Tetramerization of BEB-Doped Phenalenyls to Obtain (BE)8-[16]Annulenes (E = N, O).

Two (BE)8-[16]annulenes were prepared and fully characterized by experimental and quantum-chemical means (1, E = N; 2, E = O). The 1,8-naphthalenediyl-bridged diborane(6) 3 served as their common starting material, which was treated with [Al(NH3)6]Cl3 to form 1 (91% yield) or with 1,8-naphthalenediboronic acid anhydride to form 2 (93% yield). As a result, the heteroannulenes 1 and 2 are supported by four aromatic "clamps" and may also be viewed as NH- or O-bridged cyclic tetramers of BNB- or BOB-doped phenalenyls. X-ray crystallography on mono-, di-, and tetraadducts 2·thf, 2·py2, and 2·py4 showed that 2 is an oligotopic Lewis acid (thf/py: tetrahydrofuran/pyridine donor). The applicability of 2 also as a Lewis basic ligand in coordination chemistry was demonstrated by the synthesis of the mononuclear Ag+ complex [Ag(py)2(2·py4)]+ and the dinuclear Pb2+ complex 6. During the assembly of 6, the rearrangement of 2 led to the formation of two (BO)9-macrocycles linked by two BOB-phenalenyls to form a nanometer-sized cage with four negatively charged, tetracoordinated B atoms. Both 1 and 2 show several redox waves in the cathodic regions of the cyclic voltammograms. An in-depth assessment of the consequences of electron injection on the aromaticity of 1 and 2 was achieved by electronic structure calculations. 1 and 2 are proposed to exhibit aromatic switching capabilities in the [16]annulene motif.

Brain Tumor Imaging in Adolescents and Young Adults: 2021 WHO Updates for Molecular-based Tumor Types.

Published in 2021, the fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) introduced new molecular criteria for tumor types that commonly occur in either pediatric or adult age groups. Adolescents and young adults (AYAs) are at the intersection of adult and pediatric care, and both pediatric-type and adult-type CNS tumors occur at that age. Mortality rates for AYAs with CNS tumors have increased by 0.6% per year for males and 1% per year for females from 2007 to 2016. To best serve patients, it is crucial that both pediatric and adult radiologists who interpret neuroimages are familiar with the various pediatric- and adult-type brain tumors and their typical imaging morphologic characteristics. Gliomas account for approximately 80% of all malignant CNS tumors in the AYA age group, with the most common types observed being diffuse astrocytic and glioneuronal tumors. Ependymomas and medulloblastomas also occur in the AYA population but are seen less frequently. Importantly, biologic behavior and progression of distinct molecular subgroups of brain tumors differ across ages. This review discusses newly added or revised gliomas in the fifth edition of the CNS WHO classification, as well as other CNS tumor types common in the AYA population.

NBN- and BNB-Phenalenyls: the Yin and Yang of Heteroatom-doped π Systems.

NBN- and BNB-doped phenalenyls are isoelectronic to phenalenyl anions and cations, respectively. They represent a pair of complementary molecules that have essentially identical structures but opposite properties as electron donors and acceptors. The NBN-phenalenyls 1-4 considered here were prepared from N,N'-dimethyl-1,8-diaminonaphthalene and readily available boron-containing building blocks (i. e., BH3⋅SMe2 (1), p-CF3-C6H4B(OH)2 (2), C6H5B(OH)2 (3), or MesBCl2/iPr2NEt (4)). Treatment of 1 with 4-Me2N-2,6-Me2-C6H2Li gave the corresponding NBN derivative 5. The BNB-phenalenyl 6 was synthesized from 1,8-naphthalenediyl-bridged diborane(6), PhNH2, and MesMgBr. A computational study reveals that the photoemission of 1, 4, and 5 originates from locally excited (LE) states at the NBN-phenalenyl fragments, while that of 2 is dominated by charge transfer (CT) from the NBN-phenalenyl to the p-CF3-C6H4 fragment. Depending on the dihedral angle θ between its Ph and NBN planes, compound 3 emits mainly from a less polar LE (θ >55°) or more polar CT state (θ <55°). In turn, the energetic preference for either state is governed by the polarity of the solvent used. An equimolar aggregate of the NBN- and BNB-phenalenyls 3 and 6 (in THF/H2O) shows a distinct red-shifted emission compared to that of the individual components, which originates from an intermolecular CT state.

