chosen scenarios in the previous question, which include different choices that could affect your decision about a scenario (3) socioeconomic information about the user (age, country of residence, studies), (4) estimation of the prices of various technologies related to the energy transition and (5) descriptive statistics about the household living situation (gender of user, people living in household, yearly rent, average savings per month, type of house, size of house) and also includes questions about climate change expertise. Next you can found a description of each field in the dataset <ul> <li>Section 1 - Scenarios for energy transition. <ul> <li>ID90. Rank in order of priority, from top to bottom, in which scenario you will be willing to live or to contribute/invest to make it possible. </li> <li>ID36, ID38, ID43, ID44, ID72. Percentage of money people are willing to spend/save out of their income per scenario</li> <li>ID191, ID192.. Amount of money people would spend based on an assumed case.</li> <li>ID191, ID192. Priority service provision in case of Intermittent energy service. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority for you and 10 stars means it is absolutely necessary for you.</li> <li>[ID325, ID326, ID327, ID328, ID329, ID330, ID331, ID332, ID333, ID334, ID335, ID336, ID337, ID338, ID339, ID340, ID341, ID133, ID242]. Priority service provision in case of Intermittent energy service. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary.</li> <li>[ID251, ID256, ID257, ID292, ID293, ID294, ID295, ID296, ID297, ID298, ID299, ID301, ID302, ID303, ID304, ID305, ID306, ID250, ID251]. Priority service provision in case of full black-outs. Rating energy services from 0 to 10 stars, where 0 stars means it is extremely low priority and 10 stars means it is absolutely necessary.</li> <li>[ID141, ID5, ID147]. Used for statements that best represent survey responder</li> </ul> </li> <li>Section 2 - Determinants (factors). Questions used to rate (from 0 to 100) factors that may influence the decision-making process contributing to make an ideal scenario possible. <ul> <li>ID100 Risk profile</li> <li>ID101 Added value</li> <li>ID102 Self-Satisfaction</li> <li>ID103 Technical Fit</li> <li>ID104 Own competence</li> <li>ID105 Knowledge</li> <li>ID106 Cost-Efficiency</li> <li>ID107 Safety</li> <li>ID108 Trust</li> <li>ID109 Autarky</li> <li>ID110 Legal</li> <li>ID111 Climate Protection</li> <li>ID112 Wellbeing</li> <li>ID113 Coziness</li> <li>ID114 Rights and Duties</li> <li>ID115 Peer-Pressure</li> <li>ID116 Socialising</li> <li>ID117 Support</li> <li>ID118 Agreement</li> <li>ID119 Brag</li> <li>ID120 Fun</li> <li>ID121 Novelty</li> <li>ID122 Trends</li> <li>ID123 Authority</li> <li>ID124 Own Significance</li> <li>ID125 Poseur</li> <li>ID2 Frugality</li> <li>ID3 Environmental concerns</li> <li>ID31 Adherence</li> <li>ID52 Commitment</li> <li>ID97 Profits</li> <li>ID99 Credit Score</li> </ul> </li> <li>Section 3 - “Socio-economic” description. Questions about the socio-economic information of the survey respondents for data stratification. The indentation represents the dependency of questions and whether this data was asked <ul> <li>ID164 Understanding of questions</li> <li>ID300 Country of residence</li> <li>ID137 Age</li> <li>ID178 Highest level of education</li> <li>ID136 Willingness to provide data on the investment decision (respond apply for -Investment decision section)</li> </ul> </li> <li>Section 4 - Investment decision. Questions about specific prices of potential purchases-decisions related to four scenarios (respondent's lifestyle) <ul> <li>Appliances <ul> <li>ID42 Affordable cost of a Regular refrigerator</li> <li>ID45 Energy efficient refrigerator costs</li> <li>ID50 Willingness to purchase an energy efficient refrigerator <ul> <li>ID65 Why no</li> <li>ID66 affordable cost of an energy efficient option</li> <li>ID67 Years to amortize an efficient option</li> </ul> </li> </ul> </li> <li>Insulation <ul> <li>ID47 Affordable cost of updating to a state of the art insulation on the facade</li> <li>ID56 Willingness for paying/invest <ul> <li>ID74 Why no?