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Category: chemistry – Page 5

Scientific Notation Explained | Large & Small Numbers + Practice Questions

Scientific notation is a system developed to represent extremely large and extremely small numbers in a way that is easy to read, write, and understand. In chemistry and physics, many values such as the mass of an electron are too large or too small to be written conveniently in standard notation.

In this video, you will learn:

What scientific notation is and why it is used.
How to write numbers in the form a × 10ⁿ, where a is between 1 and 10
How to convert large numbers into scientific notation.
How to convert small numbers into scientific notation.

The LARS rule:
Left → Add to the exponent.
Right → Subtract from the exponent.

We also discuss how the direction of decimal movement affects the exponent and why the same rules apply to both very large and very small numbers.

📌 At the end of the video, you’ll find practice multiple-choice questions (MCQs) to test your understanding, including a real-life chemistry example involving the mass of an electron.

Continue reading “Scientific Notation Explained | Large & Small Numbers + Practice Questions” | >

Water-based electrolyte helps create safer and long-lasting Zn-Mn batteries

Many countries worldwide are increasingly investing in new infrastructure that enables the production of electricity from renewable energy sources, particularly wind and sunlight. To make the best of these energy solutions, one should also be able to reliably store the excess energy created during periods of intense sunlight or wind, so that it can be used later in times of need.

One promising type of battery for this purpose is based on zinc-manganese (Zn-Mn) and utilizes aqueous (i.e., water-based) electrodes instead of flammable organic electrolytes. These batteries rely on processes known as electrodeposition and dissolution, via which solid materials form and dissolve on electrodes as the battery is charging and discharging.

In Zn-Mn batteries, Zn serves as the anode (i.e., the electrode that releases electrons) and manganese dioxide (MnO₂) the cathode (i.e., the electrode from which electrons are gained). A key chemical reaction prompting their functioning, known as the MnO₂/Mn²⁺ conversion reaction, typically can only occur in acidic conditions.

The origin of magic numbers: Why some atomic nuclei are unusually stable

For the first time, physicists have developed a model that explains the origins of unusually stable magic nuclei based directly on the interactions between their protons and neutrons. Published in Physical Review Letters, the research could help scientists better understand the exotic properties of heavy atomic nuclei and the fundamental forces that hold them together.

While every chemical element is defined by a fixed number of protons in its atomic nucleus, the number of neutrons it contains is far less constrained. For almost every known element, there are at least two different nuclear configurations, or isotopes, which vary only in their number of neutrons.

However, if the number of protons and neutrons becomes too unbalanced in either direction, the nucleus becomes unstable. Since heavier elements tend to have fewer stable isotopes, these radioactive nuclei grow increasingly rare as this imbalance increases. Yet for certain specific numbers of protons and neutrons (collectively known as “nucleons”), some isotopes are found to be exceptionally stable, for reasons that physicists have struggled to fully explain.

Electronic friction can be tuned and switched off

Researchers in China have isolated the effects of electronic friction, showing for the first time how the subtle drag force it imparts at sliding interfaces can be controlled. They demonstrate that it can be tuned by applying a voltage, or switched off entirely simply by applying mechanical pressure. The results, published in Physical Review X, could inform new designs that allow engineers to fine-tune the drag forces materials experience as they slide over each other.

In engineering, friction causes materials to wear and degrade over time, and also causes useful energy to be wasted as heat. While this problem can be mitigated through lubricants and smoother surfaces, friction can also arise from deeper, more subtle effects.

Among these is an effect which can occur at metallic or chemically active surfaces as they slide past one another. In these cases, atomic nuclei in one surface can transfer some of their energy to electrons in the other surface, exciting them to higher energy levels. This lost energy produces a drag force that increases with sliding velocity: an effect known as “electronic friction.”

Scientists reveal formation mechanism behind spherical assemblies of nanocrystals

From table salt to snowflakes, and from gemstones to diamonds—we encounter crystals everywhere in daily life, usually cubic (table salt) or hexagonal (snowflakes). Researchers from Noushine Shahidzadeh’s group at the UvA Institute of Physics now demonstrate how mesmerizing spherical crystal shapes arise through structures called spherulites.

A new study done in Shahidzadeh’s lab at the Institute of Physics / Van der Waals Zeeman-Institute, reveals how neatly ordered (hemi-) spherical or pancake-like structures in nature can emerge from completely disordered salt solutions. Moreover, scientists can now harness these structures to create advanced materials. The work is published in the journal Communications Chemistry.

AI method accelerates liquid simulations by learning fundamental physical relationships

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the chemical potential—an indispensable quantity for describing liquids in thermodynamic equilibrium. The researchers present their findings in a new study published in Physical Review Letters.

Many common AI methods are based on the principle of supervised machine learning: a model—for instance, a neural network—is specifically trained to predict a particular target quantity directly. One example that illustrates this approach is image recognition, where the AI system is shown numerous images in which it is known whether or not a cat is depicted. On this basis, the system learns to identify cats in new, previously unseen images.

“However, such a direct approach is difficult in the case of the chemical potential, because determining it usually requires computationally expensive algorithms,” says Prof. Dr. Matthias Schmidt, Chair of Theoretical Physics II at the University of Bayreuth. He and his research associate Dr. Florian Sammüller address this challenge with their newly developed AI method. It is based on a neural network that incorporates the theoretical structure of liquids—and more generally, of soft matter—allowing it to predict their properties with great accuracy.