Increased confidence of radiomics facilitating pretherapeutic differentiation of BRAF-altered pediatric low-grade glioma.

OBJECTIVES: Currently, the BRAF status of pediatric low-grade glioma (pLGG) patients is determined through a biopsy. We established a nomogram to predict BRAF status non-invasively using clinical and radiomic factors. Additionally, we assessed an advanced thresholding method to provide only high-confidence predictions for the molecular subtype. Finally, we tested whether radiomic features provide additional predictive information for this classification task, beyond that which is embedded in the location of the tumor. METHODS: Random forest (RF) models were trained on radiomic and clinical features both separately and together, to evaluate the utility of each feature set. Instead of using the traditional single threshold technique to convert the model outputs to class predictions, we implemented a double threshold mechanism that accounted for uncertainty. Additionally, a linear model was trained and depicted graphically as a nomogram. RESULTS: The combined RF (AUC: 0.925) outperformed the RFs trained on radiomic (AUC: 0.863) or clinical (AUC: 0.889) features alone. The linear model had a comparable AUC (0.916), despite its lower complexity. Traditional thresholding produced an accuracy of 84.5%, while the double threshold approach yielded 92.2% accuracy on the 80.7% of patients with the highest confidence predictions. CONCLUSION: Models that included radiomic features outperformed, underscoring their importance for the prediction of BRAF status. A linear model performed similarly to RF but with the added benefit that it can be visualized as a nomogram, improving the explainability of the model. The double threshold technique was able to identify uncertain predictions, enhancing the clinical utility of the model. CLINICAL RELEVANCE STATEMENT: Radiomic features and tumor location are both predictive of BRAF status in pLGG patients. We show that they contain complementary information and depict the optimal model as a nomogram, which can be used as a non-invasive alternative to biopsy. KEY POINTS: • Radiomic features provide additional predictive information for the determination of the molecular subtype of pediatric low-grade gliomas patients, beyond what is embedded in the location of the tumor, which has an established relationship with genetic status. • An advanced thresholding method can help to distinguish cases where machine learning models have a high chance of being (in)correct, improving the utility of these models. • A simple linear model performs similarly to a more powerful random forest model at classifying the molecular subtype of pediatric low-grade gliomas but has the added benefit that it can be converted into a nomogram, which may facilitate clinical implementation by improving the explainability of the model.

Unraveling Pre-filled Syringe Needle Clogging: Exploring a Fresh Outlook Through Innovative Techniques.

OBJECTIVE: This study aimed to investigate the movement of liquid in the needle region of staked-in-needle pre-filled syringes using neutron imaging and synchrotron X-ray tomography. The objective was to gain insights into the dynamics of liquid presence and understand the factors contributing to needle clogging. METHODS: Staked-in-needle pre-filled syringes were examined using neutron radiography and synchrotron X-ray phase-contrast computed tomography. Neutron radiography provided a 2D visualization of liquid presence in the needle, while synchrotron X-ray tomography offered high-resolution 3D imaging to study detailed morphological features of the liquid. RESULTS: Neutron radiography revealed liquid presence in the needle region for as-received samples and after temperature and pressure cycling. Pressure cycling had a more pronounced effect on liquid formation. Synchrotron X-ray tomography confirmed the presence of liquid and revealed various morphologies, including droplets of different sizes, liquid segments blocking sections of the needle, and a thin layer covering the needle wall. Liquid presence was also observed between the steel needle and the glass barrel. CONCLUSIONS: The combination of neutron imaging and synchrotron X-ray tomography provided valuable insights into the dynamics of liquid movement in staked-in-needle pre-filled syringes. Temperature and pressure cycling were found to contribute to additional liquid formation, with pressure changes playing a significant role. The detailed morphological analysis enhanced the understanding of microstructural arrangements within the needle. This research contributes to addressing the issue of needle clogging and can guide the development of strategies to improve pre-filled syringe performance.

