| 1. |
- Lima, Emilly M., et al.
(författare)
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Deep neural network-estimated electrocardiographic age as a mortality predictor
- 2021
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- The electrocardiogram (ECG) is the most commonly used exam for the screening and evaluation of cardiovascular diseases. Here, the authors propose that the age predicted by artificial intelligence from the raw ECG tracing can be a measure of cardiovascular health and provide prognostic information. The electrocardiogram (ECG) is the most commonly used exam for the evaluation of cardiovascular diseases. Here we propose that the age predicted by artificial intelligence (AI) from the raw ECG (ECG-age) can be a measure of cardiovascular health. A deep neural network is trained to predict a patient's age from the 12-lead ECG in the CODE study cohort (n = 1,558,415 patients). On a 15% hold-out split, patients with ECG-age more than 8 years greater than the chronological age have a higher mortality rate (hazard ratio (HR) 1.79, p < 0.001), whereas those with ECG-age more than 8 years smaller, have a lower mortality rate (HR 0.78, p < 0.001). Similar results are obtained in the external cohorts ELSA-Brasil (n = 14,236) and SaMi-Trop (n = 1,631). Moreover, even for apparent normal ECGs, the predicted ECG-age gap from the chronological age remains a statistically significant risk predictor. These results show that the AI-enabled analysis of the ECG can add prognostic information.
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| 2. |
- Lozano, Rafael, et al.
(författare)
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Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 392:10159, s. 2091-2138
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Tidskriftsartikel (refereegranskat)abstract
- Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
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| 3. |
- Ribeiro, Antônio H., et al.
(författare)
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Automatic diagnosis of the 12-lead ECG using a deep neural network
- 2020
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice. The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. In that context, the authors present a Deep Neural Network (DNN) that recognizes different abnormalities in ECG recordings which matches or outperform cardiology and emergency resident medical doctors.
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| 4. |
- Abbafati, Cristiana, et al.
(författare)
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- 2020
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Tidskriftsartikel (refereegranskat)
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| 5. |
- Fernandes, Juliana Folloni, et al.
(författare)
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Transplantation of Hematopoietic Stem Cells for Primary Immunodeficiencies in Brazil: Challenges in Treating Rare Diseases in Developing Countries.
- 2018
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Ingår i: Journal of clinical immunology. - : Springer Science and Business Media LLC. - 1573-2592 .- 0271-9142. ; 38:8, s. 917-926
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Tidskriftsartikel (refereegranskat)abstract
- The results of hematopoietic stem cell transplant (HSCT) for primary immunodeficiency diseases (PID) have been improving over time. Unfortunately, developing countries do not experience the same results. This first report of Brazilian experience of HSCT for PID describes the development and results in the field. We included data from transplants in 221 patients, performed at 11 centers which participated in the Brazilian collaborative group, from July 1990 to December 2015. The majority of transplants were concentrated in one center (n=123). The median age at HSCT was 22months, and the most common diseases were severe combined immunodeficiency (SCID) (n=67) and Wiskott-Aldrich syndrome (WAS) (n=67). Only 15 patients received unconditioned transplants. Cumulative incidence of GVHD grades II to IV was 23%, and GVHD grades III to IV was 10%. The 5-year overall survival was 71.6%. WAS patients had better survival compared to other diseases. Most deaths (n=53) occurred in the first year after transplantation mainly due to infection (55%) and GVHD (13%). Although transplant for PID patients in Brazil has evolved since its beginning, we still face some challenges like delayed diagnosis and referral, severe infections before transplant, a limited number of transplant centers with expertise, and resources for more advanced techniques. Measures like newborn screening for SCID may hasten the diagnosis and ameliorate patients' conditions at the moment of transplant.
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| 6. |
- Habineza, Theogene, et al.
(författare)
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End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks
- 2023
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Ingår i: Journal of Electrocardiology. - : Elsevier. - 0022-0736 .- 1532-8430. ; 81, s. 193-200
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Tidskriftsartikel (refereegranskat)abstract
- Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas-cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil.Methods: We used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition.Results: The deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years.Conclusion: We developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.
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| 7. |
- Lindow, Thomas, et al.
