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Category: chemistry – Page 3

AI-driven ultrafast spectrometer-on-a-chip advances real-time sensing

For decades, the ability to visualize the chemical composition of materials, whether for diagnosing a disease, assessing food quality, or analyzing pollution, depended on large, expensive laboratory instruments called spectrometers. These devices work by taking light, spreading it out into a rainbow using a prism or grating, and measuring the intensity of each color. The problem is that spreading light requires a long physical path, making the device inherently bulky.

A recent study from the University of California Davis (UC Davis), reported in Advanced Photonics, tackles the challenge of miniaturization, aiming to shrink a lab-grade spectrometer down to the size of a grain of sand, a tiny spectrometer-on-a-chip that can be integrated into portable devices. The traditional approach of spatially spreading light is abandoned in favor of a reconstructive method.

Instead of physically separating each color, the new chip uses only 16 distinct silicon detectors, each engineered to respond slightly differently to incoming light. This is analogous to giving a handful of specialized sensors a mixed drink, with each sensor sampling a different aspect of the drink. The key to deciphering the original recipe is the second part of the invention: artificial intelligence (AI).

Elite army training reveals genetic markers for resilience

A new analysis of soldiers attempting to join the U.S. Army Special Forces suggests that specific genetic variations play a role in how individuals handle extreme physical and mental pressure. The research identified distinct links between a soldier’s DNA and their cognitive performance, psychological resilience, and physiological stress response during a grueling selection course. These findings were published recently in the academic journal Physiology & Behavior.

To become a member of the elite Army Special Forces, a soldier must first pass the Special Forces Assessment and Selection course. This training program is widely recognized as one of the most difficult military evaluations in the world. Candidates must endure nearly three weeks of intense physical exertion. They face sleep deprivation and complex problem-solving exercises. The attrition rate is notoriously high. Approximately 70 percent of the soldiers who attempt the course fail to complete it. This environment creates a unique laboratory for scientists to study human endurance.

Researchers have sought to understand why some individuals thrive in these punishing environments while others struggle. Resilience is generally defined as the ability to adapt positively to adversity, trauma, or threats. It involves a combination of psychological stability and physiological recovery. While physical training and mental preparation are essential, biological factors also play a substantial role. Genetics help determine how the brain regulates chemicals and how the body processes stress hormones.

Catalyst selectivity as a balancing act: Co₃O₄ ‘trapped’ in transition shows peak activity

In a study appearing in Nature Catalysis, researchers from the Inorganic Chemistry Department of the Fritz Haber Institute reveal how structural changes on the surface and in the bulk region of the cobalt oxide catalyst Co3O4 influence its selectivity in the production of industrially relevant chemicals like acetone.

They discovered that a metastable, structurally “trapped” state exhibits the highest catalytic activity—an important finding for catalyst design.

Vibrational spectroscopy technique enables nanoscale mapping of molecular orientation at surfaces

Sum-frequency generation (SFG) is a powerful vibrational spectroscopy that can selectively probe molecular structures at surfaces and interfaces, but its spatial resolution has been limited to the micrometer scale by the diffraction limit of light.

In a study published in The Journal of Physical Chemistry C, investigators overcame this limitation by utilizing a highly confined near field within a plasmonic nanogap and successfully extended the SFG spectroscopy into a nanoscopic regime with ~10-nm spatial resolution.

The team also established a comprehensive theoretical framework that accurately describes the microscopic mechanisms of this near-field SFG process. These experimental and theoretical achievements collectively represent a groundbreaking advancement in near-field second-order nonlinear nanospectroscopy, enabling direct access to correlated chemical and topographic information of interfacial molecular systems at the nanoscale.

Nanoscopic raft dynamics on cell membranes successfully visualized for first time

A collaborative team of four professors and several graduate students from the Departments of Chemistry and Biochemical Science and Technology at National Taiwan University, together with the Department of Applied Chemistry at National Chi Nan University, has achieved a long-sought breakthrough.

By combining atomic force microscopy (AFM) with a Hadamard product–based image reconstruction algorithm, the researchers successfully visualized, for the first time, the nanoscopic dynamics of membrane rafts in live cells—making visible what had long remained invisible on the cell membrane.

Membrane rafts are nanometer-scale structures rich in cholesterol and sphingolipids, believed to serve as vital platforms for cell signaling, viral entry, and cancer metastasis. Since the concept emerged in the 1990s, the existence and behavior of these lipid domains have been intensely debated.

Machine learning can predict patients’ responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical sleeping and/or eating habits, a lack of motivation, a loss of interest in daily activities and unhelpful thought patterns.

There are now various treatments for depression, including psychotherapy-based interventions and different types of antidepressant medications. Identifying the best treatment strategy, however, is not always easy, and many patients try different medications before they find one that works for them.

Researchers at Stanford University, Lehigh University, the University of Texas at Austin and other institutes explored the potential of machine learning techniques, computational models that can identify patterns in data, for predicting the responses of individual patients to two different antidepressants and to a placebo (i.e., a pill that contains no active chemicals).

Soft organic electrochemical neurons operating at biological speed

Organic electrochemical neurons respond to brain signals in real time, firing at biologically relevant speeds. Their flexibility and low power use could enable soft, implantable systems for closed-loop neuromodulation and future brain–computer interfaces.

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Imaging technique captures ultrafast electron and atom dynamics in chemical reactions

During chemical reactions, atoms in the reacting substances break their bonds and re-arrange, forming different chemical products. This process entails the movement of both electrons (i.e., negatively charged particles) and nuclei (i.e., the positively charged central parts of atoms). Valence electrons are shared and re-arranged between different atoms, creating new bonds.

The movements of electrons and nuclei during chemical reactions are incredibly fast, in many cases only lasting millionths of a billionth of a second (i.e., femtoseconds). Yet reliably tracking and understanding these movements could help to shed new light on how specific molecules are formed, as well as on the underpinnings of quantum mechanical phenomena.

Researchers at Shanghai Jiao Tong University recently introduced a new approach to observe chemical reactions as they unfold, precisely tracking the movement of electrons and atomic nuclei as a molecule breaks apart. This strategy, outlined in a paper published in Physical Review Letters, was successfully used to image the photodissociation of ammonia (NH₃), the process in which a NH₃ molecule absorbs light and breaks down into smaller pieces.

Honeycomb lattice sweetens quantum materials development

Researchers at the Department of Energy’s Oak Ridge National Laboratory are pioneering the design and synthesis of quantum materials, which are central to discovery science involving synergies with quantum computation. These innovative materials, including magnetic compounds with honeycomb-patterned lattices, have the potential to host states of matter with exotic behavior.

Using theory, experimentation and computation, scientists synthesized a magnetic honeycomb of potassium cobalt arsenate and conducted the most detailed characterization of the material to date. They discovered that its honeycomb structure is slightly distorted, causing magnetic spins of charged cobalt atoms to strongly couple and align.

Tuning these interactions, such as through chemically modifying the material or applying a large magnetic field, may enable the formation of a state of matter known as a quantum spin liquid. Unlike permanent magnets, in which spins align fixedly, quantum spins do not freeze in one magnetic state.

Biomass-derived furans offer sustainable alternative to petroleum in chemical production

A research project conducted by the Max-Planck-Institut für Kohlenforschung shows how biomass can be used as a raw material for chemical products instead of petroleum. The scientists have published their findings in the journal Science.

The chemical industry is facing major challenges: for reasons of CO2 neutrality, circular economy, and geopolitical instability, there is a desire to move away from petroleum and other fossil materials as raw materials for the production of high-quality chemicals. But how will molecular building blocks for essential medicines, for example, be obtained in the future?

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