Pediatric-type diffuse low-grade gliomas.

The World Health Organization's 5th edition classification of Central Nervous System (CNS) tumors differentiates diffuse gliomas into adult and pediatric variants. Pediatric-type diffuse low-grade gliomas (pDLGGs) are distinct from adult gliomas in their molecular characteristics, biological behavior, clinical progression, and prognosis. Various molecular alterations identified in pDLGGs are crucial for treatment. There are four distinct entities of pDLGGs. All four of these tumor subtypes exhibit diffuse growth and share overlapping histopathological and imaging characteristics. Molecular analysis is essential for differentiating these lesions.

The unintended consequences of artificial intelligence in paediatric radiology.

Over the past decade, there has been a dramatic rise in the interest relating to the application of artificial intelligence (AI) in radiology. Originally only 'narrow' AI tasks were possible; however, with increasing availability of data, teamed with ease of access to powerful computer processing capabilities, we are becoming more able to generate complex and nuanced prediction models and elaborate solutions for healthcare. Nevertheless, these AI models are not without their failings, and sometimes the intended use for these solutions may not lead to predictable impacts for patients, society or those working within the healthcare profession. In this article, we provide an overview of the latest opinions regarding AI ethics, bias, limitations, challenges and considerations that we should all contemplate in this exciting and expanding field, with a special attention to how this applies to the unique aspects of a paediatric population. By embracing AI technology and fostering a multidisciplinary approach, it is hoped that we can harness the power AI brings whilst minimising harm and ensuring a beneficial impact on radiology practice.

Accuracy of Information and References Using ChatGPT-3 for Retrieval of Clinical Radiological Information.

Purpose: To assess the accuracy of answers provided by ChatGPT-3 when prompted with questions from the daily routine of radiologists and to evaluate the text response when ChatGPT-3 was prompted to provide references for a given answer. Methods: ChatGPT-3 (San Francisco, OpenAI) is an artificial intelligence chatbot based on a large language model (LLM) that has been designed to generate human-like text. A total of 88 questions were submitted to ChatGPT-3 using textual prompt. These 88 questions were equally dispersed across 8 subspecialty areas of radiology. The responses provided by ChatGPT-3 were assessed for correctness by cross-checking them with peer-reviewed, PubMed-listed references. In addition, the references provided by ChatGPT-3 were evaluated for authenticity. Results: A total of 59 of 88 responses (67%) to radiological questions were correct, while 29 responses (33%) had errors. Out of 343 references provided, only 124 references (36.2%) were available through internet search, while 219 references (63.8%) appeared to be generated by ChatGPT-3. When examining the 124 identified references, only 47 references (37.9%) were considered to provide enough background to correctly answer 24 questions (37.5%). Conclusion: In this pilot study, ChatGPT-3 provided correct responses to questions from the daily clinical routine of radiologists in only about two thirds, while the remainder of responses contained errors. The majority of provided references were not found and only a minority of the provided references contained the correct information to answer the question. Caution is advised when using ChatGPT-3 to retrieve radiological information.

MRI-Based End-To-End Pediatric Low-Grade Glioma Segmentation and Classification.

Purpose: MRI-based radiomics models can predict genetic markers in pediatric low-grade glioma (pLGG). These models usually require tumour segmentation, which is tedious and time consuming if done manually. We propose a deep learning (DL) model to automate tumour segmentation and build an end-to-end radiomics-based pipeline for pLGG classification. Methods: The proposed architecture is a 2-step U-Net based DL network. The first U-Net is trained on downsampled images to locate the tumour. The second U-Net is trained using image patches centred around the located tumour to produce more refined segmentations. The segmented tumour is then fed into a radiomics-based model to predict the genetic marker of the tumour. Results: Our segmentation model achieved a correlation value of over 80% for all volume-related radiomic features and an average Dice score of .795 in test cases. Feeding the auto-segmentation results into a radiomics model resulted in a mean area under the ROC curve (AUC) of .843, with 95% confidence interval (CI) [.78-.906] and .730, with 95% CI [.671-.789] on the test set for 2-class (BRAF V600E mutation BRAF fusion) and 3-class (BRAF V600E mutation BRAF fusion and Other) classification, respectively. This result was comparable to the AUC of .874, 95% CI [.829-.919] and .758, 95% CI [.724-.792] for the radiomics model trained and tested on the manual segmentations in 2-class and 3-class classification scenarios, respectively. Conclusion: The proposed end-to-end pipeline for pLGG segmentation and classification produced results comparable to manual segmentation when it was used for a radiomics-based genetic marker prediction model.