</li> <li>ID20 affordable cost of an energy efficient option</li> <li>ID34 Years to amortize an energy efficient option</li> </ul> </li> </ul> </li> <li>Energy Generation <ul> <li>ID68 Affordable cost of a solar photovoltaic system</li> <li>ID76 Willingness for paying/invest <ul> <li>ID84 Why no?</li> <li>ID132 Affordable cost of a photovoltaic system</li> <li>ID138 Years that amortize a  photovoltaic system</li> </ul> </li> </ul> </li> <li>Energy Storage <ul> <li>ID142 Affordable cost of an energy storage system</li> <li>ID146 Willingness for paying/invest <ul> <li>ID181 Why no? </li> <li>ID182 Affordable cost of an energy storage system </li> <li>ID183 Years that amortize an energy storage systems</li> </ul> </li> </ul> </li> <li>Heating <ul> <li>ID140 Affordable cost of a gas boiler</li> <li>ID209 Affordable cost of an energy efficient heating system</li> <li>ID217 Willingness for paying/invest <ul> <li>ID238 Why no?</li> <li>ID239 Affordable cost of a energy efficient option</li> <li>ID241 Years that amortize a heat pumps</li> </ul> </li> </ul> </li> <li>Mobility <ul> <li>ID41 Average kilometers traveled a typical day</li> <li>ID51 Usual travel option</li> <li>ID264 Affordable cost of a diesel or gasoline mid-range brand new car</li> <li>ID265 Affordable cost of a mid-range brand new electric car</li> <li>ID281 Willingness to buy an electric car <ul> <li>ID289 Why no?</li> <li>ID290 Affordable price of an electric car</li> <li>ID291 Years that amortize an electric car</li> </ul> </li> </ul> </li> </ul> </li> <li>Section 5 - Household characterization <ul> <li>ID127 Selecting an asked value</li> <li>ID189 Type of living area</li> <li>ID202 Gender identity</li> <li>ID1 Those living in the house</li> <li>ID32 Number of inhabitants</li> <li>ID220 Average neat yearly income</li> <li>ID229 Average monthly saving</li> <li>ID240 Type of housing</li> <li>ID249 Owner / co-owner</li> <li>ID255 Usable area of the property (m²)</li> <li>ID263 Insulation level</li> <li>ID270 Climate zone</li> <li>ID86 Level of self-awareness about climate change. On scale of 0-10, where 0 is “climate change does not exist” and 10 is “I am a climate change expert/activist”</li> <li>ID87 Level of awareness of climate change among your peers or relatives, On a scale of 0-10, where 0 is “climate change does not exist” and 10 is “They are climate change experts/activists”</li> <li>ID88 Level of self-awareness about  energy transition. On a scale of 0-10, where 0 is “It is the first time I hear about it” and 10 is “I am an expert or activist”</li> <li>ID89 Level of awareness of energy transition among your peers or relatives On a scale of 0-10, where 0 is “It is the first time they hear about it” and 10 is “They are experts or activists”</li> <li>ID190 feedback about survey</li> </ul> </li> </ul> </li> <li>5 star: ⭐⭐⭐</li> <li>Preprocessing steps: anonymization, data fusion, imputation of gaps.</li> <li>Reuse: NA</li> <li>Update policy: No more updates are planned</li> <li>Ethics and legal aspects: Spanish electric cooperative data contains the CUPS (Meter Point Administration Number), which is personal data. A pre-processing step has been carried out to substitute the CUPS by a random value hash.</li> <li>Technical aspects: </li> <li>Other:</li> </ul>