Subaru observations suggest an intrinsic gap in NGC 5466’s tidal stream

Astronomers from the National Astronomical Observatory of Japan (NAOJ) and elsewhere have used the Subaru Telescope to perform deep imaging observations of a distant globular cluster known as NGC 5466. The observational campaign yields important information about the structure of the cluster’s tidal stream. The new findings were published February 4 on the arXiv preprint server.

In general, stellar tidal streams are the result of tidal interactions between a central galaxy and lower mass systems such as satellite galaxies or globular clusters (GCs). Therefore, they could keep the memory of their progenitors’ chemical and dynamical information, even after a few billion years.

What honey bee brain chemistry tells us about human learning

A multi-institutional team of researchers led by Virginia Tech’s Fralin Biomedical Research Institute at VTC has for the first time identified specific patterns of brain chemical activity that predict how quickly individual honey bees learn new associations, offering important insights into the biological basis of learning and decision-making. The study, published in Science Advances, found that the balance between the neurotransmitters octopamine and tyramine can predict whether a bee will learn quickly, slowly, or not at all, as they associate an odor with a reward.

Because the same ancient brain chemicals that guide learning in bees also shape attention and learning in people, the findings may help scientists better understand why individual humans learn at different speeds—and how those processes may go awry in a variety of brain disorders.

Specific patterns of brain chemical activity appear before learning begins and again when a learned behavior first emerges, signaling how quickly an individual bee will learn. The research can help explain how chemicals in the brain drive attention and reinforce learning, with implications for fundamental biology, medicine, and agriculture.

Cell Type-Specific Contributions of UBE3A to Angelman Syndrome Behavioral Phenotypes

ENeuro: Ringelberg et al. identify a key role for excitatory neuron loss of UBE3A in motor, innate, and sleep behavioral phenotypes of Angelman syndrome model mice.

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AS is a neurodevelopmental disorder with no disease-modifying treatment. However, clinical trials are currently underway using antisense oligonucleotides to unsilence the dormant paternal UBE3A allele, thereby normalizing UBE3A levels (Ionis: NCT05127226; Ultragenyx: NCT04259281). While this approach holds exciting promise and shows efficacy in mouse models (Meng et al., 2015; Milazzo et al., 2021), there is currently scant information regarding the key cell types or brain regions that require UBE3A reinstatement to mitigate core symptoms of AS. This holds particular importance, as effective biodistribution is a key concern in genetic therapies for CNS disorders (Roberts et al., 2020; Jafar-Nejad et al., 2021; Ling et al., 2023), and suboptimal targeting of necessary cell classes could hamper success. Moreover, mouse models of AS require early postnatal Ube3a reinstatement to achieve optimal phenotypic recovery (Silva-Santos et al., 2015; Sonzogni et al., 2020); early intervention could be difficult to achieve in the patient population without a corresponding early diagnosis, meaning many AS individuals are likely beyond the critical window to maximally benefit from UBE3A reinstatement-based therapies. Therefore, additional work is needed to better understand how loss of UBE3A leads to symptoms, as these insights will aid both in understanding the cell types that must be targeted for optimal genetic interventions and in developing alternative therapeutic options.

Our laboratory’s previous work identified an outsized role of GABAergic loss of UBE3A in hyperexcitability phenotypes. GABAergic loss of UBE3A drives increased delta power on cortical EEG (Judson et al., 2016), a phenotype that correlates with the severity of a range of symptoms in AS individuals (Hipp et al., 2021; Ostrowski et al., 2021). Further, mice with Ube3a deleted from GABAergic neurons show decreased threshold to chemically and acoustically driven seizures, and they also exhibit spontaneous behavioral seizures, a phenotype not observed in AS model mice on a C57BL/6J background (Judson et al., 2016; Gu et al., 2019). These data forewarn that UBE3A reinstatement in a manner biased to glutamatergic neurons could potentially worsen epilepsy-related symptoms and highlight the importance of studying the neuronal populations regulating other behaviors.

Based on the exaggerated role of GABAergic neurons in AS seizure phenotypes, we predicted that GABAergic deletion of Ube3a would underlie a broad range of behavioral phenotypes in AS mice. In the present study, we instead found a larger role of Ube3a deletion from glutamatergic neurons in motor coordination, measured by rotarod and open field behavior, and innate species-specific behaviors such as marble burying. Furthermore, glutamatergic loss of UBE3A appears to mediate alterations in sleep patterning and induces some sleep fragmentation, while UBE3A loss from GABAergic neurons only caused fragmented sleep. Interestingly, glutamatergic reinstatement of Ube3a also rescued the decreased REM sleep observed in AS mice, as estimated by the PiezoSleep system. While this study identified some roles of GABAergic neurons in nest building behavior and sleep fragmentation, our data largely suggest a divergence of the neural circuitry underlying the motor, innate behavior, and sleep phenotypes of AS mice from the circuitry responsible for seizure susceptibility and cortical EEG patterns.

New laser “comb” can enable rapid identification of chemicals with extreme precision

Researchers demonstrated a broadband infrared frequency comb that can operate stably, efficiently, and accurately without the need for bulky external components. The device could be utilized in a remote sensor or portable mass spectrometer that can track and monitor multiple chemicals in real-time for extended periods.

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