Confined Lewis Pairs: Investigation of the X- →Si20 Interaction in Halogen-Encapsulating Silafulleranes.

A joint theoretical and experimental study on 32 endohedral silafullerane derivatives [X@Si20 Y20 ]- (X=F-I; Y=F-I, H, Me, Et) and T h ${T_h }$ -[Cl@Si20 H12 Y8 ]- (Y=F-I) is presented. First, we evaluated the structure-determining template effect of Cl- in a systematic series of concave silapolyquinane model systems. Second, we investigated the X- →Si20 interaction energy ( E int ${E_{{\rm{int}}} }$ ) as a function of X- and Y and found the largest E int ${E_{{\rm{int}}} }$ values for electron-withdrawing exohedral substituents Y. Given that X- ions can be considered as Lewis bases and empty Si20 Y20 clusters as Lewis acids, we classify our inseparable host-guest complexes [X@Si20 Y20 ]- as "confined Lewis pairs". Third, 35 Cl NMR spectroscopy proved to be highly diagnostic for an experimental assessment of the Cl- →Si20 interaction as the paramagnetic shielding and, in turn, δ ${\delta }$ (35 Cl) of the endohedral Cl- ion correlate inversely with E int ${E_{{\rm{int}}} }$ . Finally, we disclose the synthesis of [PPN][Cl@Si20 Y20 ] (Y=Me, Et, Br) and provide a thorough characterization of these new silafulleranes.

B2,N4-Doped Heptacenes: Ambipolar Charge-Transfer Compounds with Deep LUMO Levels.

The B2,N4-doped heptacene H4 in which two N,N'-dihydrophenazine units are linked by two BMes bridges (Mes = mesityl) was synthesized via fourfold Buchwald-Hartwig coupling between 2,3,6,7-tetrachloro-9,10-dimesityl-9,10-dihydro-9,10-diboraanthracene and o-phenylenediamine (tBuXPhos-Pd-G3, DBU/NaOTf, 2-MeTHF, 50 °C, 16 h). Upon exposure to ambient air, H4 is oxidized to its N,N'-dihydro form H2; further oxidation with MnO2 furnishes the di(phenazine) derivative H0. Stirring under a blanket of H2 in the presence of Pd/C hydrogenates H0 back to H2 and ultimately H4. Yellow-colored H0 is a remarkably good electron acceptor with a LUMO-energy level of -3.9 eV; upon irradiation with a 405 nm LED in the presence of THF or 1,4-cyclohexadiene, H0 accepts two H atoms to furnish H2. One-electron reduction of H0 yields the isolable radical-anion salt Li[H0] (lithium naphthalenide, THF, -30 °C to rt). The ambipolar compounds H2 and H4 possess a navy blue and deep purple color, respectively, due to charge-transfer interactions from the electron-rich N,N'-dihydrophenazine donor(s) to the electron-accepting B2C4 core.

Regioselective Derivatization of Silylated [20]Silafulleranes.