openCC (other)Aug 2022View details →

Long-term above- and belowground net primary production (NPP) measurements from a grassland-shrubland transition zone in the Sevilleta National Wildlife Refuge, New Mexico, USA

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to large-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground NPP (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground NPP (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. This data package accompanies an associated manuscript in which we used sixteen years (2005-2020) of annual NPP measurements, derived from three ongoing long-term research sites, to investigate spatiotemporal responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert.

openCC0Apr 2020View details →

Public Transit Infrastructure and Heat Perceptions in Hot and Dry Climates (June-July, 2018; Phoenix, Arizona, USA)

Increasing the use of public transit is an important sustainability goal targeted by many cities worldwide. However, cities in hot and warming climates risk to compromise residents’ health and thermal comfort by incentivizing public transit use and, thus, subjecting them to prolonged heat exposure. This dataset contains data collected during a study on the relationships between public transit infrastructures, microclimate and heat perceptions in the hot and dry city of Phoenix, Arizona. A field campaign at six Phoenix bus stops was held between June 6 and July 27, 2018. Filed campaign consisted of surveying bus riders at bus stops and measuring microclimate variables at sun exposed and shaded locations at bus stops. Standard, advertising and art bus stop types along an arterial Phoenix road in South Mountain Village neighborhood were sampled. Standard and advertising bus stop shelters were metal with no landscaping, art stops had a larger polycarbonate canopy, integrated artwork, trees and landscaping features. Eighty-three participants filled out the survey, 241 microclimate measurements and 1003 surface temperatures at bus stops were taken. Data were collected at three intervals: 7:00-9:00am, 12:00-2:00pm, and 3:00-5:00pm. Differences between sun and shade, as well as heat perceptions were analyzed using statistical methods. The research team has found that certain infrastructure types are more effective in reducing particular microclimate variables, for instance, trees were most effective in reducing air temperature by as much as 1.3°C on average, and shade from vertical advertising sign was most effective in reducing mean radiant temperature by an average of 11°C. Many surface temperatures of sun exposed materials sampled at bus stops exceeded skin burn thresholds. Study participants perceived stops with improved infrastructure and landscaping as slightly cooler. Data collected in this study gives a glimpse of current microclimate conditions at Phoenix bus stops

openCC (other)Jan 2025View details →

Physical Hydrologic Data for the National Audubon Society's 16 Research Sites in coastal mangrove transition zone of southern Florida, March 1986 - ongoing

Temperature, salinity and depth were continuously collected using Hydrolab/Hach sensors within the coastal mangrove transition zone at 16 sites from southern Biscayne Bay to Cape Sable. Data were collected at 12 sites within the coastal mangrove zone of Everglades National Park, incorporating the Cape Sable, Taylor River and Panhandle region. Data were collected at 4 sites within the coastal mangrove zone of southern Biscayne Bay, incorporating the Manatee Bay, Barnes Sound, and Card Sound regions. Rainfall, pH, and dissolved oxygen were collected at a number of these sites with varying periods of record.

openCustomJan 2020View details →

Quarterly plant monitoring survey -- shoot height and flowering status and calculated biomass of plants in three GCE LTER permanent monitoring plots (7,8,9) and three Altamaha River plant transition sites (SCSA,ZSC1,ZSC2) following hurricane Irma from October 2017 through October 2018.

The biomass of plants surveyed in permanent plots at 3 GCE LTER sampling sites (7,8,9) and 3 Altamaha River plant transition sites (SCSA, ZSC1, ZSC2) following hurricane Irma from October 2017 through October 2018. October data are duplicates of data from the annual fall monitoring data sets but are included here for completeness. The plots were visually surveyed and the species, shoot height, and flowering status was recorded individually for each shoot over 10 cm in height present in each plot. Observations from plots exhibiting signs of disturbance were noted in a separate data set (PLT-IRMA-2002a). Biomass twas estimated based on allometric relationships between biomass and shoot height and flowering status derived for each site, zone, and species in October 2002 and October 2008. Biomass was calculated for dominant species, including Spartina alterniflora, S. cynosuroides, Juncus roemerianus, and Zizaniopsis miliacea, as well as rarer species including Scirpus spp, Panicum spp. And Typha angustifolia. This data set is based on GCE plant monitoring survey data set PLT-GCEM-1711a, and allometric relationships were based on GCE data sets PLT-GCEM-0211b and PLT-GCEM-0812a. NOTE: These relationships were measured in the fall and may not be valid at other seasons.

openCustomJan 2020View details →

Quarterly disturbance observations to three GCE LTER permanent monitoring plots (7,8,9) and three Altamaha River plant transition sites (SCSA,ZSC1,ZSC2) following hurricane Irma from October 2017 through October 2018.