(författare)
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Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival
- 2023
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Ingår i: The European Heart Journal - Digital Health. - : Oxford University Press. - 2634-3916. ; 4:5, s. 384-392
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Tidskriftsartikel (refereegranskat)abstract
- AimsDeep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age.Methods and resultsBoth A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [n = 731, 103 (14.1%) deaths, 52 (7.1%) HF hospitalizations, median (interquartile range) follow-up 5.7 (4.7-6.7) years], A-ECG Heart Age Gap was associated with risk factors and outcomes [unadjusted hazard ratio (HR) (95% confidence interval) (5 year increments): 1.23 (1.13-1.34) and adjusted HR 1.11 (1.01-1.22)]. DNN-AI Heart Age Gap was associated with risk factors and outcomes after adjustments [HR (5 year increments): 1.11 (1.01-1.21)], but not in unadjusted analyses [HR 1.00 (0.93-1.08)], making it less easily applicable in clinical practice.ConclusionA-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods. Graphical Abstract
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| 8. |
- Pastika, Libor, et al.
(författare)
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Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease
- 2024
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Ingår i: npj Digital Medicine. - : Springer Nature. - 2398-6352. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.
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| 9. |
- Sangha, Veer, et al.
(författare)
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Automated multilabel diagnosis on electrocardiographic images and signals
- 2022
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- The application of artificial intelligence for automated diagnosis of electrocardiograms can improve care in remote settings but is limited by the reliance on infrequently available signal-based data. Here, the authors report the development of a multi-label automated diagnosis model for electrocardiographic images. The application of artificial intelligence (AI) for automated diagnosis of electrocardiograms (ECGs) can improve care in remote settings but is limited by the reliance on infrequently available signal-based data. We report the development of a multilabel automated diagnosis model for electrocardiographic images, more suitable for broader use. A total of 2,228,236 12-lead ECGs signals from 811 municipalities in Brazil are transformed to ECG images in varying lead conformations to train a convolutional neural network (CNN) identifying 6 physician-defined clinical labels spanning rhythm and conduction disorders, and a hidden label for gender. The image-based model performs well on a distinct test set validated by at least two cardiologists (average AUROC 0.99, AUPRC 0.86), an external validation set of 21,785 ECGs from Germany (average AUROC 0.97, AUPRC 0.73), and printed ECGs, with performance superior to signal-based models, and learning clinically relevant cues based on Grad-CAM. The model allows the application of AI to ECGs across broad settings.
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| 10. |
- Sangha, Veer, et al.
(författare)
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Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images
- 2023
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Ingår i: Circulation. - : Wolters Kluwer. - 0009-7322 .- 1524-4539. ; 148:9, s. 765-777
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a >8-fold increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in screening for LV systolic dysfunction is limited by their availability to clinicians. We developed a novel deep learning-based approach that can use ECG images for the screening of LV systolic dysfunction.METHODS: Using 12-lead ECGs plotted in multiple different formats, and corresponding echocardiographic data recorded within 15 days from the Yale New Haven Hospital between 2015 and 2021, we developed a convolutional neural network algorithm to detect an LV ejection fraction <40%. The model was validated within clinical settings at Yale New Haven Hospital and externally on ECG images from Cedars Sinai Medical Center in Los Angeles, CA; Lake Regional Hospital in Osage Beach, MO; Memorial Hermann Southeast Hospital in Houston, TX; and Methodist Cardiology Clinic of San Antonio, TX. In addition, it was validated in the prospective Brazilian Longitudinal Study of Adult Health. Gradient-weighted class activation mapping was used to localize class-discriminating signals on ECG images.RESULTS: Overall, 385 601 ECGs with paired echocardiograms were used for model development. The model demonstrated high discrimination across various ECG image formats and calibrations in internal validation (area under receiving operation characteristics [AUROCs], 0.91; area under precision-recall curve [AUPRC], 0.55); and external sets of ECG images from Cedars Sinai (AUROC, 0.90 and AUPRC, 0.53), outpatient Yale New Haven Hospital clinics (AUROC, 0.94 and AUPRC, 0.77), Lake Regional Hospital (AUROC, 0.90 and AUPRC, 0.88), Memorial Hermann Southeast Hospital (AUROC, 0.91 and AUPRC 0.88), Methodist Cardiology Clinic (AUROC, 0.90 and AUPRC, 0.74), and Brazilian Longitudinal Study of Adult Health cohort (AUROC, 0.95 and AUPRC, 0.45). An ECG suggestive of LV systolic dysfunction portended >27-fold higher odds of LV systolic dysfunction on transthoracic echocardiogram (odds ratio, 27.5 [95% CI, 22.3-33.9] in the held-out set). Class-discriminative patterns localized to the anterior and anteroseptal leads (V2 and V3), corresponding to the left ventricle regardless of the ECG layout. A positive ECG screen in individuals with an LV ejection fraction & GE;40% at the time of initial assessment was associated with a 3.9-fold increased risk of developing incident LV systolic dysfunction in the future (hazard ratio, 3.9 [95% CI, 3.3-4.7]; median follow-up, 3.2 years).CONCLUSIONS: We developed and externally validated a deep learning model that identifies LV systolic dysfunction from ECG images. This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.