Silafulleranes with endohedral Cl- ions are a unique, scarcely explored class of structurally well-defined silicon clusters and host-guest complexes. Herein, we report regioselective derivatization reactions on the siladodecahedrane [nBu4N][Cl@Si20(SiCl3)12Cl8] ([nBu4N][1]), which has its cluster surface decorated with 12 SiCl3 and 8 Cl substituents in perfect Th symmetry. The room-temperature reaction of [nBu4N][1] with excess iBu2AlH in ortho-difluorobenzene (oDFB) furnishes perhydrogenated [nBu4N][Cl@Si20(SiH3)12H8] ([nBu4N][2]) in 50% yield; the non-pyrophoric [2]- is the largest structurally authenticated (by X-ray diffraction) hydridosilane known to date. A simple switch from pure oDFB to an oDFB/Et2O solvent mixture suppresses core hydrogenation and results in the formation of [nBu4N][Cl@Si20(SiH3)12Cl8] ([nBu4N][3]). In addition to the exhaustive Cl/H exchange at all 44 Si-Cl bonds of [1]- and the regioselective 36-fold silyl group hydrogenation, we achieved the simultaneous introduction of Me substituents at all 8 SiCl vertices along with the conversion of all 12 SiCl3 to SiH3 groups by treating [nBu4N][1] with Me2AlH/Me3Al in oDFB ([nBu4N][Cl@Si20(SiH3)12Me8], [nBu4N][4]; 73%). Quantum-chemical free-energy calculations find an SN2-Si-type hydrogenation of the exohedral SiCl3 moieties in [1]- (trigonal-bipyramidal intermediate) slightly preferred over metathesis-like SNi-Si substitutions (four-membered transition state). Cage hydrogenation likely occurs via SNi-Si processes. The experimentally demonstrated influence of an Et2O co-solvent, which drastically increases the respective reaction barriers, is attributed to the increased stability of the resulting iBu2AlH-OEt2 adduct and its higher steric bulk compared to free iBu2AlH.

A Hydride-Substituted Homoleptic Silylborate: How Similar is it to its Diborane(6)-Dianion Isostere?

The B-nucleophilic 9H-9-borafluorene dianion reacts with 9-chloro-9-silafluorene to afford air- and moisture-stable silylborate salts M[Ar2 (H)B-Si(H)Ar2 ] (M[HBSiH], M=Li, Na). Li[HBSiH] and Me3 SiCl give the B-pyridine adduct Ar2 (py)B-Si(H)Ar2 ((py)BSiH) or the chlorosilane Li[Ar2 (H)B-Si(Cl)Ar2 ] (Li[HBSiCl]) in C6 H6 -pyridine or THF. In both cases, the first step is H- abstraction at the B center. The resulting free borane subsequently binds a py or thf ligand. While the py adduct is stable at room temperature, the thf adduct undergoes a 1,2-H shift via the cyclic B(µ-H)Si intermediate BHSi, which is afterwards attacked at the Si atom by a Cl- ion to give Li[HBSiCl]. DFT calculations were employed to support the proposed reaction mechanism and to characterize the electronic structure of BHSi. Treatment of Li[HBSiCl] with the N-heterocyclic carbene IMe introduces the neutral donor at the Si atom and leads to Ar2 (H)B-Si(IMe)Ar2 (HBSi(IMe)), a donor-acceptor-stabilized silylene.

European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

A new task force dedicated to artificial intelligence (AI) with respect to paediatric radiology was created in 2021 at the International Paediatric Radiology (IPR) meeting in Rome, Italy (a joint society meeting by the European Society of Pediatric Radiology [ESPR] and the Society for Pediatric Radiology [SPR]). The concept of a separate task force dedicated to AI was borne from an ESPR-led international survey of health care professionals' opinions, expectations and concerns regarding AI integration within children's imaging departments. In this survey, the majority (> 80%) of ESPR respondents supported the creation of a task force and helped define our key objectives. These include providing educational content about AI relevant for paediatric radiologists, brainstorming ideas for future projects and collaborating on AI-related studies with respect to collating data sets, de-identifying images and engaging in multi-case, multi-reader studies. This manuscript outlines the starting point of the ESPR AI task force and where we wish to go.

Can You Tell Who Scores? An Assessment of the Recognition of Affective States Based on the Nonverbal Behavior of Amateur Tennis Players in Competitive Matches.