To access the effect of hurricane Irma on the GCE domain, yearly monitoring of species and size distribution of plants at three GCE LTER sampling sites (7, 8, 9) and three Altamaha plant transition sites (SCSA, ZSC1, ZSC2) was expanded to quarterly sampling between October 2017 and October 2018. We established permanent vegetation monitoring plots in creekbank and midmarsh at GCE sites 1-10 in 2000. A dedicated Juncus zone was later added at sites 10 and 9. We established creekbank permanent vegetation monitoring plots in three plant transition zones along the Altamaha River in 2012. When we recorded plant sizes, we also noted any disturbance to the plots. Plots were scored as normal (no visible disturbance), disturbed by wrack (wrack present in plots and stems dead or broken), disturbed by snails (>100 Littoraria per square meter and plant biomass low), disturbed by pigs (animal trail through the plot, this mostly happened at site 8 mid-marsh), initial slump (plot at the creekbank sliding into the creek based on movement of pvc poles or formation of a crevasse), and terminal slump (plot had slid far enough down that vegetation had drowned). Plots that experienced terminal slump or could not be found for any reason were scored as lost. Lost plots were replaced with a new plot in the same general area with the plot code incremented by 10. For example if plot 3 was lost, it was replaced by 13, and then in turn by 23. October data are duplicates of data from the annual fall monitoring data sets but are included here for completeness.

opencc-by-4.0Aug 2020View details →

Vertex-transitive Graphs On Fewer Than 48 Vertices

Vertex-transitive Graphs On Fewer Than 48 Vertices This dataset contains all the vertex-transitive graphs on 10-47 vertices. It consists of a collection of tar files, with names like alltrans26.tar meaning that this tar file contains all the vertex-transitive graphs on 26 vertices. Once the tar file is unpacked (using "tar xf alltrans26.tar") this will create a number of smaller gzipped files with names such as alltrans26_k=03.gz meaning that this file contains all the transitive graphs on 26 vertices with degree (valency) 3.  Once the gzip file is unpacked using "gunzip alltrans26_k=03.gz" the resulting file contains all the graphs, one per line, in graph6 format (this format was invented by Brendan McKay and is recognised by SageMath).  The first five lines of the file alltrans26_k=03 are as follows: <pre>Ys???C????_CA?@?`?_GO?c?@_?Q??K??O@CG?aA?GAG@?OCCG?GGC?? Ys??WO@?O??O?J?E?A_H??A?C??O?????_?DC?AQ?AAA??oG?C_O?I?? Ys??WWG@?@?A?W?c??g?S?@??G???G??O??S??I?_?Ac??SS??OW??_? Ys?GGSG@?@?A?W?c??g?S?@??G???G??O??S??I?_?Ac??SS??OW??_? Ys?GOO?????c?Q?c?B?@_?I?A??G??A?@?CCC?OP?CCC?C_O?AOC?C_? </pre> These can be directly used as input to SageMath with commands such as g = Graph("Ys???C????_CA?@?`?_GO?c?@_?Q??K??O@CG?aA?GAG@?OCCG?GGC??") No attempt has been made to reduce data storage by removing redundancy. So the tar file for vertex-transitive graphs on n vertices contains files for each feasible valency from 0 to n-1, despite the redundancy inherent in storing both a graph and its complement, and in storing both disconnected and connected graphs.

opencc-by-nc-sa-4.0Jun 2017View details →

A Non-galvanic D-band MMIC-to-Waveguide Transition Using eWLB Packaging Technology-dataset