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| 11. |
- Stanaway, Jeffrey D., et al.
(författare)
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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1923-1994
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Tidskriftsartikel (refereegranskat)abstract
- Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
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| 12. |
- Zvuloni, Eran, et al.
(författare)
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On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG
- 2023
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Ingår i: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9294 .- 1558-2531. ; 70:7, s. 2227-2236
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical feature engineering (FE) approaches, based on domain knowledge, hold. In addition, it remains unclear whether combining DL with FE may improve performance over a single modality.Methods: To address these research gaps and in-line with recent major experiments, we revisited three tasks: cardiac arrhythmia diagnosis (multiclass-multilabel classification), atrial fibrillation risk prediction (binary classification), and age estimation (regression). We used an overall dataset of 2.3M 12-lead ECG recordings to train the following models for each task: i) a random forest taking FE as input; ii) an end-to-end DL model; and iii) a merged model of FE+DL.Results: FE yielded comparable results to DL while necessitating significantly less data for the two classification tasks. DL outperformed FE for the regression task. For all tasks, merging FE with DL did not improve performance over DL alone. These findings were confirmed on the additional PTB-XL dataset. Conclusion: We found that for traditional 12-lead ECG based diagnosis tasks, DL did not yield a meaningful improvement over FE, while it improved significantly the nontraditional regression task. We also found that combining FE with DL did not improve over DL alone, which suggests that the FE was redundant with the features learned by DL.Significance: Our findings provides important recommendations on 12-lead ECG based machine learning strategy and data regime to choose for a given task. When looking at maximizing performance as the end goal, if the task is nontraditional and a large dataset is available then DL is preferable. If the task is a classical one and/or a small dataset is available then a FE approach may be the better choice.
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| 13. |
- da Cunha, Wiliam Ferreira, et al.
(författare)
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Reactive Scattering between Excitons and Charge Carriers in Conjugated Polymers
- 2014
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Ingår i: The Journal of Physical Chemistry C. - : American Chemical Society (ACS). - 1932-7447 .- 1932-7455. ; 118:41, s. 23451-23458
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Tidskriftsartikel (refereegranskat)abstract
- The temperature influence on the scattering process between an exciton and a positively charged carrier (polaron or bipolaron) is theoretically investigated using a version of the SuSchriefferHeeger (SSH) model modified to include temperature, Coulomb interactions, and an external electric field. In general, it is observed that the products of the reactive scattering are spin independent when thermal effects are taken into account. For the interaction between a polaron and an exciton, the polaron can be annihilated, when subjected to temperatures higher than a critical value, or pass through the exciton maintaining both their consistencies, if a lower temperature regime is considered. Regarding the recombination between a bipolaron and an exciton, it is observed that the bipolaron can be annihilated whereas the exciton dissociates into two trions or into one polaron and one trion. In all cases, the recombination mechanisms depend on a suitable balance between temperature and electric field. These results may extend the knowledge about electroluminescence process in conjugated polymers, thus being of potential use to improve internal quantum efficiency in polymer light-emitting diodes.
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| 14. |
- de Sousa, Leonardo Evaristo, et al.
(författare)
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Dynamical exciton decay in organic materials: the role of bimolecular recombination
- 2019
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : ROYAL SOC CHEMISTRY. - 1463-9076 .- 1463-9084. ; 21:4, s. 1711-1716
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Tidskriftsartikel (refereegranskat)abstract
- Excitons play a critical role in light emission when it comes to organic semiconductors. In high exciton concentration regimes, monomolecular and bimolecular routes for exciton recombination can yield different products affecting significantly the materials optical properties. Here, the dynamical decay of excitons is theoretically investigated using a kinetic Monte Carlo approach that addresses singlet exciton diffusion. Our numerical protocol includes two distinct exciton-exciton interaction channels: exciton annihilation and biexciton cascade emission. Our findings reveal that these channels produce different consequences concerning diffusion and spectroscopic properties, being able to explain diverging experimental observations. Importantly, we estimate critical exciton densities for which bimolecular recombination becomes dominant and investigate its effect on average exciton lifetimes and diffusion lengths.