The purpose of the present study was to assess whether the recognition of tennis players' affective state associated with their nonverbal behavior would be influenced by (a) the importance of the situation, (b) the point outcome, and (c) the tennis expertise of the observer. Two hundred sixty-nine participants (Mage = 30.51 years; 116 female; 79 tennis club members) watched video excerpts showing the nonverbal behavior of amateur tennis players during competitive matches immediately after the end of a rally and were asked to estimate whether the player had just won or lost the point. Results indicate that the recognition rates were higher for situations closer to the end of a game, closer to the end of a set, and with a tighter score during a game. Moreover, recognition rates were higher for lost than for won points, while the tennis expertise of participants had no influence on the recognition rates.

An Educational Graphical User Interface to Construct Convolutional Neural Networks for Teaching Artificial Intelligence in Radiology.

Deep learning techniques using convolutional neural networks (CNNs) have been successfully developed for various medical image analysis tasks. However, the skills to understand and develop deep learning models are not usually taught during radiology training, which constitutes a barrier for radiologists looking to integrate machine learning (ML) into their research or clinical practice. In this work, we developed and evaluated an educational graphical user interface (GUI) to construct CNNs for teaching deep learning concepts to radiology trainees. The GUI was developed in Python using the PyQt and PyTorch frameworks. The functionality of the GUI was demonstrated through a binary classification task on a dataset of MR images of the brain. The usability of the GUI was assessed through 45-min user testing sessions with 5 neuroradiologists and neuroradiology fellows, assessing mean task completion times, the System Usability Scale (SUS), and a qualitative questionnaire as metrics. Task completion times were compared against a ML expert who performed the same tasks. After a 20-min introduction to CNNs and a walkthrough of the GUI, users were able to perform all assigned tasks successfully. There was no significant difference in task completion time compared to a ML expert. The educational GUI achieved a score of 82.5 on the SUS, suggesting that the system is highly usable. Users indicated that the GUI seems useful as an educational tool to teach ML topics to radiology trainees. An educational GUI allows interactive teaching in ML that can be incorporated into radiology training.

Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma.

Purpose: Biopsy-based assessment of H3 K27 M status helps in predicting survival, but biopsy is usually limited to unusual presentations and clinical trials. We aimed to evaluate whether radiomics can serve as prognostic marker to stratify diffuse intrinsic pontine glioma (DIPG) subsets. Methods: In this retrospective study, diagnostic brain MRIs of children with DIPG were analyzed. Radiomic features were extracted from tumor segmentations and data were split into training/testing sets (80:20). A conditional survival forest model was applied to predict progression-free survival (PFS) using training data. The trained model was validated on the test data, and concordances were calculated for PFS. Experiments were repeated 100 times using randomized versions of the respective percentage of the training/test data. Results: A total of 89 patients were identified (48 females, 53.9%). Median age at time of diagnosis was 6.64 years (range: 1-16.9 years) and median PFS was 8 months (range: 1-84 months). Molecular data were available for 26 patients (29.2%) (1 wild type, 3 K27M-H3.1, 22 K27M-H3.3). Radiomic features of FLAIR and nonenhanced T1-weighted sequences were predictive of PFS. The best FLAIR radiomics model yielded a concordance of .87 [95% CI: .86-.88] at 4 months PFS. The best T1-weighted radiomics model yielded a concordance of .82 [95% CI: .8-.84] at 4 months PFS. The best combined FLAIR + T1-weighted radiomics model yielded a concordance of .74 [95% CI: .71-.77] at 3 months PFS. The predominant predictive radiomic feature matrix was gray-level size-zone. Conclusion: MRI-based radiomics may predict progression-free survival in pediatric diffuse midline glioma/diffuse intrinsic pontine glioma.

Diboraanthracene-Doped Polymer Systems for Colour-Tuneable Room-Temperature Organic Afterglow.