This paper presents a novel D-band interconnect implemented in a low-cost embedded Wafer Ball Grid Array (eWLB) commercial process. The transition is realized through a patch slot antenna directly radiating to a standard waveguide opening. The interconnect achieves low insertion loss and good bandwidth. The measured minimum Insertion Loss (IL) is 2 dB and the average is 3 dB across a bandwidth of 22% covering the frequency range 110-138 GHz. In addition, the structure is easy to integrate as it does not require any special assembly nor any galvanic contacts. Adopting the low-cost eWLB process and standard waveguides makes the transition an attractive solution for interconnects beyond 100 GHz.

opencc-by-4.0Nov 2023View details →

Mutual Induced Fit Transition Structure Stabilization of Corannulene's Bowl-to-Bowl Inversion in a Perylene Bisimide Cyclophane

Additional data to report <a href="https://doi.org/10.1039/D3SC05341E">https://doi.org/10.1039/D3SC05341E</a>: Corannulene is known to undergo a fast bowl-to-bowl inversion at r.t. via a planar transition structure (TS). Herein we present the catalysis of this process within a perylene bisimide (PBI) cyclophane composed of chirally twisted, non-planar chromophores, linked by para-xylylene spacers. Variable temperature NMR studies reveal that the bowl-to-bowl inversion is significantly accelerated within the cyclophane template despite the structural non-complementarity between the binding site of the host and the TS of the guest. The observed acceleration corresponds to a decrease in the bowl-to-bowl inversion barrier of 11.6 kJ mol−1 compared to the uncatalyzed process. Comparative binding studies for corannulene (20 π-electrons) and other planar polycyclic aromatic hydrocarbons (PAHs) with 14 to 24 π-electrons were applied to rationalize this barrier reduction. They revealed high binding constants that reach, in tetrachloromethane as a solvent, the picomolar range for the largest guest coronene. Computational models corroborate these experimental results and suggest that both TS stabilization and ground state destabilization contribute to the observed catalytic effect. Hereby, we find a “mutual induced fit” between host and guest in the TS complex, such that mutual geometric adaptation of the energetically favored planar TS and curved π-systems of the host results in an unprecedented non-planar TS of corannulene. Concomitant partial planarization of the PBI units optimizes noncovalent TS stabilization by π–π stacking interactions. This observation of a “mutual induced fit” in the TS of a host–guest complex was further validated experimentally by single crystal X-ray analysis of a host–guest complex with coronene as a qualitative transition state analogue.

opencc-by-4.0Nov 2023View details →

Raw data of healthy children and adults in a visual learning task, a conditional learning task and a transitive inference task.

Raw data of 71 healthy children (31 girls; average age: 6.42 years; range: 2.95-11.64 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.Raw data of 22 healthy adults (11 femaleswomen; average age: 26.05 years; range: 20.32-29.76 years at the beginning of the study) in a visual learning task, a 3-item conditional learning task, and a 5-item conditional learning and transitive inference task.

opencc-by-4.0Sep 2024View details →

3d Transition Metal K-edge XANES Dataset for Machine Learning Models

Data This dataset contains machine learning data for K-edge X-ray Absorption Near-Edge Structure (XANES) prediction models for eight 3d transition metals (Ti -Cu). <ul> <li>features_and_spectra: Material features (X) and corresponding XAS spectra (y) for each dataset split: training (train), validation (val), and test.</li> <li> material_id_and_site: Material identifiers and site indices (according to <a href="https://github.com/AI-multimodal/Lightshow">Lightshow</a>) for each dataset split. </li> </ul> Funding This research is based upon work supported by the U.S. Department of Energy, Office of Science, Office Basic Energy Sciences, under Award Number FWP PS-030. This research also used theory and computational resources of the Center for Functional Nanomaterials, which is a U.S. Department of Energy Office of Science User Facility, and the Scientific Data and Computing Center, at Brookhaven National Laboratory under Contract No. DE-SC0012704 and by Brookhaven National Laboratory (BNL), Laboratory Directed Research and Development (LDRD) grant no. 24-004.