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| 15. |
- Ferreira da Cunha, Wiliam, et al.
(författare)
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Impurity effects on polaron dynamics in graphene nanoribbons
- 2015
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Ingår i: Carbon. - : Elsevier. - 0008-6223 .- 1873-3891. ; 91, s. 171-177
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Tidskriftsartikel (refereegranskat)abstract
- The impurity effects on the dynamics of polarons in armchair graphene nanoribbons are numerically investigated in the scope of a two-dimensional tight-binding approach with lattice relaxation. The results show that the presence of an impurity changes significantly the net charge distribution associated to the polaron structure. Moreover, the interplay between external electric field and the local impurities plays the role of drastically modifying the polaron dynamics. Interestingly, nanoribbons containing mobile polarons are noted to take place even when considering high impurity levels, which is associated with the highly conductive character of the graphene nanoribbons. This investigation may enlighten the understanding of the charge transport mechanism in carbon-based nanomaterials. (C) 2015 Elsevier Ltd. All rights reserved.
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| 16. |
- Ferreira Monteiro, Fabio, et al.
(författare)
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Encapsulated beta-carotene in ZnO nanotubes: Theoretical insight into the stabilization dynamics
- 2015
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Ingår i: Chemical Physics Letters. - : ELSEVIER SCIENCE BV. - 0009-2614 .- 1873-4448. ; 636, s. 62-66
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Tidskriftsartikel (refereegranskat)abstract
- The stabilization dynamics of a molecular dye (beta-carotene) encapsulated in single-wall zinc oxide nanotubes (ZnONTs) is theoretically investigated in the scope of molecular dynamics and density functional theory simulations. Our findings show that the beta-carotene encapsulation in ZnONTs is an energetically favorable process. Once encapsulated, this molecular dye remains close to the ZnONT wall, in accordance with recent experimental reports. Interestingly, the interaction between the beta-carotene and ZnONT can form a charge delocalization state, where an amount of charge concentrated on beta-carotene is transferred to ZnONT. (C) 2015 Elsevier B.V. All rights reserved.
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| 17. |
- Kastinen, Tuuva, et al.
(författare)
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Electronic couplings and rates of excited state charge transfer processes at poly(thiophene-co-quinoxaline)-PC71BM interfaces: two- versus multi-state treatments
- 2019
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : ROYAL SOC CHEMISTRY. - 1463-9076 .- 1463-9084. ; 21:46, s. 25606-25625
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Tidskriftsartikel (refereegranskat)abstract
- Electronic coupling between adjacent molecules is one of the key parameters determining the charge transfer (CT) rates in bulk heterojunction (BHJ) polymer solar cells (PSCs). We calculate theoretically electronic couplings for exciton dissociation (ED) and charge recombination (CR) processes at local poly(thiophene-co-quinoxaline) (TQ)-PC71BM interfaces. We use eigenstate-based coupling schemes, i.e. the generalized Mulliken-Hush (GMH) and fragment charge difference (FCD) schemes, including 2 to multiple (3-11) states. Moreover, we study the effects of functionals, excited state methods, basis sets, surrounding media, and relative placements of TQ and PC71BM on the coupling values. Generally, both schemes provide consistent couplings with the global hybrid functionals, which yield more charge-localized diabatic states and constant coupling values regardless of the number of states, and so the 2-state schemes may be sufficient. The (non-tuned and optimally tuned) long-range corrected (LRC) functionals result in more notable mixing of the local components with the CT states. Employing multiple states reduces the mixing and thus improves the LRC results, although the method still affects the GMH CR couplings. As the FCD scheme is less sensitive, we recommend combining it with the multi-state treatment for polymer-fullerene systems when using the LRC functionals. Finally, we employ the 11-state FCD couplings to calculate the ED and CR rates, which are consistent with the experimental rates of the polymer-fullerene systems. Our results provide more insight into choosing a suitable eigenstate-based coupling scheme for predicting the electronic couplings and CT rates in photoactive systems.