Organic ultralong room temperature phosphorescence (RTP), or organic afterglow, is a unique phenomenon, gaining widespread attention due to its far-reaching application potential and fundamental interest. Here, two laterally expanded 9,10-dimesityl-dihydro-9,10-diboraanthracene (DBA) derivatives are demonstrated as excellent afterglow materials for red and blue-green light emission, which is traced back to persistent thermally activated delayed fluorescence and RTP. The lateral substitution of polycyclic DBA scaffold, together with weak transversal electron-donating mesityl groups, ensures the optimal molecular properties for (reverse) intersystem crossing and long-lived triplet states in a rigid poly(methyl methacrylate) matrix. The achieved afterglow emission quantum yields of up to 3 % and 15 %, afterglow lifetimes up to 0.8 s and 3.2 s and afterglow durations up to 5 s and 25 s (for red and blue-green emitters, respectively) are attributed to the properties of single molecules.

(BO)2 -Doped Tetrathia[7]helicene: A Configurationally Stable Blue Emitter.

Helicenes combine two central themes in chemistry: extended π-conjugation and chirality. Hetero-atom doping preserves both characteristics and allows modulation of the electronic structure of a helicene. Herein, we report the (BO)2 -doped tetrathia[7]helicene 1, which was prepared from 2-methoxy-3,3'-bithiophene in four steps. 1 is formally derived by substituting two (Mes)B-O moieties in place of (H)C=C(H) fragments in two benzene rings of the parent tetrathia[7]helicene. X-ray crystallography revealed a dihedral angle of 50.26(9)° between the two terminal thiophene rings. The (P)-/(M)-1 enantiomers were separated by chiral HPLC and are configurationally stable at room temperature. The experimentally determined enantiomerization barrier of 27.4±0.1 kcal mol-1 is lower than that of tetrathia[7]helicene (39.4±0.1 kcal mol-1 ). The circular dichroism spectra of (P)- and (M)-1 show a perfect mirror-image relationship. 1 is a blue emitter (λem =411 nm) with a photoluminescence quantum efficiency of ΦPL =6 % (cf. tetrathia[7]helicene: λem ≈405 nm, ΦPL =5 %).

Exploring Structure-Property Relations of B,S-Doped Polycyclic Aromatic Hydrocarbons through the Trinity of Synthesis, Spectroscopy, and Theory.

Polycyclic aromatic hydrocarbons (PAHs) are prominent lead structures for organic optoelectronic materials. This work describes the synthesis of three B,S-doped PAHs with heptacene-type scaffolds via nucleophilic aromatic substitution reactions between fluorinated arylborane precursors and 1,2-(Me3SiS)2C6H4/1,8-diazabicyclo[5.4.0]undec-7-ene (72-92% yield). All compounds contain tricoordinate B atoms at their 7,16-positions, kinetically protected by mesityl (Mes) substituents. PAHs 1/2 feature two/four S atoms at their 5,18-/5,9,14,18-positions; PAH 3 is a 6,8,15,17-tetrafluoro derivative of 2. For comparison, we also prepared the skewed naphtho[2,3-c]pentaphene-type isomer 4. The simultaneous presence of electron-accepting B atoms and electron-donating S atoms results in a redox-ambiphilic behavior; the radical cations [1•]+ and [2•]+ were characterized by electron paramagnetic resonance spectroscopy. Several low-lying charge-transfer states exist, some of which (especially S-to-B and Mes-to-B transitions) compete on the excited-state potential-energy surface. Consistent with the calculated state characters and oscillator strengths, this competition results in a spread of fluorescence quantum yields (2-27%). The optoelectronic properties of 1 change drastically upon addition of Ag+ ions: while the color of 1 in CH2Cl2 changes bathochromically from yellow to red (λmax from 463 to 486 nm; -0.13 eV), the emission band shifts hypsochromically from 606 to 545 nm (+0.23 eV), and the fluorescence quantum yield increases from 12 to 43%. According to titration experiments, higher order adducts [Agn1m]n+ are formed. As a suitable system for modeling Ag+ complexation, our calculations predict a dimer structure (n = m = 2) with Ag2S4 core, approximately linear S-Ag-S fragments, and Ag-Ag interaction. The computed optoelectronic properties of [Ag212]2+ agree well with the experimentally observed ones.