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| 18. |
- Passos Abreu, Ana Virginia, et al.
(författare)
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Impact of the Electron-Phonon Interactions on the Polaron Dynamics in Graphene Nanoribbons
- 2016
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Ingår i: Journal of Physical Chemistry A. - : AMER CHEMICAL SOC. - 1089-5639 .- 1520-5215. ; 120:27, s. 4901-4906
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Tidskriftsartikel (refereegranskat)abstract
- The influence of the electron-phonon (e-ph) interactions on the filed-included polaron dynamics in armchair graphene nanoribbons (GNRs) is theoretically investigated in the scope of a two-dimensional tight-binding model. The results show that the localization of the polaronic charge increases when the strength of e-ph coupling also increases. Consequently, the polaron saturation velocity decreases for higher e-ph coupling strengths. Interestingly, the interplay between the e-ph coupling strength and the GNR width changes substantially the polaron dynamics properties.
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| 19. |
- Ribeiro Jr, Luiz Antonio, et al.
(författare)
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Spin-Orbit Effects on the Dynamical Properties of Polarons in Graphene Nanoribbons
- 2018
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- The dynamical properties of polarons in armchair graphene nanoribbons (GNR) is numerically investigated in the framework of a two-dimensional tight-binding model that considers spin-orbit (SO) coupling and electron-lattice (e-l) interactions. Within this physical picture, novel polaron properties with no counterparts to results obtained from conventional tight-binding models are obtained. Our findings show that, depending on the systems width, the presence of SO coupling changes the polarons charge localization giving rise to different degrees of stability for the charge carrier. For instance, the joint action of SO coupling and e-l interactions could promote a slight increase on the charge concentration in the center of the lattice deformation associated to the polaron. As a straightforward consequence, this process of increasing stability would lead to a depreciation in the polarons motion by decreasing its saturation velocity. Our finds are in good agreement with recent experimental investigations for the charge localization in GNR, mostly when it comes to the influence of SO coupling. Moreover, the contributions reported here provide a reliable method for future works to evaluate spin-orbit influence on the performance of graphene nanoribbons.
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| 20. |
- Ribeiro, Luiz Antonio, et al.
(författare)
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Bloch oscillations in organic and inorganic polymers
- 2017
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Ingår i: Journal of Chemical Physics. - : AMER INST PHYSICS. - 0021-9606 .- 1089-7690. ; 146:14
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Tidskriftsartikel (refereegranskat)abstract
- The transport of polarons above the mobility threshold in organic and inorganic polymers is theoretically investigated in the framework of a one-dimensional tight-binding model that includes lattice relaxation. The computational approach is based on parameters for which the model Hamiltonian suitably describes different polymer lattices in the presence of external electric fields. Our findings show that, above critical field strengths, a dissociated polaron moves through the polymer lattice as a free electron performing Bloch oscillations. These critical electric fields are considerably smaller for inorganic lattices in comparison to organic polymers. Interestingly, for inorganic lattices, the free electron propagates preserving charge and spin densities localization which is a characteristic of a static polaron. Moreover, in the turning points of the spatial Bloch oscillations, transient polaron levels are formed inside the band gap, thus generating a fully characterized polaron structure. For the organic case, on the other hand, no polaron signature is observed: neither in the shape of the distortion-those polaron profile signatures are absent-nor in the energy levels-as no such polaron levels are formed during the simulation. These results solve controversial aspects concerning Bloch oscillations recently reported in the literature and may enlighten the understanding about the charge transport mechanism in polymers above their mobility edge. Published by AIP Publishing.
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| 21. |
- Ribeiro, Luiz Antonio, et al.
(författare)
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Concentration effects on intrachain polaron recombination in conjugated polymers
- 2015
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Ingår i: Physical Chemistry, Chemical Physics - PCCP. - : Royal Society of Chemistry. - 1463-9076 .- 1463-9084. ; 17:2, s. 1299-1308
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Tidskriftsartikel (refereegranskat)abstract
- The influence of different charge carrier concentrations on the recombination dynamics between oppositely charged polarons is numerically investigated using a modified version of the Su-Schrieffer-Heeger (SSH) model that includes an external electric field and electron-electron interactions. Our findings show that the external electric field can play the role of avoiding the formation of excited states (polaron-exciton and neutral excitation) leading the system to a dimerized lattice. Interestingly, depending on a suitable balance between the polaron concentration and the electric field strength, the recombination mechanism can form stable polaron-excitons or neutral excitations. These results may provide guidance to improve the electroluminescence efficiency in Polymer Light Emitting Diodes.
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| 22. |
- Ribeiro, Luiz Antonio, et al.
(författare)
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Dynamic Formation of Bipolaron-Exciton Complexes in Conducting Polymers
- 2018
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Ingår i: Journal of Physical Chemistry A. - : AMER CHEMICAL SOC. - 1089-5639 .- 1520-5215. ; 122:15, s. 3866-3872
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Tidskriftsartikel (refereegranskat)abstract
- The recombination dynamics of two oppositely charged bipolarons within a single polymer chain is numerically studied in the scope of a one-dimensional tight-binding model that considers electron electron and electron-phonon (e-ph) interactions. By scanning among values of e-ph coupling and electric field, novel channels for the bipolaron recombination were yielded based on the interplay between these two parameters. The findings point to the formation of a compound species formed from the coupling between a bipolaron and an exciton. Depending on the electric field and e-ph coupling strengths, the recombination mechanism may yield two distinct products: a trapped (and almost neutral) or a moving (and partially charged) bipolaron-exciton. These results might enlighten the understanding of the electroluminescence processes in organic light-emitting devices.
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| 23. |
- Ribeiro, Luiz Antonio, et al.
(författare)
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Temperature effects on intrachain recombination of bipolarons in conjugated polymers
- 2014
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Ingår i: Chemical Physics Letters. - : Elsevier. - 0009-2614 .- 1873-4448. ; 614, s. 151-155
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Tidskriftsartikel (refereegranskat)abstract
- The temperature influence over the intrachain recombination dynamics between oppositely charged bipolarons has been theoretically investigated using a version of the Su-Schrieffer-Heeger model. The results shown that, below of a critical temperature regime, these charge carriers can recombine into a biexciton. This excited state is a light emissive specie that can emit one photon and turn into an exciton state. This specie can thereafter decay to the ground state by other photon emission. This knowledge can enlighten the understanding needed to improve the internal quantum efficiency of electroluminescence in Polymer Light Emitting Diodes.
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| 24. |
- Ribeiro, Luiz Antonio, et al.
(författare)
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Transport of Polarons in Graphene Nanoribbons
- 2015
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Ingår i: The Journal of Physical Chemistry Letters. - : American Chemical Society. - 1948-7185. ; 6:3, s. 510-514
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Tidskriftsartikel (refereegranskat)abstract
- The field-induced dynamics of polarons in armchair graphene nanoribbons (GNRs) is theoretically investigated in the framework of a two-dimensional tight-binding model with lattice relaxation. Our findings show that the semiconductor behavior, fundamental to polaron transport to take place, depends upon of a suitable balance between the GNR width and the electronphonon (eph) coupling strength. In a similar way, we found that the parameter space for which the polaron is dynamically stable is limited to an even narrower region of the GNR width and the eph coupling strength. Interestingly, the interplay between the external electric field and the eph coupling plays the role to define a phase transition from subsonic to supersonic velocities for polarons in GNRs.
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| 25. |
- Rivera Vila, Henrique Vieira, et al.
(författare)
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On the Angular Distribution of the H+Li-2 Cross Sections: a Converged Time-Independent Quantum Scattering Study
- 2018
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Ingår i: Scientific Reports. - : NATURE PUBLISHING GROUP. - 2045-2322. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- A thorough time-independent quantum scattering study is performed on a benchmark potential energy surface for the H+Li-2 reaction at the fundamental electronic state. Integral and differential cross sections are calculated along with thermal rate coefficients until convergence is reached. Our findings show that vibrational and rotational excitations of the reactant hinder reactivity, though for the latter a considerable reaction promotion was spotted as we increase the reactant rotational quantum number until the critical value of j = 4. Such a promotion then begins to retract, eventually becoming an actual inhibition for larger j. In a straightforward manner, the concept of time-independent methods implemented in this study allowed this accurate state-to-state analysis. Furthermore, a nearly isotropic behaviour of the scattering is noted to take place from the angular point of view. Remarkably, our computational protocol is ideally suited to yield converged thermal rate coefficients, revealing a non-Arrhenius pattern and showing that J-shifting approach fails to describe this particular reaction. Our results, when compared to previous and independent ones, reinforce the latest theoretical reference for future validation in the experimental field.
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